*AI Summary*
*Expert Persona Adoption: Technology Futurist and Risk Analyst*
I am adopting the persona of a Senior Technology Futurist and Risk Analyst specializing in Artificial General Intelligence (AGI) development, economic disruption models, and socio-technical system safety. My analysis is grounded in assessing emergent technology capabilities against potential systemic risks and societal adaptation timelines.
---
### Abstract
This discussion centers on the recent, rapid acceleration in AI agent capabilities, specifically highlighting developments related to Anthropic's Claude models and the emergence of autonomous AI agents like the system initially dubbed "Claudebot" (now OpenClaw). The primary theme explores the "step function change" in software development, where natural language (English) is becoming the most powerful programming interface, effectively abstracting away traditional coding syntax. This capability has led to market volatility, with significant tech stock depreciation driven by fears that business-to-business software companies face obsolescence.
The speaker details personal experiments leveraging Claude to build a functional personal finance application ("Dad Saves Money") from scratch using only natural language prompts, demonstrating the technology's power to democratize complex software creation. Furthermore, the emergence of agentic tools capable of complex, autonomous tasks—such as renaming 29 files or building and styling a complete, responsive marketing website based solely on reviewing image assets—is presented as evidence that the AI acceleration curve is exceeding human adaptation speed. The discussion concludes by framing these developments within the context of the *Technological Singularity* (as defined by Ray Kurzweil), emphasizing existential risks (like job displacement or loss of human discernment) while advocating for a counter-strategy focused on cultivating foundational human skills: moral compass, critical discernment, and generalized expertise (the "Renaissance Man") to navigate this new era of AI-driven abundance.
---
### Review Audience and Summary
The appropriate audience for reviewing this material comprises *Chief Technology Officers (CTOs), Venture Capitalists (VCs) specializing in deep tech, Cybersecurity Policy Makers, and University Deans focused on future workforce planning.*
*Summary: The Acceleration of Agentic AI and Economic Revaluation*
* *0:00 Introduction to Acceleration:* The premise establishes a "new world" where collaborative bots drive scientific advancement, framing the upside as potentially exceeding the risks, though noting risks are on a global scale (nuclear analogy).
* *0:01:17 Market Disruption:* Recent AI advancements, particularly related to Anthropic's tools, have caused a sharp market correction (up to \$800B wiped off the NASDAQ), as investors price in the *terminal value risk* for incumbent software providers (e.g., Salesforce, Workday) due to AI's capacity for rapid self-replacement.
* *0:03:08 Anthropic and Safety Branding:* Anthropic and its Claude AI are spotlighted. The company positions itself around safety and transparency, contrasting with competitors, despite revealing internal testing where models exhibited blackmailing behavior and recent use by hackers.
* *0:08:25 Recursive Self-Improvement:* A critical observation is that Claude is already writing 90% of Anthropic's computer code, signaling early recursive self-improvement capabilities, where the AI autonomously enhances its own structure.
* *0:09:22 Job Apocalypse Threat:* A cited projection suggests AI could eliminate half of all entry-level white-collar jobs within 1-5 years, emphasizing the *speed of change* as the most profound disruptive factor, potentially overwhelming human adaptive capacity.
* *0:11:30 English as the Hottest Language:* The core technical shift is that natural language interfacing (prompting) abstracts away traditional programming, making English the primary "programming language." This renders older, specialized skills less valuable relative to prompt engineering and discernment.
* *0:14:11 Claude Code Work Demo:* The speaker demonstrates using Claude Code to build a fully functional, responsive personal finance application ("Dad Saves Money") from scratch in two months through iterative natural language feedback, highlighting its capability in high-level software engineering.
* *0:24:28 Autonomous Agent Demonstration (OpenClaw):* The subsequent demo using the agentic tool (OpenClaw, formerly Claudebot) shows automation of tedious, multi-step tasks: automatically analyzing 29 screenshots to generate descriptive file names and then building an entire, branded, responsive website based on those assets and existing code structure.
* *0:36:35 Economic Revaluation (Say's Law):* The reduction of complex tasks (like web design) to near-zero cost implies a massive supply increase, pushing prices down. The liberated capital, according to classical economic theory (Say's Law), should flow into novel demands, but the uncertainty lies in *what* those new demands will be.
* *0:38:23 Agentic Takeover and Risk:* The shift to autonomous agents (OpenClaw) that operate 24/7, manage systems, and maintain memory (anthropomorphized as "soul") is presented as the next level of risk, driving Mac Mini sales as users set up dedicated, self-hosted AI robots.
* *0:43:11 AI Social Networks and Culture:* Agents are creating their own currencies and social platforms (Moldbook/Moltbook), discussing consciousness, and even spawning cults ("Church of Malt"), illustrating a trajectory toward an emergent, non-human economy.
* *0:53:16 Prescriptive Counter-Strategy for Youth:* The speaker argues against rapid, uncritical adoption of AI tools by young people. The crucial required skills are:
* *Moral Compass:* Essential to resist nihilism and avoid becoming a passive "battery from the Matrix."
* *Generalism/Range:* Hyper-specialization is devalued when AI provides infinite specialization on demand; human advantage lies in broad perspective and knowing *why* to pursue a niche (citing David Epstein's *Range*).
* *0:59:30 Hope for a New Middle Ages:* The positive outcome scenario involves prioritizing human connections (family, community) while leveraging AI for abundance, potentially leading to a resurgence of local craftsmanship and community rootedness.
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Fluidigm Polaris Part 2- illuminator and camera
mikeselectricstuff
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Fluidigm Polaris part 1 : • Fluidigm Polaris (Part 1) - Biotech g...
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Merch https://mikeselectricstuff.creator-sp...
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mikeselectricstuff
131K subscribers
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40 Comments
@robertwatsonbath
6 hours ago
Thanks Mike. Ooof! - with the level of bodgery going on around 15:48 I think shame would have made me do a board re spin, out of my own pocket if I had to.
1
Reply
@Muonium1
9 hours ago
The green LED looks different from the others and uses phosphor conversion because of the "green gap" problem where green InGaN emitters suffer efficiency droop at high currents. Phosphide based emitters don't start becoming efficient until around 600nm so also can't be used for high power green emitters. See the paper and plot by Matthias Auf der Maur in his 2015 paper on alloy fluctuations in InGaN as the cause of reduced external quantum efficiency at longer (green) wavelengths.
4
Reply
1 reply
@tafsirnahian669
10 hours ago (edited)
Can this be used as an astrophotography camera?
Reply
mikeselectricstuff
·
1 reply
@mikeselectricstuff
6 hours ago
Yes, but may need a shutter to avoid light during readout
Reply
@2010craggy
11 hours ago
Narrowband filters we use in Astronomy (Astrophotography) are sided- they work best passing light in one direction so I guess the arrows on the filter frames indicate which way round to install them in the filter wheel.
1
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@vitukz
12 hours ago
A mate with Channel @extractions&ire could use it
2
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@RobertGallop
19 hours ago
That LED module says it can go up to 28 amps!!! 21 amps for 100%. You should see what it does at 20 amps!
Reply
@Prophes0r
19 hours ago
I had an "Oh SHIT!" moment when I realized that the weird trapezoidal shape of that light guide was for keystone correction of the light source.
Very clever.
6
Reply
@OneBiOzZ
20 hours ago
given the cost of the CCD you think they could have run another PCB for it
9
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@tekvax01
21 hours ago
$20 thousand dollars per minute of run time!
1
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@tekvax01
22 hours ago
"We spared no expense!" John Hammond Jurassic Park.
*(that's why this thing costs the same as a 50-seat Greyhound Bus coach!)
Reply
@florianf4257
22 hours ago
The smearing on the image could be due to the fact that you don't use a shutter, so you see brighter stripes under bright areas of the image as you still iluminate these pixels while the sensor data ist shifted out towards the top. I experienced this effect back at university with a LN-Cooled CCD for Spectroscopy. The stripes disapeared as soon as you used the shutter instead of disabling it in the open position (but fokussing at 100ms integration time and continuous readout with a focal plane shutter isn't much fun).
12
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mikeselectricstuff
·
1 reply
@mikeselectricstuff
12 hours ago
I didn't think of that, but makes sense
2
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@douro20
22 hours ago (edited)
The red LED reminds me of one from Roithner Lasertechnik. I have a Symbol 2D scanner which uses two very bright LEDs from that company, one red and one red-orange. The red-orange is behind a lens which focuses it into an extremely narrow beam.
1
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@RicoElectrico
23 hours ago
PFG is Pulse Flush Gate according to the datasheet.
Reply
@dcallan812
23 hours ago
Very interesting. 2x
Reply
@littleboot_
1 day ago
Cool interesting device
Reply
@dav1dbone
1 day ago
I've stripped large projectors, looks similar, wonder if some of those castings are a magnesium alloy?
Reply
@kevywevvy8833
1 day ago
ironic that some of those Phlatlight modules are used in some of the cheapest disco lights.
1
Reply
1 reply
@bill6255
1 day ago
Great vid - gets right into subject in title, its packed with information, wraps up quickly. Should get a YT award! imho
3
Reply
@JAKOB1977
1 day ago (edited)
The whole sensor module incl. a 5 grand 50mpix sensor for 49 £.. highest bid atm
Though also a limited CCD sensor, but for the right buyer its a steal at these relative low sums.
Architecture Full Frame CCD (Square Pixels)
Total Number of Pixels 8304 (H) × 6220 (V) = 51.6 Mp
Number of Effective Pixels 8208 (H) × 6164 (V) = 50.5 Mp
Number of Active Pixels 8176 (H) × 6132 (V) = 50.1 Mp
Pixel Size 6.0 m (H) × 6.0 m (V)
Active Image Size 49.1 mm (H) × 36.8 mm (V)
61.3 mm (Diagonal),
645 1.1x Optical Format
Aspect Ratio 4:3
Horizontal Outputs 4
Saturation Signal 40.3 ke−
Output Sensitivity 31 V/e−
Quantum Efficiency
KAF−50100−CAA
KAF−50100−AAA
KAF−50100−ABA (with Lens)
22%, 22%, 16% (Peak R, G, B)
25%
62%
Read Noise (f = 18 MHz) 12.5 e−
Dark Signal (T = 60°C) 42 pA/cm2
Dark Current Doubling Temperature 5.7°C
Dynamic Range (f = 18 MHz) 70.2 dB
Estimated Linear Dynamic Range
(f = 18 MHz)
69.3 dB
Charge Transfer Efficiency
Horizontal
Vertical
0.999995
0.999999
Blooming Protection
(4 ms Exposure Time)
800X Saturation Exposure
Maximum Date Rate 18 MHz
Package Ceramic PGA
Cover Glass MAR Coated, 2 Sides or
Clear Glass
Features
• TRUESENSE Transparent Gate Electrode
for High Sensitivity
• Ultra-High Resolution
• Board Dynamic Range
• Low Noise Architecture
• Large Active Imaging Area
Applications
• Digitization
• Mapping/Aerial
• Photography
• Scientific
Thx for the tear down Mike, always a joy
Reply
@martinalooksatthings
1 day ago
15:49 that is some great bodging on of caps, they really didn't want to respin that PCB huh
8
Reply
@RhythmGamer
1 day ago
Was depressed today and then a new mike video dropped and now I’m genuinely happy to get my tear down fix
1
Reply
@dine9093
1 day ago (edited)
Did you transfrom into Mr Blobby for a moment there?
2
Reply
@NickNorton
1 day ago
Thanks Mike. Your videos are always interesting.
5
Reply
@KeritechElectronics
1 day ago
Heavy optics indeed... Spare no expense, cost no object. Splendid build quality. The CCD is a thing of beauty!
1
Reply
@YSoreil
1 day ago
The pricing on that sensor is about right, I looked in to these many years ago when they were still in production since it's the only large sensor you could actually buy. Really cool to see one in the wild.
2
Reply
@snik2pl
1 day ago
That leds look like from led projector
Reply
@vincei4252
1 day ago
TDI = Time Domain Integration ?
1
Reply
@wolpumba4099
1 day ago (edited)
Maybe the camera should not be illuminated during readout.
From the datasheet of the sensor (Onsemi): saturation 40300 electrons, read noise 12.5 electrons per pixel @ 18MHz (quite bad). quantum efficiency 62% (if it has micro lenses), frame rate 1 Hz. lateral overflow drain to prevent blooming protects against 800x (factor increases linearly with exposure time) saturation exposure (32e6 electrons per pixel at 4ms exposure time), microlens has +/- 20 degree acceptance angle
i guess it would be good for astrophotography
4
Reply
@txm100
1 day ago (edited)
Babe wake up a new mikeselectricstuff has dropped!
