Offshore
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God of Prompt
RT @godofprompt: 🚨 Holy shit… Stanford just published a paper that questions whether we even need humans to study humans.
The title sounds like a joke:
“This human study did not involve human subjects.”
But it’s dead serious.
The researchers are asking a controversial question:
Can LLM simulations count as behavioral evidence?
Here’s the core idea.
Instead of recruiting thousands of participants, running surveys, and waiting weeks for results, they simulate people using large language models.
Not generic prompts.
But structured simulations where the model is assigned demographic traits, preferences, beliefs, and contextual constraints.
Then they test whether the simulated responses statistically match real-world human data.
And disturbingly… they often do.
Across multiple behavioral tasks, the LLM-generated “participants” reproduced known human patterns:
• Established psychological biases
• Preference distributions
• Decision-making trends
• Even demographic splits
Not perfectly. Not universally.
But far closer than most people would expect.
The key contribution of the paper isn’t “LLMs are human.”
It’s validation.
They systematically compare simulated outputs to ground-truth human datasets and evaluate alignment using statistical benchmarks.
When the distributions match, the simulation isn’t just storytelling.
It becomes empirical evidence.
That’s the uncomfortable shift.
If a sufficiently constrained LLM simulation reproduces real behavioral patterns, does it become a legitimate experimental proxy?
Because if the answer is yes, this changes everything:
• Behavioral economics
• Political science
• Market research
• Policy testing
• UX experimentation
You could prototype social interventions before deploying them in the real world.
You could stress-test messaging strategies across simulated demographics.
You could explore rare edge-case populations without recruitment bottlenecks.
But here’s where Stanford is careful.
The models don’t “understand” humans.
They reflect training data patterns.
They can amplify biases.
They can collapse under distribution shift.
And they can simulate plausibility without causality.
So the paper doesn’t claim replacement.
It argues for calibration.
LLM simulations can be useful behavioral instruments if validated against real data and bounded within known limits.
That’s the distinction.
Not synthetic humans.
Synthetic behavioral priors.
The wild part?
This paper forces academia to confront something bigger:
If large models encode large-scale behavioral regularities from the internet, they become compressed maps of human tendencies.
Not minds.
Maps.
And maps can be useful.
We’re moving from “AI as text generator” to “AI as behavioral simulator.”
The ethics, methodology, and epistemology implications are massive.
Because once simulation becomes statistically reliable, the bottleneck in social science shifts from data collection to model alignment.
And that might be the real revolution hidden in this paper.
tweet
RT @godofprompt: 🚨 Holy shit… Stanford just published a paper that questions whether we even need humans to study humans.
The title sounds like a joke:
“This human study did not involve human subjects.”
But it’s dead serious.
The researchers are asking a controversial question:
Can LLM simulations count as behavioral evidence?
Here’s the core idea.
Instead of recruiting thousands of participants, running surveys, and waiting weeks for results, they simulate people using large language models.
Not generic prompts.
But structured simulations where the model is assigned demographic traits, preferences, beliefs, and contextual constraints.
Then they test whether the simulated responses statistically match real-world human data.
And disturbingly… they often do.
Across multiple behavioral tasks, the LLM-generated “participants” reproduced known human patterns:
• Established psychological biases
• Preference distributions
• Decision-making trends
• Even demographic splits
Not perfectly. Not universally.
But far closer than most people would expect.
The key contribution of the paper isn’t “LLMs are human.”
It’s validation.
They systematically compare simulated outputs to ground-truth human datasets and evaluate alignment using statistical benchmarks.
When the distributions match, the simulation isn’t just storytelling.
It becomes empirical evidence.
That’s the uncomfortable shift.
If a sufficiently constrained LLM simulation reproduces real behavioral patterns, does it become a legitimate experimental proxy?
Because if the answer is yes, this changes everything:
• Behavioral economics
• Political science
• Market research
• Policy testing
• UX experimentation
You could prototype social interventions before deploying them in the real world.
You could stress-test messaging strategies across simulated demographics.
You could explore rare edge-case populations without recruitment bottlenecks.
But here’s where Stanford is careful.
The models don’t “understand” humans.
They reflect training data patterns.
They can amplify biases.
They can collapse under distribution shift.
And they can simulate plausibility without causality.
So the paper doesn’t claim replacement.
It argues for calibration.
LLM simulations can be useful behavioral instruments if validated against real data and bounded within known limits.
That’s the distinction.
Not synthetic humans.
Synthetic behavioral priors.
The wild part?
This paper forces academia to confront something bigger:
If large models encode large-scale behavioral regularities from the internet, they become compressed maps of human tendencies.
Not minds.
Maps.
And maps can be useful.
We’re moving from “AI as text generator” to “AI as behavioral simulator.”
The ethics, methodology, and epistemology implications are massive.
Because once simulation becomes statistically reliable, the bottleneck in social science shifts from data collection to model alignment.
And that might be the real revolution hidden in this paper.
tweet
Offshore
Photo
Fiscal.ai
Remitly Global has grown its active customers ~10X since 2019.
2019: 948k
2020: 1.9M
2021: 2.8M
2022: 4.2M
2023: 5.9M
2024: 7.8M
2025: 9.3M
That's a 46% CAGR over 6 years.
$RELY https://t.co/VvbQLgoaHA
tweet
Remitly Global has grown its active customers ~10X since 2019.
2019: 948k
2020: 1.9M
2021: 2.8M
2022: 4.2M
2023: 5.9M
2024: 7.8M
2025: 9.3M
That's a 