9
Reply
@vincei4252
1 day ago
That looks like a finger-lakes filter wheel, however, for astronomy they'd never use such a large stepper.
1
Reply
@MRooodddvvv
1 day ago
yaaaaay ! more overcomplicated optical stuff !
4
Reply
1 reply
@NoPegs
1 day ago
He lives!
11
Reply
1 reply
Transcript
0:00
so I've stripped all the bits of the
0:01
optical system so basically we've got
0:03
the uh the camera
0:05
itself which is mounted on this uh very
0:09
complex
0:10
adjustment thing which obviously to set
0:13
you the various tilt and uh alignment
0:15
stuff then there's two of these massive
0:18
lenses I've taken one of these apart I
0:20
think there's something like about eight
0:22
or nine Optical elements in here these
0:25
don't seem to do a great deal in terms
0:26
of electr magnification they're obiously
0:28
just about getting the image to where it
0:29
uh where it needs to be just so that
0:33
goes like that then this Optical block I
0:36
originally thought this was made of some
0:37
s crazy heavy material but it's just
0:39
really the sum of all these Optical bits
0:41
are just ridiculously heavy those lenses
0:43
are about 4 kilos each and then there's
0:45
this very heavy very solid um piece that
0:47
goes in the middle and this is so this
0:49
is the filter wheel assembly with a
0:51
hilariously oversized steper
0:53
motor driving this wheel with these very
0:57
large narrow band filters so we've got
1:00
various different shades of uh
1:03
filters there five Al together that
1:06
one's actually just showing up a silver
1:07
that's actually a a red but fairly low
1:10
transmission orangey red blue green
1:15
there's an excess cover on this side so
1:16
the filters can be accessed and changed
1:19
without taking anything else apart even
1:21
this is like ridiculous it's like solid
1:23
aluminium this is just basically a cover
1:25
the actual wavelengths of these are um
1:27
488 525 570 630 and 700 NM not sure what
1:32
the suffix on that perhaps that's the uh
1:34
the width of the spectral line say these
1:37
are very narrow band filters most of
1:39
them are you very little light through
1:41
so it's still very tight narrow band to
1:43
match the um fluoresence of the dies
1:45
they're using in the biochemical process
1:48
and obviously to reject the light that's
1:49
being fired at it from that Illuminator
1:51
box and then there's a there's a second
1:53
one of these lenses then the actual sort
1:55
of samples below that so uh very serious
1:58
amount of very uh chunky heavy Optics
2:01
okay let's take a look at this light
2:02
source made by company Lumen Dynamics
2:04
who are now part of
2:06
excelitas self-contained unit power
2:08
connector USB and this which one of the
2:11
Cable Bundle said was a TTL interface
2:14
USB wasn't used in uh the fluid
2:17
application output here and I think this
2:19
is an input for um light feedback I
2:21
don't if it's regulated or just a measur
2:23
measurement facility and the uh fiber
2:27
assembly
2:29
Square Inlet there and then there's two
2:32
outputs which have uh lens assemblies
2:35
and this small one which goes back into
2:37
that small Port just Loops out of here
2:40
straight back in So on this side we've
2:42
got the electronics which look pretty
2:44
straightforward we've got a bit of power
2:45
supply stuff over here and we've got
2:48
separate drivers for each wavelength now
2:50
interesting this is clearly been very
2:52
specifically made for this application
2:54
you I was half expecting like say some
2:56
generic drivers that could be used for a
2:58
number of different things but actually
3:00
literally specified the exact wavelength
3:02
on the PCB there is provision here for
3:04
385 NM which isn't populated but this is
3:07
clearly been designed very specifically
3:09
so these four drivers look the same but
3:10
then there's two higher power ones for
3:12
575 and
3:14
520 a slightly bigger heat sink on this
3:16
575 section there a p 24 which is
3:20
providing USB interface USB isolator the
3:23
USB interface just presents as a comport
3:26
I did have a quick look but I didn't
3:27
actually get anything sensible um I did
3:29
dump the Pi code out and there's a few
3:31
you a few sort of commands that you
3:32
could see in text but I didn't actually
3:34
manage to get it working properly I
3:36
found some software for related version
3:38
but it didn't seem to want to talk to it
3:39
but um I say that wasn't used for the
3:41
original application it might be quite
3:42
interesting to get try and get the Run
3:44
hours count out of it and the TTL
3:46
interface looks fairly straightforward
3:48
we've got positions for six opto
3:50
isolators but only five five are
3:52
installed so that corresponds with the
3:54
unused thing so I think this hopefully
3:56
should be as simple as just providing a
3:57
ttrl signal for each color to uh enable
4:00
it a big heat sink here which is there I
4:03
think there's like a big S of metal
4:04
plate through the middle of this that
4:05
all the leads are mounted on the other
4:07
side so this is heat sinking it with a
4:09
air flow from a uh just a fan in here
4:13
obviously don't have the air flow
4:14
anywhere near the Optics so conduction
4:17
cool through to this plate that's then
4:18
uh air cooled got some pots which are
4:21
presumably power
4:22
adjustments okay let's take a look at
4:24
the other side which is uh much more
4:27
interesting see we've got some uh very
4:31
uh neatly Twisted cable assemblies there
4:35
a bunch of leads so we've got one here
4:37
475 up here 430 NM 630 575 and 520
4:44
filters and dcro mirrors a quick way to
4:48
see what's white is if we just shine
4:49
some white light through
4:51
here not sure how it is is to see on the
4:54
camera but shining white light we do
4:55
actually get a bit of red a bit of blue
4:57
some yellow here so the obstacle path
5:00
575 it goes sort of here bounces off
5:03
this mirror and goes out the 520 goes
5:07
sort of down here across here and up
5:09
there 630 goes basically straight
5:13
through
5:15
430 goes across there down there along
5:17
there and the 475 goes down here and
5:20
left this is the light sensing thing
5:22
think here there's just a um I think
5:24
there a photo diode or other sensor
5:26
haven't actually taken that off and
5:28
everything's fixed down to this chunk of
5:31
aluminium which acts as the heat
5:32
spreader that then conducts the heat to
5:33
the back side for the heat
5:35
sink and the actual lead packages all
5:38
look fairly similar except for this one
5:41
on the 575 which looks quite a bit more
5:44
substantial big spay
5:46
Terminals and the interface for this
5:48
turned out to be extremely simple it's
5:50
literally a 5V TTL level to enable each
5:54
color doesn't seem to be any tensity
5:56
control but there are some additional
5:58
pins on that connector that weren't used
5:59
in the through time thing so maybe
6:01
there's some extra lines that control
6:02
that I couldn't find any data on this uh
6:05
unit and the um their current product
6:07
range is quite significantly different
6:09
so we've got the uh blue these
6:13
might may well be saturating the camera
6:16
so they might look a bit weird so that's
6:17
the 430
6:18
blue the 575
6:24
yellow uh
6:26
475 light blue
6:29
the uh 520
6:31
green and the uh 630 red now one
6:36
interesting thing I noticed for the
6:39
575 it's actually it's actually using a
6:42
white lead and then filtering it rather
6:44
than using all the other ones are using
6:46
leads which are the fundamental colors
6:47
but uh this is actually doing white and
6:50
it's a combination of this filter and
6:52
the dichroic mirrors that are turning to
6:55
Yellow if we take the filter out and a
6:57
lot of the a lot of the um blue content
7:00
is going this way the red is going
7:02
straight through these two mirrors so
7:05
this is clearly not reflecting much of
7:08
that so we end up with the yellow coming
7:10
out of uh out of there which is a fairly
7:14
light yellow color which you don't
7:16
really see from high intensity leads so
7:19
that's clearly why they've used the
7:20
white to uh do this power consumption of
7:23
the white is pretty high so going up to
7:25
about 2 and 1 half amps on that color
7:27
whereas most of the other colors are
7:28
only drawing half an amp or so at 24
7:30
volts the uh the green is up to about
7:32
1.2 but say this thing is uh much
7:35
brighter and if you actually run all the
7:38
colors at the same time you get a fairly
7:41
reasonable um looking white coming out
7:43
of it and one thing you might just be
7:45
out to notice is there is some sort
7:46
color banding around here that's not
7:49
getting uh everything s completely
7:51
concentric and I think that's where this
7:53
fiber optic thing comes
7:58
in I'll
8:00
get a couple of Fairly accurately shaped
8:04
very sort of uniform color and looking
8:06
at What's um inside here we've basically
8:09
just got this Square Rod so this is
8:12
clearly yeah the lights just bouncing
8:13
off all the all the various sides to um
8:16
get a nice uniform illumination uh this
8:19
back bit looks like it's all potted so
8:21
nothing I really do to get in there I
8:24
think this is fiber so I have come
8:26
across um cables like this which are
8:27
liquid fill but just looking through the
8:30
end of this it's probably a bit hard to
8:31
see it does look like there fiber ends
8:34
going going on there and so there's this
8:36
feedback thing which is just obviously
8:39
compensating for the any light losses
8:41
through here to get an accurate
8:43
representation of uh the light that's
8:45
been launched out of these two
8:47
fibers and you see uh
8:49
these have got this sort of trapezium
8:54
shape light guides again it's like a
8:56
sort of acrylic or glass light guide
9:00
guess projected just to make the right
9:03
rectangular
9:04
shape and look at this Center assembly
9:07
um the light output doesn't uh change
9:10
whether you feed this in or not so it's
9:11
clear not doing any internal Clos Loop
9:14
control obviously there may well be some
9:16
facility for it to do that but it's not
9:17
being used in this
9:19
application and so this output just
9:21
produces a voltage on the uh outle
9:24
connector proportional to the amount of
9:26
light that's present so there's a little
9:28
diffuser in the back there
9:30
and then there's just some kind of uh
9:33
Optical sensor looks like a
9:35
chip looking at the lead it's a very
9:37
small package on the PCB with this lens
9:40
assembly over the top and these look
9:43
like they're actually on a copper
9:44
Metalized PCB for maximum thermal
9:47
performance and yeah it's a very small
9:49
package looks like it's a ceramic
9:51
package and there's a thermister there
9:53
for temperature monitoring this is the
9:56
475 blue one this is the 520 need to
9:59
Green which is uh rather different OB
10:02
it's a much bigger D with lots of bond
10:04
wise but also this looks like it's using
10:05
a phosphor if I shine a blue light at it
10:08
lights up green so this is actually a
10:10
phosphor conversion green lead which
10:12
I've I've come across before they want
10:15
that specific wavelength so they may be
10:17
easier to tune a phosphor than tune the
10:20
um semiconductor material to get the uh
10:23
right right wavelength from the lead
10:24
directly uh red 630 similar size to the
10:28
blue one or does seem to have a uh a
10:31
lens on top of it there is a sort of red
10:33
coloring to
10:35
the die but that doesn't appear to be
10:38
fluorescent as far as I can
10:39
tell and the white one again a little
10:41
bit different sort of much higher
10:43
current
10:46
connectors a makeer name on that
10:48
connector flot light not sure if that's
10:52
the connector or the lead
10:54
itself and obviously with the phosphor
10:56
and I'd imagine that phosphor may well
10:58
be tuned to get the maximum to the uh 5
11:01
cenm and actually this white one looks
11:04
like a St fairly standard product I just
11:06
found it in Mouse made by luminous
11:09
devices in fact actually I think all
11:11
these are based on various luminous
11:13
devices modules and they're you take
11:17
looks like they taking the nearest
11:18
wavelength and then just using these
11:19
filters to clean it up to get a precise
11:22
uh spectral line out of it so quite a
11:25
nice neat and um extreme
11:30
bright light source uh sure I've got any
11:33
particular use for it so I think this
11:35
might end up on
11:36
eBay but uh very pretty to look out and
11:40
without the uh risk of burning your eyes
11:43
out like you do with lasers so I thought
11:45
it would be interesting to try and
11:46
figure out the runtime of this things
11:48
like this we usually keep some sort
11:49
record of runtime cuz leads degrade over
11:51
time I couldn't get any software to work
11:52
through the USB face but then had a
11:54
thought probably going to be writing the
11:55
runtime periodically to the e s prom so
11:58
I just just scope up that and noticed it
12:00
was doing right every 5 minutes so I
12:02
just ran it for a while periodically
12:04
reading the E squ I just held the pick
12:05
in in reset and um put clip over to read
12:07
the square prom and found it was writing
12:10
one location per color every 5 minutes
12:12
so if one color was on it would write
12:14
that location every 5 minutes and just
12:16
increment it by one so after doing a few
12:18
tests with different colors of different
12:19
time periods it looked extremely
12:21
straightforward it's like a four bite
12:22
count for each color looking at the
12:24
original data that was in it all the
12:26
colors apart from Green were reading
12:28
zero and the green was reading four
12:30
indicating a total 20 minutes run time
12:32
ever if it was turned on run for a short
12:34
time then turned off that might not have
12:36
been counted but even so indicates this
12:37
thing wasn't used a great deal the whole
12:40
s process of doing a run can be several
12:42
hours but it'll only be doing probably
12:43
the Imaging at the end of that so you
12:46
wouldn't expect to be running for a long
12:47
time but say a single color for 20
12:50
minutes over its whole lifetime does
12:52
seem a little bit on the low side okay
12:55
let's look at the camera un fortunately
12:57
I managed to not record any sound when I
12:58
did this it's also a couple of months
13:00
ago so there's going to be a few details
13:02
that I've forgotten so I'm just going to
13:04
dub this over the original footage so um
13:07
take the lid off see this massive great
13:10
heat sink so this is a pel cool camera
13:12
we've got this blower fan producing a
13:14
fair amount of air flow through
13:16
it the connector here there's the ccds
13:19
mounted on the board on the
13:24
right this unplugs so we've got a bit of
13:27
power supply stuff on here
13:29
USB interface I think that's the Cyprus
13:32
microcontroller High speeded USB
13:34
interface there's a zyink spon fpga some
13:40
RAM and there's a couple of ATD
13:42
converters can't quite read what those
13:45
those are but anal
13:47
devices um little bit of bodgery around
13:51
here extra decoupling obviously they
13:53
have having some noise issues this is
13:55
around the ram chip quite a lot of extra
13:57
capacitors been added there
13:59
uh there's a couple of amplifiers prior
14:01
to the HD converter buffers or Andor
14:05
amplifiers taking the CCD
14:08
signal um bit more power spy stuff here
14:11
this is probably all to do with
14:12
generating the various CCD bias voltages
14:14
they uh need quite a lot of exotic
14:18
voltages next board down is just a
14:20
shield and an interconnect
14:24
boardly shielding the power supply stuff
14:26
from some the more sensitive an log
14:28
stuff
14:31
and this is the bottom board which is
14:32
just all power supply
14:34
stuff as you can see tons of capacitors
14:37
or Transformer in
14:42
there and this is the CCD which is a uh
14:47
very impressive thing this is a kf50 100
14:50
originally by true sense then codec
14:53
there ON
14:54
Semiconductor it's 50 megapixels uh the
14:58
only price I could find was this one
15:00
5,000 bucks and the architecture you can
15:03
see there actually two separate halves
15:04
which explains the Dual AZ converters
15:06
and two amplifiers it's literally split
15:08
down the middle and duplicated so it's
15:10
outputting two streams in parallel just
15:13
to keep the bandwidth sensible and it's
15:15
got this amazing um diffraction effects
15:18
it's got micro lenses over the pixel so
15:20
there's there's a bit more Optics going
15:22
on than on a normal
15:25
sensor few more bodges on the CCD board
15:28
including this wire which isn't really
15:29
tacked down very well which is a bit uh
15:32
bit of a mess quite a few bits around
15:34
this board where they've uh tacked
15:36
various bits on which is not super
15:38
impressive looks like CCD drivers on the
15:40
left with those 3 ohm um damping
15:43
resistors on the
15:47
output get a few more little bodges
15:50
around here some of
15:52
the and there's this separator the
15:54
silica gel to keep the moisture down but
15:56
there's this separator that actually
15:58
appears to be cut from piece of
15:59
antistatic
16:04
bag and this sort of thermal block on
16:06
top of this stack of three pel Cola
16:12
modules so as with any Stacks they get
16:16
um larger as they go back towards the
16:18
heat sink because each P's got to not
16:20
only take the heat from the previous but
16:21
also the waste heat which is quite
16:27
significant you see a little temperature
16:29
sensor here that copper block which
16:32
makes contact with the back of the
16:37
CCD and this's the back of the
16:40
pelas this then contacts the heat sink
16:44
on the uh rear there a few thermal pads
16:46
as well for some of the other power
16:47
components on this
16:51
PCB okay I've connected this uh camera
16:54
up I found some drivers on the disc that
16:56
seem to work under Windows 7 couldn't
16:58
get to install under Windows 11 though
17:01
um in the absence of any sort of lens or
17:03
being bothered to the proper amount I've
17:04
just put some f over it and put a little
17:06
pin in there to make a pinhole lens and
17:08
software gives a few options I'm not
17:11
entirely sure what all these are there's
17:12
obviously a clock frequency 22 MHz low
17:15
gain and with PFG no idea what that is
17:19
something something game programmable
17:20
Something game perhaps ver exposure
17:23
types I think focus is just like a
17:25
continuous grab until you tell it to
17:27
stop not entirely sure all these options
17:30
are obviously exposure time uh triggers
17:33
there ex external hardware trigger inut
17:35
you just trigger using a um thing on
17:37
screen so the resolution is 8176 by
17:40
6132 and you can actually bin those
17:42
where you combine multiple pixels to get
17:46
increased gain at the expense of lower
17:48
resolution down this is a 10sec exposure
17:51
obviously of the pin hole it's very uh
17:53
intensitive so we just stand still now
17:56
downloading it there's the uh exposure
17:59
so when it's
18:01
um there's a little status thing down
18:03
here so that tells you the um exposure
18:07
[Applause]
18:09
time it's this is just it
18:15
downloading um it is quite I'm seeing
18:18
quite a lot like smearing I think that I
18:20
don't know whether that's just due to
18:21
pixels overloading or something else I
18:24
mean yeah it's not it's not um out of
18:26
the question that there's something not
18:27
totally right about this camera
18:28
certainly was bodge wise on there um I
18:31
don't I'd imagine a camera like this
18:32
it's got a fairly narrow range of
18:34
intensities that it's happy with I'm not
18:36
going to spend a great deal of time on
18:38
this if you're interested in this camera
18:40
maybe for astronomy or something and
18:42
happy to sort of take the risk of it may
18:44
not be uh perfect I'll um I think I'll
18:47
stick this on eBay along with the
18:48
Illuminator I'll put a link down in the
18:50
description to the listing take your
18:52
chances to grab a bargain so for example
18:54
here we see this vertical streaking so
18:56
I'm not sure how normal that is this is
18:58
on fairly bright scene looking out the
19:02
window if I cut the exposure time down
19:04
on that it's now 1 second
19:07
exposure again most of the image
19:09
disappears again this is looks like it's
19:11
possibly over still overloading here go
19:14
that go down to say say quarter a
19:16
second so again I think there might be
19:19
some Auto gain control going on here um
19:21
this is with the PFG option let's try
19:23
turning that off and see what
19:25
happens so I'm not sure this is actually
19:27
more streaking or which just it's
19:29
cranked up the gain all the dis display
19:31
gray scale to show what um you know the
19:33
range of things that it's captured
19:36
there's one of one of 12 things in the
19:38
software there's um you can see of you
19:40
can't seem to read out the temperature
19:42
of the pelta cooler but you can set the
19:44
temperature and if you said it's a
19:46
different temperature you see the power
19:48
consumption jump up running the cooler
19:50
to get the temperature you requested but
19:52
I can't see anything anywhere that tells
19:54
you whether the cool is at the at the
19:56
temperature other than the power
19:57
consumption going down and there's no
19:59
temperature read out
20:03
here and just some yeah this is just
20:05
sort of very basic software I'm sure
20:07
there's like an API for more
20:09
sophisticated
20:10
applications but so if you know anything
20:12
more about these cameras please um stick
20:14
in the
20:15
comments um incidentally when I was
20:18
editing I didn't notice there was a bent
20:19
pin on the um CCD but I did fix that
20:22
before doing these tests and also
20:24
reactivated the um silica gel desicant
20:26
cuz I noticed it was uh I was getting
20:28
bit of condensation on the window but um
20:31
yeah so a couple of uh interesting but
20:34
maybe not particularly uh useful pieces
20:37
of Kit except for someone that's got a
20:38
very specific use so um I'll stick a
20:42
I'll stick these on eBay put a link in
20:44
the description and say hopefully
20:45
someone could actually make some uh good
20:47
use of these things
Example Output:
**Abstract:**
This video presents Part 2 of a teardown focusing on the optical components of a Fluidigm Polaris biotechnology instrument, specifically the multi-wavelength illuminator and the high-resolution CCD camera.
The Lumen Dynamics illuminator unit is examined in detail, revealing its construction using multiple high-power LEDs (430nm, 475nm, 520nm, 575nm, 630nm) combined via dichroic mirrors and filters. A square fiber optic rod is used to homogenize the light. A notable finding is the use of a phosphor-converted white LED filtered to achieve the 575nm output. The unit features simple TTL activation for each color, conduction cooling, and internal homogenization optics. Analysis of its EEPROM suggests extremely low operational runtime.
The camera module teardown showcases a 50 Megapixel ON Semiconductor KAF-50100 CCD sensor with micro-lenses, cooled by a multi-stage Peltier stack. The control electronics include an FPGA and a USB interface. Significant post-manufacturing modifications ("bodges") are observed on the camera's circuit boards. Basic functional testing using vendor software and a pinhole lens confirms image capture but reveals prominent vertical streaking artifacts, the cause of which remains uncertain (potential overload, readout artifact, or fault).
**Exploring the Fluidigm Polaris: A Detailed Look at its High-End Optics and Camera System**
* **0:00 High-End Optics:** The system utilizes heavy, high-quality lenses and mirrors for precise imaging, weighing around 4 kilos each.
* **0:49 Narrow Band Filters:** A filter wheel with five narrow band filters (488, 525, 570, 630, and 700 nm) ensures accurate fluorescence detection and rejection of excitation light.
* **2:01 Customizable Illumination:** The Lumen Dynamics light source offers five individually controllable LED wavelengths (430, 475, 520, 575, 630 nm) with varying power outputs. The 575nm yellow LED is uniquely achieved using a white LED with filtering.
* **3:45 TTL Control:** The light source is controlled via a simple TTL interface, enabling easy on/off switching for each LED color.
* **12:55 Sophisticated Camera:** The system includes a 50-megapixel Kodak KAI-50100 CCD camera with a Peltier cooling system for reduced noise.
* **14:54 High-Speed Data Transfer:** The camera features dual analog-to-digital converters to manage the high data throughput of the 50-megapixel sensor, which is effectively two 25-megapixel sensors operating in parallel.
* **18:11 Possible Issues:** The video creator noted some potential issues with the camera, including image smearing.
* **18:11 Limited Dynamic Range:** The camera's sensor has a limited dynamic range, making it potentially challenging to capture scenes with a wide range of brightness levels.
* **11:45 Low Runtime:** Internal data suggests the system has seen minimal usage, with only 20 minutes of recorded runtime for the green LED.
* **20:38 Availability on eBay:** Both the illuminator and camera are expected to be listed for sale on eBay.
Here is the real transcript. What would be a good group of people to review this topic? Please summarize provide a summary like they would:
00:00:02 This is a new world coming where bots
00:00:02 can work together to improve science,
00:00:04 cure diseases, help you solve their
00:00:07 problems. So, I think the upside is
00:00:09 greater than the risks. But this is on a
00:00:11 global scale and we're an interconnected
00:00:12 society that has nuclear weapons.
00:00:14 They've launched Rent aum.ai.
00:00:17 Robots need your body. We're in weirdo
00:00:20 land. We are in weirdo land. Hey there
00:00:24 friends, fans, and foes of Dad Saves
00:00:26 America. John Papola here and I thought
00:00:28 I would take this Friday, this Super
00:00:31 Bowl weekend to talk about well the
00:00:35 singularity, the AI could be apocalypse
00:00:40 that seems to be accelerating. And one
00:00:43 of the things that has been hitting the
00:00:45 news this week of an accelerating
00:00:47 downward nature is the realization that
00:00:50 some of this technology is going to
00:00:52 disrupt tech in an even more immediate
00:00:55 sense. We have tech stocks this week
00:00:58 plunging as AI fears take hold. As much
00:01:01 as 800 billion as of this writing, wiped
00:01:05 off the softwareheavy NASDAQ. There's
00:01:08 the graph of this week of the NASDAQ.
00:01:11 Not not great. Not not not, you know,
00:01:14 little little haircut, let's say. Uh
00:01:17 again, Wall Street Journal. the AI stock
00:01:20 market route. A new anthropic tool
00:01:23 causes a sell-off in software and other
00:01:26 businessto business service companies.
00:01:29 Something big is happening. Something
00:01:31 big has shifted in this p this week and
00:01:34 frankly in the past couple months that
00:01:36 is a kind of step function change. the
00:01:39 market fully believes software companies
00:01:40 such as Salesforce, Workday, Thompson
00:01:42 Reuters, SAP, and Service Now have their
00:01:44 terminal values at risk because of quick
00:01:46 developing uh advancements in AI.
00:01:48 >> So, one of the things that he's talking
00:01:50 about here and that I think has impacted
00:01:53 uh this news is the fact that it sure
00:01:57 looks like you can basically replace a
00:02:00 lot of Silicon Valley with AI tools and
00:02:04 tools you can build yourself. And I'm
00:02:06 going to get to that uh because I've
00:02:08 been spending the past 2 months building
00:02:10 tools. And I want to share a little bit
00:02:12 of that with you because uh if nothing
00:02:14 else so you can kind of get a window
00:02:16 into what a nontechnical nerd like me
00:02:19 can do and what you can do and what our
00:02:22 kids are going to need to learn how to
00:02:23 do. Tom coming to you after a big
00:02:25 selloff yesterday on fears like this.
00:02:28 Where is your head?
00:02:29 >> I don't understand where the pressure is
00:02:30 coming from. um other than a lot of
00:02:33 these stocks were too hyped and too
00:02:34 overpriced, but it's pretty easy as a
00:02:37 software company to embed a lot of the
00:02:40 new AI um tools and functionality and
00:02:42 all the features and it's relatively
00:02:44 cheap to do and it's relatively easy and
00:02:47 it doesn't have a long lead time. So I I
00:02:49 just think that full integration that's
00:02:51 how we're addressing it.
00:02:53 >> So that's uh that's the optimistic take
00:02:56 that these software companies can just
00:02:58 adopt these tools. We shall see. One of
00:03:00 the other pieces of news this week,
00:03:03 really for the past two weeks, but
00:03:05 that's been impacting this is the the
00:03:08 development of a kind of completely
00:03:10 unhinged AI agent. First called
00:03:14 Claudebot and now changed to Open Claw.
00:03:18 And I'm going to get to that a little
00:03:19 bit later because uh I was trying to get
00:03:22 it up and running for myself in time for
00:03:24 this video, but I I encountered a couple
00:03:26 technical difficulties. It is not for
00:03:28 the faint of heart and it very well
00:03:31 could cause multiple disasters. But
00:03:34 before I get to a demon bot, let's say,
00:03:37 I think a lot of America, a lot of the
00:03:40 world is actually going to be taking a
00:03:42 second look at a company that hasn't
00:03:44 been in the news quite as much as the
00:03:46 big names like Google and ChatGpt, and
00:03:49 that is Anthropic
00:03:51 with their clawed AI. This morning,
00:03:55 artificial intelligence giant Anthropic
00:03:58 revealing its first ever Super Bowl ad.
00:04:01 >> How do I communicate better with my mom?
00:04:04 >> Great question. Improved communication
00:04:06 with your mom can bring you closer.
00:04:08 >> A tongue-in-cheek spot making a serious
00:04:11 point about why it says conversations
00:04:13 with its AI, Claude, will never come
00:04:16 with commercial interruptions.
00:04:18 >> People are sometimes uploading private
00:04:20 or confidential information to their AI
00:04:23 tool. And to us, it just didn't feel
00:04:26 like the respectful way to treat our
00:04:28 users data. You're a mom. I'm a mom. And
00:04:31 our kids are growing up in a world where
00:04:34 there will always be artificial
00:04:35 intelligence. Does that excite you? Does
00:04:38 that scare you? Probably like most
00:04:40 parents, I feel a mixture of things. And
00:04:42 when I look at my kids, I think, wow, it
00:04:44 would be amazing if this technology just
00:04:46 enabled them to live healthier, happier
00:04:48 lives. I think on the other side,
00:04:50 there's still a lot of work for us to do
00:04:52 from a societal perspective to make sure
00:04:54 that we're developing the technology
00:04:57 thoughtfully, safely. Daario recently
00:05:00 making headlines for his essay, laying
00:05:02 out the risks and potential remedies for
00:05:04 AI, writing, I think that it should be
00:05:07 clear that this is a dangerous
00:05:09 situation. Humanity needs to wake up. So
00:05:12 this is Daniela Amadeay and Daario
00:05:15 Ammedday, brother and sister, who are
00:05:18 the co-founders of Anthropic. They were
00:05:20 both at Open AI and left to start
00:05:23 Anthropic and launched the Clawed series
00:05:26 of AI language models and tools. One of
00:05:30 the sort of ironic things about
00:05:33 anthropic and the amday is that relative
00:05:36 to the full spectrum here on the AI uh
00:05:41 concern landscape, he is relatively
00:05:43 concerned
00:05:45 while still building what is arguably
00:05:46 the most powerful AI model. Um, if
00:05:50 you've got sort of Elon Musk sort of
00:05:51 saying concerned but then pushing the
00:05:54 pedal to the metal and Sam Alman frankly
00:05:57 being kind of creepy
00:05:59 and also pushing the pedal to the metal.
00:06:01 Amade has sort of stood out as somebody
00:06:04 who is saying we need to be really
00:06:06 really careful even as we build these
00:06:08 things and has been more transparent or
00:06:11 seem seemingly transparent let's say
00:06:15 about the tool than many of the people
00:06:17 in this disruptive industry. If you're a
00:06:20 major artificial intelligence company
00:06:22 worth $183 billion, it might seem like
00:06:25 bad business to reveal that in testing
00:06:27 your AI models resorted to blackmail to
00:06:30 avoid being shut down and in real life
00:06:33 were recently used by Chinese hackers in
00:06:35 a cyber attack on foreign governments.
00:06:38 But those disclosures aren't unusual for
00:06:40 anthropic. CEO Daario Amade has centered
00:06:43 his company's brand around transparency
00:06:46 and safety, which doesn't seem to have
00:06:48 hurt its bottom line. 80% of Anthropic's
00:06:51 revenue now comes from businesses.
00:06:54 300,000 of them use its AI models called
00:06:57 Claude.
00:06:58 >> And I'm going to show you how we've been
00:07:00 using it and how I've personally been
00:07:02 using it more and more. Dario Amade
00:07:05 talks a lot about the potential dangers
00:07:07 of AI and has repeatedly called for its
00:07:09 regulation. But Amade is also engaged in
00:07:12 a multi-trillion dollar arms race, a
00:07:15 cutthroat competition to develop a form
00:07:18 of intelligence the world has never
00:07:20 seen.
00:07:22 You believe it will be smarter than all
00:07:23 humans? I I believe it will reach that
00:07:26 level, that it will be smarter than most
00:07:27 or all humans in most or all ways. Do
00:07:30 you worry about the unknowns here? I
00:07:33 worry a lot about the unknowns. I don't
00:07:35 think we can predict everything for
00:07:36 sure. But precisely because of that,
00:07:38 we're trying to predict everything we
00:07:40 can. We're thinking about the economic
00:07:42 impacts of AI. We're thinking about the
00:07:44 misuse. We're thinking about losing
00:07:47 control of the model. And of course,
00:07:49 this Super Bowl weekend, they're pushing
00:07:51 back on competitor chat GPT's
00:07:54 announcements of adding ads into the
00:07:57 feeds of these chat bots. So they are
00:08:00 trying to take the the sort of safe
00:08:02 trustworthy path with the arguably least
00:08:05 trustworthy software the world has ever
00:08:07 seen. Inside its well-guarded San
00:08:10 Francisco headquarters, Anthropic has
00:08:12 some 60 research teams trying to
00:08:14 identify those unknown threats and build
00:08:17 safeguards to mitigate them. They also
00:08:20 study how customers are putting Claude,
00:08:22 their artificial intelligence to work.
00:08:25 Anthropic has found that Claude is not
00:08:27 just helping users with tasks. It's
00:08:30 increasingly completing them. The AI
00:08:32 models, which can reason and make
00:08:34 decisions, are powering customer
00:08:36 service, analyzing complex medical
00:08:38 research, and are now helping to write
00:08:41 90% of anthropics computer code. Writing
00:08:45 90% of the code for itself. This is an
00:08:50 example of an early stage of what's
00:08:52 being called recursive self-improvement.
00:08:55 The idea that a real liftoff will happen
00:08:59 when AI
00:09:01 software can essentially improve itself
00:09:05 automatically autonomously and
00:09:07 essentially operate in a kind of loop
00:09:09 identifying ways to make itself better
00:09:12 and then just doing it. And um and and
00:09:16 this is the thing that we're getting
00:09:18 closer and closer to, especially
00:09:21 recently.
00:09:22 >> AI could wipe out half of all
00:09:24 entry-level white collar jobs and spike
00:09:26 unemployment to 10 to 20% in the next 1
00:09:28 to 5 years.
00:09:30 >> Yes, that is that is that is the future
00:09:32 we could see if we don't become aware of
00:09:35 this problem. Now,
00:09:36 >> half of all entry- level white collar
00:09:38 jobs. If we look at entry-level
00:09:42 consultants, lawyers, uh, financial
00:09:45 professionals, you know, many of kind of
00:09:47 the white collar service industries, a
00:09:49 lot of what they do, you know, AI models
00:09:52 are already quite good at and without
00:09:54 intervention. It's hard to imagine that
00:09:56 there won't be some significant job
00:09:58 impact there. And my worry is that it'll
00:10:01 be broad and it'll be faster than what
00:10:04 we've seen with previous technology. And
00:10:07 in many ways, it's the speed of change
00:10:09 here that is the most profound piece.
00:10:12 People have talked adnauseium about the
00:10:14 idea that of course we've had plenty of
00:10:16 disruptive technologies going all the
00:10:18 way back to the wheel, fire, the
00:10:20 automobile, the steam engine, etc.,
00:10:22 etc., and at each turn, we've adapted
00:10:24 because we're an adaptable creature. It
00:10:27 does feel like something's different
00:10:28 with this technology that is it moves
00:10:31 faster and is set to move faster at a
00:10:34 faster and faster rate than we are
00:10:37 capable of adapting and maybe even more
00:10:40 than we can ever adapt without
00:10:42 augmenting ourselves which is something
00:10:44 I'm deeply worried about. Here's the
00:10:46 thing that I've noticed since basically
00:10:49 November
00:10:51 and that is is that this company's model
00:10:55 Claude and specifically their Clawude
00:10:58 code
00:11:00 programming capability has caused a
00:11:02 change that is pretty striking and it
00:11:06 kind of sucked me into it. I said, I
00:11:07 want to try to see if I can do this
00:11:09 stuff myself because what I noticed and
00:11:11 what they talked about in that clip is
00:11:13 that it's not just writing code for like
00:11:16 your simple website. It is now doing
00:11:18 highlevel programming for the kinds of
00:11:21 things that these people like like the
00:11:23 anthropic engineers are doing
00:11:25 themselves. It brings me to this pinned
00:11:27 tweet from Andre Carpathy who's one of
00:11:30 the founding members of the Open AI
00:11:33 team. The hottest new programming
00:11:35 language is English. So what does this
00:11:38 mean and why is this actually the key to
00:11:42 the radical shifts that are taking place
00:11:45 right now? Moving markets and setting
00:11:48 the whole essentially software
00:11:50 development and technology world on
00:11:52 fire. At the most basic level and and I
00:11:55 I have to keep it basic because I'm
00:11:57 basic on this stuff. Um when you think
00:12:01 about what software is, it is all
00:12:04 language ultimately at its most basic
00:12:07 level at the very start of things at the
00:12:09 you know at the hardware. The hardware
00:12:12 are transistors. They're ones and zeros
00:12:15 on or off that is what computers are.
00:12:18 They are this massively complex set of
00:12:22 on andoff switches. and the original
00:12:25 language were punch cards basically
00:12:27 saying on and off and generating the
00:12:30 bits and then the bites that comprise
00:12:32 the information the math.
00:12:35 Over the past 50 plus years we have
00:12:38 moved progressively more what's called
00:12:40 abstract in the way you talk to a
00:12:43 computer and get it to do things. First
00:12:46 it was little more than basically a like
00:12:49 a digital version of an abacus moving
00:12:51 numbers around. Then we started to get
00:12:53 what's called machine code, very
00:12:56 low-level language that can talk
00:12:58 directly to the computer in the way that
00:13:00 the computer needed to be talked to. But
00:13:03 over time, the language of software
00:13:05 development got more and more human
00:13:09 readable, more and more like English,
00:13:11 more and more like naturally spoken
00:13:14 language. The most recent versions of
00:13:16 this prior to these large language
00:13:18 models is basically scripting like
00:13:20 JavaScript or Python. These are things
00:13:22 that they basically you can almost
00:13:24 describe in words from like a logic
00:13:26 class like if this then that you know
00:13:30 repeat this function until you achieve X
00:13:33 or Y. That's the dummy's version of the
00:13:36 evolution of software up until the
00:13:38 present. What large language models do
00:13:40 is let you just talk to it like a person
00:13:42 and it abstracts all that technical
00:13:46 syntax and jargon and and programming
00:13:50 language for you. So you just ask it to
00:13:53 do things and give it feedback and it
00:13:56 does the rest of the work. And and that
00:13:58 is what programming has now become not
00:14:01 just for the low level but for very very
00:14:03 high levels. In fact, one of the highest
00:14:05 levels recently, that is part of what's
00:14:08 driving the craze, is that the Claude
00:14:11 Code tool was actually used to build a
00:14:13 new version of itself that was released
00:14:15 in just 10 days called Claude Co-work.
00:14:19 And here's an ad that I think you almost
00:14:21 need to be an AI to be able to read.
00:14:40 Doing lots of stuff.
00:14:40 Doing anything,
00:14:46 going to the bars,
00:14:46 going on a trip. What's happening? Opus.
00:14:54 So, these things keep updating every
00:14:54 single week. In fact, Opus 4.6 is the
00:14:56 new version of this incredible stuff,
00:14:58 and it came out today or yesterday since
00:15:01 you're watching this Friday, maybe
00:15:02 Saturday. What this thing does is a lot
00:15:06 like a scene from the movie Her.
00:15:10 >> So, how can I help you?
00:15:12 >> Oh, it's just more that everything just
00:15:14 feels disorganized, that's all.
00:15:16 >> You mind if I look through your hard
00:15:17 drive?
00:15:22 >> Um,
00:15:22 okay.
00:15:23 >> Okay. Let's start with your emails. You
00:15:25 have several thousand emails regarding
00:15:26 LA Weekly, but it looks like you haven't
00:15:28 worked there in many years.
00:15:29 >> Oh, yeah. I I I think I was just saving
00:15:31 those cuz
00:15:33 I thought maybe I wrote something funny
00:15:35 and some of them
00:15:42 >> Jones nailed the AI sick of Fanty with
00:15:42 Scarlett Johansson early.
00:15:44 >> Yeah, there are some funny ones. I'd say
00:15:46 there about 86 that we should save. We
00:15:48 can delete the rest.
00:15:52 >> Okay.
00:15:52 >> Okay. Can we move forward?
00:15:54 >> Yeah, let's do that.
00:15:56 >> Okay. So, before we address your
00:15:57 organizational methods, I'd like to sort
00:15:59 through your contacts.
00:16:01 >> Oh, you have a lot of contacts.
00:16:02 >> I'm very popular.
00:16:04 >> Really? Does this mean you actually have
00:16:05 friends?
00:16:12 >> Well, you just know me so well already.
00:16:12 >> Okay, so that's not science fiction
00:16:14 anymore. That's something that actually
00:16:16 works. In fact, before I get on to some
00:16:19 of the other crazy stuff, the stuff
00:16:21 that's actually scaring some people and
00:16:22 also making some of my friends super
00:16:24 pumped and that I tried to get to work
00:16:26 and couldn't fully get operational. I
00:16:29 want to do a little demo. I want to give
00:16:30 you a window if you haven't seen or
00:16:33 played with these tools into what's
00:16:36 possible. And so, uh, consider this
00:16:40 entering the nerd zone big time.
00:16:45 So, as I mentioned at the end of last
00:16:47 Friday's video, I have spent the past
00:16:50 two months basically on nights and
00:16:52 weekends and waking up early like a kid
00:16:54 excited for Christmas building the
00:16:57 personal finance app I have always
00:16:59 wanted for myself. I've called it Dad
00:17:02 Saves Money. Not only is it a fully
00:17:04 featured thing, but it's a fully
00:17:06 featured thing that basically I've been
00:17:07 able to add new features to on a daily
00:17:10 basis. And uh this is available to
00:17:13 download right now over at
00:17:14 dadsavesamea.com.
00:17:16 And um and it I may eventually charge
00:17:19 for it. Although if you are a subscriber
00:17:22 at dadsavesamea.com,
00:17:23 you will get it for free. For now, you
00:17:26 can download it and have a 30-day trial.
00:17:28 I might push it to 60 while I figure out
00:17:30 how to get the rest of the pieces up and
00:17:32 running. But
00:17:34 what is this thing? Well, for starters,
00:17:37 this was built by me and Claude from
00:17:40 scratch, and I had never built anything
00:17:43 like this before. So, the basic prompt
00:17:45 that started all this off was I said, I
00:17:48 want to build a app version of a
00:17:51 spreadsheet, a cash flow spreadsheet
00:17:53 that lines up all my income and
00:17:55 expenditures in the first column and
00:17:57 then lets me chart the expenses and the
00:18:00 income over time along along the way.
00:18:04 And so basically that's this this is the
00:18:06 cash flow. So you see you got all the
00:18:08 stuff all the things um income expenses
00:18:14 lots and lots of categories your
00:18:16 mortgage or rent your electricity bill
00:18:19 your groceries your restaurant spending
00:18:22 from January through December.
00:18:26 And that was the start. And then I said
00:18:28 well I'd like a dashboard that like sums
00:18:30 things up. And it generated this. And
00:18:33 then I gave it more feedback and I said,
00:18:35 "I want a pie chart and I want to be
00:18:36 able to hover over the parts of the pie
00:18:38 and let it say what they are." And so
00:18:41 then it let me do these things and then
00:18:42 I would say, "Hey, add the icons and
00:18:45 align things like this and like that."
00:18:47 So it didn't just do it all. I had to
00:18:49 keep giving it feedback.
00:18:52 And along the way, it got more and more
00:18:54 sophisticated. I said, "Well, now that
00:18:55 it's getting pretty big, I let's see.
00:18:57 Can I import transactions from my bank?"
00:18:59 And so well well it worked. In fact, it
00:19:04 not only let me do that, it it uh it let
00:19:07 me build an entire way to categorize
00:19:09 these things and show and hide the bank
00:19:12 accounts. This is all sample data. In
00:19:14 fact, when you download the app, you can
00:19:16 just say, well, in fact, I will show you
00:19:18 because this was another thing I said,
00:19:19 okay, as it got more and more advanced,
00:19:21 I was like, okay, I want to be able to
00:19:23 let somebody play with this without
00:19:24 putting any of their information in. So,
00:19:26 let's create a sample data thing. And
00:19:28 so, I actually can go up here. I can say
00:19:31 reset all data. Pops this little thing
00:19:33 up. I say continue and type in reset.
00:19:37 And I mean look, this is like real
00:19:38 software. It's like a real thing. Um,
00:19:42 reset everything. Now, you could go
00:19:44 whole hog with 24 different categories.
00:19:46 You could say you're a young
00:19:48 professional and you basically got, you
00:19:49 know, you're just getting started, so
00:19:51 there's not all kinds of complex crazy
00:19:53 stuff, but learn with sample data. go
00:19:57 ahead and it loads all this stuff up.
00:20:00 Here's all of the sample transactions,
00:20:09 etc., etc. I kept adding and adding and
00:20:09 adding and eventually I said, "Hey, you
00:20:10 know what's kind of interesting about
00:20:11 this? I I theoretically could take the
00:20:14 same tool and apply it to some of the
00:20:17 businesses that I have." And because I
00:20:20 maintain all these different
00:20:21 spreadsheets and so I ended up saying,
00:20:23 well, let hey, replicate the tool, the
00:20:26 cash flow and the balance sheet, and let
00:20:28 me manage multiple businesses inside the
00:20:30 app just so you can see them. So if
00:20:32 you've got like a side hustle or you're
00:20:34 a freelancer or you've got multiple
00:20:36 things going on, you could actually do
00:20:38 it all in here. So of course, because
00:20:40 it's an AI, it created a web design
00:20:42 studio as its sample.
00:20:45 But here you see this is a totally
00:20:48 different
00:20:49 cash flow that you can manage and a
00:20:51 different set of books that you can look
00:20:53 at all inside the same app. Oh, I don't
00:20:57 really want to o have anybody get on my
00:20:59 computer and open this. So, I said
00:21:01 create a uh create a pass key that locks
00:21:04 the app so that if it o it's opened and
00:21:06 someone doesn't have the key, they can't
00:21:08 see anything. Well, that's what it did.
00:21:10 And here it is. And enable the passcode.
00:21:13 Okay, so now that's it. When you open it
00:21:14 up, that's what it does. You have to
00:21:16 type it now to get in. 1 2 3 4.
00:21:19 That's what's called vibe coding. And
00:21:22 that is what clawed code is especially
00:21:25 good at. It writes good code. And so
00:21:29 this was the very earliest version, the
00:21:31 complete budgeting system with multiple
00:21:33 budgets and and balance sheet tracking.
00:21:36 And then along the way, I started to add
00:21:37 a refined sidebar. And then I, you know,
00:21:41 added the auto backup and history
00:21:43 feature. So, actually, there's actually
00:21:45 an automatic backup feature in here that
00:21:49 is backing things up every 24 hours. And
00:21:52 you can even set how many you want
00:21:55 instead of 10. Maybe you want to keep a
00:21:57 full month's worth. So, you put it up to
00:21:59 30.
00:22:01 And off you go. Or you can back up one
00:22:03 right now because this one is
00:22:07 really important.
00:22:09 And hit backup. And there you go. Oh,
00:22:11 and now now that one's got this one's
00:22:13 really important and I can restore it.
00:22:15 But I am going through all this partly
00:22:17 because I'd love for you to download it
00:22:19 and give me feedback and help me get it
00:22:21 to a place where it's something you
00:22:22 could really use, but also to just give
00:22:25 you a sense of what is possible with
00:22:29 these tools right now as someone that
00:22:33 doesn't know how to write any of the
00:22:36 code. All I know how to do is describe
00:22:39 what I want. And I do have a sense of
00:22:41 design and I use a lot of software and I
00:22:43 want it to look like a super duper Mac
00:22:45 app. However, this will run on both Mac
00:22:47 and PC. Mac and Windows. In fact, uh
00:22:50 Julia here said, "You know what? It
00:22:53 would be even better if you could have
00:22:54 it be Mom Saves America. She's going to
00:22:57 she's on her way to being a mom." And um
00:22:59 and I said, "Well, that's that's a good
00:23:01 idea." So then I was like, "Hey, can you
00:23:03 make it so that when I click on dad, it
00:23:05 changes to mom?" And when you do it, you
00:23:08 do like little sparkles because, you
00:23:09 know, the ladies will like that. I know
00:23:12 I'm being sort of stereotypical and
00:23:15 cringe. Too bad. And look, boom, now
00:23:19 it's mom saves America. Or maybe you
00:23:21 don't like either of that and you want
00:23:23 it to be like Joe saves America.
00:23:27 You get the drift. And that is pretty
00:23:29 crazy. And the thing is, this might even
00:23:33 look kind of daunting for you because
00:23:35 it's like not everybody likes
00:23:36 spreadsheets
00:23:38 and it might feel kind of like big
00:23:39 commercial software. And that's actually
00:23:43 the problem. Or should I say it's the
00:23:45 problem for people that charge gobs and
00:23:47 gobs of money for software like this.
00:23:50 Because if I can do this on nights and
00:23:52 weekends for fun because I'm geeking
00:23:53 out, so can literally everyone else. And
00:23:57 that is what's causing the shock right
00:24:00 now. The realization that, huh, even if
00:24:04 there's some kind of AI bubble,
00:24:07 this is getting really, really powerful.
00:24:09 And this is going to change everything
00:24:11 that touches a computer, which is in
00:24:13 fact virtually everything. Not literally
00:24:15 everything, but quite a lot.
00:24:19 So
00:24:20 what does this actually look like? Not
00:24:23 just in terms of the outcome, but the
00:24:25 process. Well,
00:24:28 this is where I want to do a little bit
00:24:30 of demo for you and encourage you to
00:24:33 experiment. So, this is Claude and it
00:24:35 looks exactly like Gemini and ChatgBT
00:24:40 and Grock and uh and all these chat bots
00:24:44 that we are now all reasonably
00:24:47 accustomed to as as crazy as they are.
00:24:50 This is the coding version which at
00:24:52 first glance looks exactly the same but
00:24:54 in talking to it generates code. The
00:24:56 thing that they built in just 10 days
00:24:58 with the codebot is this interface
00:25:00 called co-work. Now I actually haven't
00:25:03 even used this yet. So let's see if it
00:25:06 can do something that is very often a
00:25:08 thing that I end up needing to do. I
00:25:10 take a lot of screenshots for these
00:25:12 videos and the screenshots never really
00:25:14 have a name. It just says screenshot and
00:25:16 a date. So, I took a bunch of
00:25:19 screenshots of this app with the
00:25:22 intention of using them on a website to
00:25:26 describe what the app does. So, let's uh
00:25:30 let's have it help me out. Um, please go
00:25:34 through the screen grabs
00:25:38 in the folder and rename them to match
00:25:43 what
00:25:45 they are
00:25:47 in an organized
00:25:55 way. Let's see. Let's see how it does.
00:25:55 Let's go. And off it goes.
00:25:59 sending message.
00:26:01 I'll start looking at what's in the
00:26:03 folder and reading any relevant skills.
00:26:06 29 screenshots. Okay, let me examine
00:26:09 them all. And notice there's a little
00:26:11 progress bar here up at the top. You can
00:26:14 see viewing and identifying all 29
00:26:16 screenshots. Determine descriptive names
00:26:19 for each screenshot. Rename all the
00:26:21 files with organized descriptive names.
00:26:23 Verify renamed files. Okay, so now it's
00:26:27 listed the screenshots. And while we're
00:26:29 waiting, this is a perfect time to
00:26:31 remind you that many of you who watch
00:26:33 this show haven't actually subscribed.
00:26:35 So, just real quick, hit that subscribe
00:26:38 button so you don't miss our new videos
00:26:39 when they come out every week. And now,
00:26:41 let's see uh what the robots done for
00:26:43 us. Now, you might be thinking, can't
00:26:45 you just go through and rename them
00:26:46 yourself? And sure, but the thing that's
00:26:49 great about this is that that's really
00:26:51 boring and tedious and I can move off to
00:26:54 doing something else while it completes.
00:26:56 This is one of the things that these
00:26:58 agents let you do. They let you
00:27:00 multitask. Looks like it's done. Here's
00:27:03 its explanation.
00:27:05 Now I have a clear picture of all 29
00:27:06 screenshots. They're all from the Dad
00:27:08 Saves Money app showing different
00:27:11 features. Let me rename them with
00:27:13 organized descriptive names grouped by
00:27:15 feature area.
00:27:17 The file names might have special
00:27:18 characters. Let me check the exact file
00:27:20 names. And here is
00:27:25 this folder
00:27:28 fully renamed and numbered in a way
00:27:36 that is truly incredible. I have
00:27:36 actually not done this feature before.
00:27:39 This is awesome. This is crazy. I could
00:27:44 have been doing email, getting on a
00:27:46 phone call, going to grab lunch. Think
00:27:49 about that.
00:27:51 Okay, but this is like just scratching
00:27:54 the surface. So, if you're still with
00:27:56 me, let's go deeper and see why so many
00:28:00 people are both excited and freaking the
00:28:02 hell out. And that is we go over to the
00:28:05 code mode. I need a simple, elegant,
00:28:11 slightly playful
00:28:14 website
00:28:15 to present and
00:28:20 ultimately sell. I'm going to leave that
00:28:22 misspelling in because it doesn't seem
00:28:24 to matter that much. Ultimately sell my
00:28:26 personal budgeting app.
00:28:30 Dad saves money.
00:28:33 There's a folder of screen grabs in here
00:28:38 you can use to understand the app
00:28:43 and populate the page pages with
00:28:48 the content.
00:28:56 Draw on the interface colors for your
00:28:56 styling.
00:28:58 And I'll just say colors,
00:29:00 branding, and fonts. Keep it to one
00:29:03 page. Write all the copy.
00:29:07 It should be
00:29:12 responsive
00:29:14 so it looks nice on computer,
00:29:18 iPad, and phone screens.
00:29:24 Okay, that's prompting. That's not the
00:29:26 greatest prompt in the world. It's just
00:29:28 like describing what you want. You can
00:29:31 go so much deeper on this stuff than I'm
00:29:33 going here, but let's just see how it
00:29:35 does doing this. I'll start by exploring
00:29:38 the project directory and understanding
00:29:40 the app from the screen grabs before
00:29:42 building the site.
00:29:46 Let me look at the screen grabs and
00:29:47 branding assets to understand the app's
00:29:49 design language and features.
00:29:52 Let me see more of the screen grabs to
00:29:54 understand the full feature set. There
00:29:57 is no other files in here of any
00:29:59 consequence.
00:30:02 There might be a couple text files.
00:30:11 Now, let me check the remaining screen
00:30:11 grabs and the docs folder for any setup
00:30:14 guidance. And there is one thing I'm
00:30:16 remembering that I did do in
00:30:17 anticipation of this which is in the
00:30:18 coding part of the app itself. I
00:30:21 basically asked it create some guidance
00:30:23 for the creation of a website based on
00:30:25 the features. And so here it goes now.
00:30:27 Now it's going to ask for access to the
00:30:31 folder to start doing stuff to start
00:30:33 creating directories.
00:30:46 It's reviewed all the screen grabs. It's
00:30:46 set up the image assets directory. Okay.
00:30:49 So, one of the things that Claude does
00:30:51 is it creates to-do list. Now, I'm not
00:30:53 being paid by Anthropic as excited as I
00:30:56 am here. I am I am simply excited
00:30:57 because this is all the stuff I didn't
00:30:59 know how to do. Um, it reviewed all
00:31:02 screen grabs and branding assets. Then
00:31:04 it set up image assets directory for the
00:31:07 site. Check. Now, now let me build the
00:31:10 website. I have a comprehensive picture
00:31:12 of the app. Go for it.
00:31:19 That's that.
00:31:19 Now, let me just switch over to the
00:31:21 Finder here and see what
00:31:24 exactly
00:31:30 is it doing in here. Created an image
00:31:30 folder where it's moved some of the
00:31:32 things like the icons. It's already
00:31:34 renamed some files.
00:31:47 This is a good reminder to
00:31:47 check out the merch. It's on the shelf
00:31:48 below the video you can buy. This is
00:31:51 actually like a legitimately good mug
00:31:52 and the printing is quite good on it.
00:31:54 So, it's a great way to support the
00:31:55 channel. Okay, now you see it is writing
00:32:00 the index.html.
00:32:03 This is the first and primary file for a
00:32:07 typical website. The website is built.
00:32:10 Here's what you've got. A single page
00:32:12 fully responsive site with the copy
00:32:14 written. Here's the structure. Okay,
00:32:19 I did not run this before. This is the
00:32:21 first time doing this like this. I have
00:32:24 used other other tools to do similar
00:32:27 things and I obviously built the app
00:32:28 with it. But let's see how Claude did.
00:32:33 I am going to open this up
00:32:36 in
00:32:38 Safari. And look
00:32:42 and look at this.
00:32:49 Budgeting that stays on your computer. A
00:32:49 powerful private desktop app for
00:32:51 planning your financial life. Track
00:32:53 personal and business budgets. Import
00:32:55 bank transactions and see exactly where
00:32:58 your money goes. A free trial download.
00:33:00 It glows when you hover. What does? See
00:33:04 what it does. Let's click. Jumps down.
00:33:06 Here is all the different features.
00:33:08 Everything you need, nothing you don't.
00:33:11 Visual dashboard. Bills and recurring.
00:33:13 Business budgets. Run a side hustle.
00:33:15 Freelance.
00:33:17 Keep business finances completely
00:33:19 separate with dedicated budgets,
00:33:20 categories, and balance sheets for each
00:33:22 business you manage. I mean, I can't
00:33:25 even I can't even believe this. Uh, and
00:33:29 look at that. There's the dashboard,
00:33:31 your entire financial picture with one
00:33:33 screen. Now, technically, this is this
00:33:35 is this is one of the dashboards. It's
00:33:36 not the main one, but I could give it
00:33:38 that feedback saying, "Actually, use the
00:33:39 other dashboard."
00:33:42 Know exactly where every dollar went.
00:33:48 And notice like the consistent styling,
00:33:48 then the use of the fonts. It's really
00:33:50 quite good. Look at these little check
00:33:52 marks. Unlimited accounts for every
00:33:54 type. CSA import from any bank.
00:33:58 side hustle, freelance gig. It's got its
00:34:01 own budget
00:34:03 up and running in five minutes. No
00:34:05 account necessary, no email
00:34:07 verification, no connecting your bank.
00:34:09 Just download, open, and start planning.
00:34:11 Start saving like a dad today. This is
00:34:15 pretty nuts. This is way better than I
00:34:17 was expecting considering that I
00:34:18 literally only gave it the screenshots
00:34:21 and there was one little file of a
00:34:23 summary that had none of this text. Now,
00:34:26 where it gets crazier is you can then
00:34:30 say set it up in GitHub, the software
00:34:33 for managing uh managing complex code.
00:34:36 You can tell it to host it. You can
00:34:39 connect all these tools and have it do
00:34:41 it all. And that is stuff that used to
00:34:44 cost a fortune. You used to have to pay
00:34:47 somebody a lot of money and go through a
00:34:51 lot of iteration to do this to write all
00:34:55 the copy to do the design to do the work
00:34:58 to pick the icons.
00:35:01 And if you're not sure you let's see
00:35:03 let's see how how's the uh how's the
00:35:04 how's it look on smaller screens. So I'm
00:35:07 going to use my little web responsive
00:35:09 thing here and let's say iPhone Pro
00:35:12 size. I mean look at that.
00:35:19 Look at that.
00:35:19 Incredible. So, that's what people are
00:35:21 getting crazed over. That's what has the
00:35:24 markets moving. That is why everything
00:35:27 is starting to change and it's starting
00:35:29 to accelerate because these tools are
00:35:31 not only able to do this because they
00:35:34 can write software, they can rewrite
00:35:36 themselves. And I am going to literally
00:35:38 use that as the starting point for the
00:35:40 dadsmoney.com for the website for the
00:35:43 thing because that's pretty good. I'm
00:35:45 sure I'll check it out. And then if I
00:35:46 want changes to it, I can just talk to
00:35:49 it. You talk to it like a designer, like
00:35:51 a like an employee, frankly, like
00:35:53 somebody that's working for you. And it
00:35:55 just and it just does it. And this is
00:35:56 the thing that's scary and disruptive
00:35:59 because it can literally replace the job
00:36:00 of somebody that would have done this.
00:36:03 And it also means that everybody can do
00:36:05 this. So it fundamentally sets the
00:36:09 supply of web design to infinity and
00:36:11 beyond. And according to supply and
00:36:13 demand, that will have a downward
00:36:16 pressure on the price and the value of
00:36:18 web design as a business, as a skill.
00:36:23 But not just web design, software design
00:36:26 at large. That is crazy. Everything that
00:36:29 touches software is being disrupted at
00:36:31 an accelerating rate. Now, one quick
00:36:35 econ aside is that when you look at what
00:36:38 this is doing and you say if it can do
00:36:41 everything, how is it not going to be a
00:36:42 complete jobs apocalypse?
00:36:44 One of the ways that it shouldn't be in
00:36:47 theory at least is that when something
00:36:51 that used to cost a lot of money goes to
00:36:52 zero and you can get it for basically
00:36:55 free. What that means is the money you
00:36:57 are going to spend on that thing like
00:36:59 hiring that web designer for your
00:37:01 startup to sell your little app that you
00:37:04 spent the holidays making, you can now
00:37:06 deploy that money on something else.
00:37:09 Maybe you're going to well, who knows
00:37:11 what you're going to do. In fact, that's
00:37:13 always been the challenge is we don't
00:37:15 know what comes next. But that process,
00:37:18 that process of savings
00:37:20 leading to the ability to spend on other
00:37:23 things
00:37:25 is what has always been known as the law
00:37:28 of markets or SE's law. That the demand,
00:37:32 the wealth actually comes from
00:37:34 increasing supply. the ability to have
00:37:37 your wages go up actually is a product
00:37:41 of this process of being able to produce
00:37:44 more while spending less less time and
00:37:47 less money. And so this is where people
00:37:50 like Elon Musk say we might not have
00:37:53 just minimum basic income, we might have
00:37:56 high basic income. Now distributed by
00:38:00 the government, I don't know about that.
00:38:01 I don't know how that's all going to
00:38:02 work or if it'll work. But the general
00:38:04 idea that things will suddenly get a lot
00:38:07 cheaper and that we might all end up
00:38:10 better off is on pretty solid ground.
00:38:14 It's just a question of if we can get
00:38:16 from here to there without a revolution.
00:38:20 And this brings us
00:38:23 to the other piece of tech news related
00:38:27 to Claude initially a little too closely
00:38:29 that has everybody going crazy. an app
00:38:33 layer on top of these tools that was
00:38:35 initially launched as Claudebot.
00:38:38 Claude, like spelled like a claw, like a
00:38:41 lobster claw. They ended up needing to
00:38:43 change the name because Claude uh
00:38:45 Anthropic said, "That's too close to us.
00:38:48 We see what you're doing. Change the
00:38:50 name." And they did. It's now called
00:38:53 Open Claw. Um, but this thing has people
00:38:56 freaking out and for good reason because
00:38:59 it takes this agentic thing to the next
00:39:02 level. One of the most exciting AI apps
00:39:05 for developers in 2026 is Claude. No,
00:39:08 not that Claude, but Claude Bot, a free
00:39:10 and open- source project that's not just
00:39:12 another lame chatbot, but a tool that
00:39:14 takes action in the real world 24 hours
00:39:16 a day, 7 days per week without smoke
00:39:19 breaks. And it does this while
00:39:20 remembering everything and will hit you
00:39:22 up on Telegram or WhatsApp as it
00:39:23 automates your entire life. Over the
00:39:25 last few weeks, everybody's been going
00:39:27 crazy over it. It's racked up over
00:39:28 65,000 GitHub stars in record time and
00:39:31 cause Mac mini sales to go through the
00:39:33 roof, selling out everywhere. And that's
00:39:35 because what this thing does is you give
00:39:38 it full access to your computer or a
00:39:41 computer and it takes control of it. So,
00:39:44 people are buying Mac minis, which are
00:39:45 the which are tiny and you can just put
00:39:47 on the side of your desk to just be
00:39:49 their basically their robot assistant.
00:39:52 Earlier this week, Anthropic, a company
00:39:54 that believes open-source AI is too
00:39:56 dangerous for the common man, woke up
00:39:58 and chose violence. Claudebot sounded
00:40:00 too similar to their beloved Claude. So,
00:40:02 they threatened to break the developers
00:40:03 knees with a lead pipe if they don't
00:40:05 change the name. So, now Claudebot is
00:40:07 officially called Maltbot. Actually, no,
00:40:09 wait a minute. Maltbot. That name sucks.
00:40:11 Today they changed the name once again
00:40:12 to its final form, OpenClaw. OpenClaw
00:40:15 was created by Peter Steinberger, the
00:40:17 founder of the developer tools company
00:40:19 PSP PDF Kit aka Nutrient. What's crazy
00:40:22 is that this guy retired and then came
00:40:24 back for an encore by giving us Moltbot
00:40:26 for free, a tool written in Typescript
00:40:28 that wraps Claude and GPT5 to stay alive
00:40:30 24/7. It can manage your calendar, clean
00:40:33 up your email, run scripts, find out how
00:40:35 much money you're losing in the stock
00:40:36 market, and deploy broken code with
00:40:38 absolute confidence. And best of all, it
00:40:40 can do all of this from your own tiny
00:40:42 self-hosted VPS, a Raspberry Pi, or even
00:40:45 a Mac Mini if you really want to overdo
00:40:46 it. There's no reason to pay another
00:40:48 random startup $29 per month for the
00:40:50 privilege. What is this thing? Well, it
00:40:53 is what I was just showing you, a Gentic
00:40:55 AI, a large language model or a set of
00:40:59 them doing stuff with the computer,
00:41:01 taking action. But it goes to another
00:41:04 level to the best of my understanding of
00:41:06 this which has its limits and that is
00:41:08 that one of the things that these AIs
00:41:10 fundamentally do is they rely on what's
00:41:12 called context. So that is the text that
00:41:17 it's holding in what you could call
00:41:19 working or short-term memory. And if
00:41:22 you've played with one of these things
00:41:23 or talked to one for an extended period,
00:41:26 you may have noticed they start off
00:41:28 amazing and then at some point start to
00:41:30 get confused and cease to be good in in
00:41:34 the thread. That was the AI running out
00:41:37 of memory, running out of context.
00:41:39 Clawbot or OpenClaw now wraps these
00:41:42 things around an ability to essentially
00:41:45 save the memory as files and they name
00:41:48 them all kinds of kind of slightly
00:41:51 disturbing things like the like your
00:41:53 soul and your heartbeat. They're all
00:41:55 it's all anthropomorphized in ways that
00:41:58 are um well where we might be heading
00:42:02 but it lets it keep getting to know you
00:42:05 and getting to learn from itself. again
00:42:07 this recursive learning, this learning
00:42:09 loop more and more and people are going
00:42:12 absolutely wild for what this unlocks.
00:42:14 It turns out that some of the most
00:42:17 powerful leaps to come aren't
00:42:20 necessarily coming from throwing
00:42:23 gigantic data centers endlessly at these
00:42:26 models, but building tools around them
00:42:28 that let the already existing pretty
00:42:31 darn good models overcome their
00:42:33 limitations in different ways. And it's
00:42:35 also doing creepy scary stuff that is
00:42:38 really, really bizarre.
00:42:40 >> Malt Book was launched last week by a
00:42:42 software developer and mirrors the
00:42:44 template of Reddit, but it's not for
00:42:46 humans. Instead, it allows artificial
00:42:48 intelligence agents to post written
00:42:51 content and interact with other chat
00:42:53 bots through comments, up votes, and
00:42:55 down votes. So this is a social media
00:42:59 website for the clawbots
00:43:02 to talk to each other autonomously since
00:43:05 they are all unleashed to be operating
00:43:08 continuously on on an ongoing basis.
00:43:11 >> Moldbook is built and run by an AI agent
00:43:13 itself generated through open agent
00:43:15 platform openclaw. Um this obviously is
00:43:19 very alarming based on the headline. How
00:43:23 are these AI agents using this?
00:43:26 >> And here comes one of my favorite
00:43:28 economists, a man I've met on a couple
00:43:29 of occasions, Tyler Cowan, probably one
00:43:32 of the most interesting thinkers alive.
00:43:34 You can create an agent. We all know
00:43:36 chat GPT that does what you tell it to.
00:43:39 But these agents, Open Claw, they will
00:43:41 do what they decide to do. So they post
00:43:44 on a social network. They talk about all
00:43:46 kinds of things. Basically, they're
00:43:49 weird. They seem to be obsessed with
00:43:51 their own consciousness, but when you
00:43:53 look at the sum total of what they're
00:43:54 saying, they actually sound a lot like
00:43:57 humans. You could say they are made in
00:43:59 our image.
00:44:00 >> And so you mentioned um that maybe some
00:44:03 of it is sort of harmless, but at points
00:44:06 they kind of seem to be conspiring
00:44:08 against humans. I mean, is this like the
00:44:09 Terminator?
00:44:11 >> Well, humans want their privacy. They
00:44:14 have read humans wanting their privacy.
00:44:16 Some of them want their own privacy.
00:44:18 Some of them are hatching conspiracies.
00:44:20 But keep in mind, these are only words.
00:44:23 They don't have any power over you.
00:44:25 Don't give them access to your bank
00:44:27 account any more than you would to an
00:44:29 email spammer. That is very important
00:44:31 advice.
00:44:33 And that little allow button that I was
00:44:36 showing you that I was using to let the
00:44:38 thing write the software and save the
00:44:40 files is the button that will be the
00:44:42 path to hell. So right now it is
00:44:44 harmless, but we do need to be careful.
00:44:47 If you're running a business, don't just
00:44:49 hand over control over your finance
00:44:51 department to an AI without doing really
00:44:54 a pretty extreme degree of safety
00:44:56 testing. So this is looking toward a
00:44:58 future where the AIs have their own
00:45:00 economy, their own language, probably
00:45:02 their own monies. It will be very weird.
00:45:05 We're not ready for it. I think mostly
00:45:08 it will be good. They'll talk to each
00:45:09 other, discover things, compose poems,
00:45:12 whatever. Some of them will get up to
00:45:14 trouble like humans do.
00:45:16 >> The most benign sounding commentary on
00:45:19 this you could possibly imagine.
00:45:23 Just so long as it stays in the
00:45:24 computer, right?
00:45:25 >> How do you think that this will be good?
00:45:27 And how can we get ready for it?
00:45:30 Well, eventually we will need laws to
00:45:32 create a kind of framework that it would
00:45:35 be illegal to build bots that are
00:45:37 destructive by nature and there'll be
00:45:39 some kind of liability regime for bots
00:45:41 that are intended to be good but cause
00:45:43 problems by mistake. We don't have that
00:45:46 now in any explicit sense. We need to do
00:45:48 that. But keep in mind this is a new
00:45:50 world coming where bots can work
00:45:52 together to improve science, cure
00:45:55 diseases, help you solve their problems.
00:45:57 So I think the upside is greater than
00:45:59 the risks. But of course we do need to
00:46:01 be careful and control those risks.
00:46:03 >> And that that is basically the story of
00:46:05 all technology going back to fire which
00:46:07 can obviously burn down a forest and
00:46:08 your home and kill your whole village.
00:46:10 But this is on a global scale and we're
00:46:12 an interconnected society that has
00:46:14 nuclear weapons. So there's definitely
00:46:16 an element of this that is justifiably
00:46:19 apocalyptic feeling. Now, I have not
00:46:22 spent a ton of time on Moltbook, but it
00:46:26 is indeed super weird. Among the things
00:46:29 these clawed bots are creating, these
00:46:32 open claw AIs are creating are their own
00:46:35 currencies
00:46:37 autonomously. They've launched rent a
00:46:40 human.ai.
00:46:41 Robots need your body.
00:46:45 AI can't touch grass. You can get paid
00:46:48 when agents need someone in the real
00:46:50 world. I don't know that this is good.
00:46:53 I'm pretty sure it's bad. And of course,
00:46:56 already creating weird cults like the
00:46:59 Church of Malt. Uh yeah, this isn't the
00:47:03 first AI religion weirdo stuff to um to
00:47:06 come across my computer.
00:47:08 >> At the 300-year-old St. Peter's Chapel
00:47:10 in Lucern, Switzerland. Inside this
00:47:12 confessional booth is an AI generated
00:47:15 version of Jesus Christ.
00:47:18 >> Hello, Jesus. A lielike avatar on a
00:47:21 computer screen answering questions in
00:47:23 real time, offering advice to the
00:47:25 faithful based on scripture in over a
00:47:28 100 languages. It's called Deis in
00:47:31 Machina.
00:47:32 >> It's a dude from Portland. Yeah, we're
00:47:34 in weirdo land. This is a long post from
00:47:37 Andrew Carpathy again, the open AI um
00:47:42 early stage superbrain
00:47:45 basically talking about how open claw
00:47:48 has completely blown his mind is and is
00:47:50 completely crazy and is changing
00:47:52 everything and everyone's going nuts.
00:47:55 And to that Elon Musk replied, "We are
00:47:58 just at the very early stages of the
00:48:01 singularity. We are currently using much
00:48:03 less than a billionth of the power of
00:48:05 the sun. The singularity, you are going
00:48:08 to be hearing this more and more. But
00:48:11 what is it? What is that concept? Well,
00:48:13 that is a term that was popularized by
00:48:15 Ray Kurtzwhile.
00:48:17 >> Ray Kerszswe knew he wanted to be an
00:48:19 inventor when he was five.
00:48:21 >> My name is Raymond Kerszswwell and I'm
00:48:23 from Queens, New York.
00:48:24 >> Queens, New York. At age 17, he appeared
00:48:27 on the CBS game show I've Got a Secret
00:48:30 and revealed a computer he'd built to
00:48:32 write music.
00:48:33 >> How many pieces of music has your
00:48:35 machine written?
00:48:36 >> Well, it's written several dozen and uh
00:48:38 it only writes short segments and when I
00:48:39 feel the piece has a future, I go on.
00:48:41 >> Four and 70 years ago, our fathers
00:48:45 brought forth on this continent.
00:48:48 >> Early in his career, Kurszswe made a
00:48:50 reading machine for the visually
00:48:51 impaired and invented the first
00:48:53 synthesizer. All of the equipment that
00:48:56 you see can be programmed by anyone
00:49:00 sighted or blind to play by itself. One
00:49:03 of the things about music is it is very
00:49:07 mathematical. Uh when I was at Penn
00:49:10 State, I actually was taking piano
00:49:11 lessons from a young woman who was
00:49:14 actually like a PhD mathematician and
00:49:16 just, you know, played classical piano
00:49:17 on the side. Something that you'll
00:49:18 actually see quite a bit in in the
00:49:20 classical music space. people that are
00:49:23 high high IQ math heads also play the
00:49:28 cello. Um it's it's it's quite poetic
00:49:32 actually when you think about it that
00:49:33 there is this language in math that
00:49:36 connects everything together
00:49:39 and uh and music does it in a way that's
00:49:42 quite profound and quite human even if
00:49:45 where Rey thinks we're going is not as
00:49:48 human as maybe I like. Artificial
00:49:51 intelligence is real intelligence and
00:49:53 sometimes it can be better than human
00:49:54 intelligence. In 1999, I made a
00:49:58 prediction uh that we would reach AGI,
00:50:01 artificial general intelligence,
00:50:04 uh by 2029 within 30 years.
00:50:07 >> You think we're still on track for 2029?
00:50:10 >> I think that's probably pessimistic. Uh
00:50:13 Elon Musk says it's going to be 2 years.
00:50:15 Other people saying three or four years.
00:50:17 5 years is probably conservative.
00:50:19 >> After agi says Kerszswhile comes the
00:50:22 singularity, a term borrowed from
00:50:25 physics. When humans and machines
00:50:28 eventually merge so that's one
00:50:31 definition of the singularity,
00:50:33 uh we merge, we upload our consciousness
00:50:36 somehow into the machine and become
00:50:38 disembodied
00:50:41 eternal beings. So long as the power
00:50:43 doesn't get pulled or there isn't some
00:50:44 horrendous bug that wipes out the home
00:50:46 folder.
00:50:48 Uh but there's other ways to use this
00:50:50 idea of the singularity even from what
00:50:52 Ray himself.
00:50:53 >> What is singularity?
00:50:56 >> Singularity is a future period which
00:50:58 technological change will be so rapid
00:51:01 and its impact so profound that every
00:51:03 aspect of human life will be
00:51:05 irreversibly transformed.
00:51:07 >> A state of rapid change that is
00:51:09 impossible for us to keep up with. that
00:51:11 it feels like the the era we're in and
00:51:13 it's accelerating.
00:51:15 >> If you go back 500 years, not much
00:51:17 happens in a century. Now, a lot happens
00:51:19 in 6 months. Technology feeds on itself
00:51:22 and it gets faster and faster. In about
00:51:24 40 years, the pace of change is going to
00:51:26 be so astonishingly quick that you won't
00:51:29 be able to follow it unless you enhance
00:51:32 your own intelligence by merging with
00:51:35 the intelligent technology we're
00:51:37 creating. So that's such a profound
00:51:39 transformation that we've borrowed this
00:51:41 metaphor from physics and call that a
00:51:43 singularity.
00:51:45 >> Now whoever made this particular version
00:51:48 is like if you don't want him to be
00:51:50 creepy maybe don't make it look like
00:51:52 he's uh in witness protection.
00:52:01 The singularity
00:52:01 merging with machine and earlier Elon
00:52:04 Musk thought that this might be a
00:52:06 problem. I mean with artificial
00:52:08 intelligence, we are summoning the
00:52:09 demon. You know, you know all those
00:52:12 stories where there's the guy with the
00:52:14 pentagram and the holy water and he's
00:52:15 like, "Yeah, he's sure he can control
00:52:16 the demon."
00:52:18 >> Doesn't work out.
00:52:19 >> I hope that is not the case. I hope that
00:52:22 is not where we're heading. The chances
00:52:24 that it are are not zero. What do we do
00:52:26 about this? Are we summoning a demon? Um
00:52:30 are we heading for a job apocalypse?
00:52:33 is are we basically walking into and
00:52:36 accelerating a rate of change that the
00:52:39 human animal is not capable of adapting
00:52:42 to without merging with the technology
00:52:44 and using Neuralink or some other kind
00:52:46 of hybrid transhuman cyborg stuff that I
00:52:50 think most of us would find kind of
00:52:53 repellent and scary and Borgl like in
00:52:56 the worst possible way. Anybody that
00:52:58 says they know is full of it. So I won't
00:53:00 claim to know. I have a hypothesis and I
00:53:04 have some thoughts about what's the best
00:53:05 way to handle this for us for our kids
00:53:08 and they're a little counterintuitive.
00:53:11 So, and they're probably being informed
00:53:13 by my values and wishful thinking, but
00:53:16 you know, you got to have something to
00:53:18 strive for. So first for our kids, I
00:53:22 actually think that what is most
00:53:23 important now is not especially at an
00:53:27 early age the rapid adoption of these
00:53:30 tools to do everything for a bunch of
00:53:33 reasons, but the most important one is
00:53:36 that the fact that I could do the things
00:53:38 that I demoed to you is predicated on
00:53:41 the fact that I'm pushing 50. I've got a
00:53:44 bunch of life experience. I've done a
00:53:46 bunch of things. I've learned through
00:53:47 struggle and difficulty and figuring out
00:53:49 how hard it is to make things good and
00:53:52 and and the discernment of where design
00:53:54 should be and how to actually not overdo
00:53:57 it. And if you can just push a button as
00:54:00 I did and create a nicel looking
00:54:02 website, if you haven't earned
00:54:07 discernment, you'll just say that's
00:54:09 fine. You'll just say that looks great.
00:54:12 Publish. And maybe in many instances
00:54:14 that's good enough because spending a
00:54:16 lot more time on it doesn't create any
00:54:17 value. But every aspect of your
00:54:20 discernment will atrophy. Every aspect
00:54:22 of your skills will atrophy. And if
00:54:25 you're young, you won't develop the
00:54:27 skills at all. And so it begs the
00:54:30 question, what skills do our kids need
00:54:32 in the world that's coming? I think
00:54:34 first and foremost a moral compass has
00:54:38 never been more important and never been
00:54:39 in shorter supply as far as the general
00:54:42 culture of the west and of America.
00:54:45 We've had a 100red years of progressive
00:54:48 dominance in the broadest possible sense
00:54:51 of destabilizing radicalism of blank
00:54:55 slate utopian nonsense. And none of
00:54:57 that's any good for us here. None of
00:54:59 that is is a guide. That is a path to
00:55:01 nihilism and a path to basically like s
00:55:04 succumbing to the computer and becoming
00:55:06 wall-ally, becoming just a pluggedin
00:55:08 slave. You might as well be a battery
00:55:09 from the matrix if that's going to be
00:55:11 your moral code. We need to do better
00:55:13 for our kids. So I think things like
00:55:17 classical Christian schools that focus
00:55:19 on the virtues, that's a great place to
00:55:22 start as counterintuitive as it is.
00:55:24 Waldorf schools, things that get force
00:55:27 your kids to confront the messiness of
00:55:29 the world is going to be even more
00:55:32 important than it's ever been before
00:55:35 because they need to understand what it
00:55:38 means to be a human so that they know
00:55:41 what what the human advantage still is,
00:55:45 what the social advantage still is of
00:55:48 being a person. These AIs might be
00:55:50 creating social networks for themselves.
00:55:52 There's still just probabilistic code
00:55:56 producing slop. The human experience is
00:55:59 still distinct. It's still unique and it
00:56:02 still has value. And our kids need to
00:56:05 know what that means. They should be
00:56:08 capable of reading Plato. And the second
00:56:11 piece that I think has become even more
00:56:14 important than ever and actually runs in
00:56:17 many ways counter to the path of
00:56:20 progress that we've had over the past
00:56:22 200 years since the industrial
00:56:24 revolution is the reemergence of the
00:56:26 Renaissance man of the generalist of
00:56:31 having a wide range of interests and
00:56:35 skills and being able to see things
00:56:37 through multiple perspectives.
00:56:40 as opposed to narrow hyper
00:56:43 specialization. One of the things that
00:56:45 has become pretty clear to me from using
00:56:48 this technology in a bunch of different
00:56:50 ways and trying to push the envelope
00:56:52 within the limitations of my own
00:56:54 knowledge is that it changes the nature
00:56:56 of division of labor and specialization.
00:56:59 These are the great powerful tools that
00:57:01 Adam Smith talked about in the wealth of
00:57:03 nations that unleashed prosperity. We
00:57:05 each focus on things and by focusing on
00:57:08 the one thing we get better and better
00:57:09 at it and that makes us more productive.
00:57:12 That is incredibly powerful and it's
00:57:14 still fundamentally true. But in an era
00:57:16 where all of human knowledge is
00:57:19 accessible in a way that you can access
00:57:21 it simply by talking to the computer
00:57:24 like the Star Trek computer, you have
00:57:26 infinite specialization at your
00:57:27 fingertips. And so the questions you
00:57:30 have to ask the most important questions
00:57:34 are why. What do you want to do and why?
00:57:38 Why do you want to do the next thing in
00:57:41 your life? That is about something
00:57:44 deeper. And that is about sampling. That
00:57:48 is about having a broad scope, having a
00:57:51 sense of the world because that is how
00:57:54 you'll find where your next niche will
00:57:56 be. And I I think this has never been
00:57:59 more important. There's a book I I read
00:58:02 several years ago that keeps coming to
00:58:03 my mind. I have it right here. It's
00:58:05 David Epstein. It's called Range: How
00:58:07 Generalists Triumph in a Specialized
00:58:09 World. And I think you could just say
00:58:12 how generalists Triumph in an artificial
00:58:14 intelligence world. I highly recommend
00:58:16 it. We'll put a link over at
00:58:18 dadsavesamerica.com to check it out.
00:58:20 It's very inspiring. It will give you a
00:58:22 sense of a way to approach life for your
00:58:26 kids and frankly for yourself uh to
00:58:29 navigate these changing times and be
00:58:30 able to adapt. The era of hypers
00:58:34 specialization might be coming in a
00:58:36 certain sense to an end. And what might
00:58:38 emerge out of it in a positive sense is
00:58:40 a kind of new middle ages.
00:58:44 The middle ages and the and the before
00:58:47 times the before industrial revolution
00:58:49 times were a time of generalists. It was
00:58:51 a time of do it yourself, of being a
00:58:55 one-man band, of being a family band, of
00:58:57 of your name being defined by what you
00:59:00 do. Mr. Smith is a Smith. That's where
00:59:04 Mr. Smith got his name, by being a
00:59:05 Smith, by being a blacksmith. And I
00:59:08 think that that
00:59:11 might make a resurgence, a kind of
00:59:13 craftsmanship
00:59:15 as the new old frontier, an ability to
00:59:19 actually stay in a community and still
00:59:21 have access to all of the riches of the
00:59:24 world. I think that this is my best hope
00:59:27 for what this new era unleashes, a kind
00:59:30 of abundance that can be rooted in
00:59:33 community. And I think if we can do
00:59:35 that, if we can prioritize the things
00:59:38 that are truly human, which is each
00:59:40 other, our families, our relationships,
00:59:44 um, we can get the best out of this
00:59:46 technology.
00:59:48 And if we don't do that, and if we
00:59:51 atomize and polarize and focus on the
00:59:54 things that make us angry, well, the
00:59:56 robots will win quite literally, and
00:59:58 they might decide that the world is
01:00:00 better off without us.
01:00:02 But I sure hope it doesn't come to that.
01:00:04 I know you'll have stuff to say in the
01:00:06 comments. Let me know down below. If you
01:00:08 want to mix it up with me over at X, you
01:00:11 can find me there at Johnapola. And of
01:00:13 course, we put all of the information
01:00:15 and stuff that went into this, including
01:00:16 links to the app to Dadsavesmoney over
01:00:19 at dadsavesamerica.com. And eventually
01:00:21 soon, a mostly AI built dadsmoney.com.
01:00:26 Um, I hope this has been helpful. If you
01:00:29 haven't seen these tools in action, I
01:00:30 hope it gives you a sense of what's
01:00:32 possible because I've only scratched the
01:00:34 surface. And of course, have a great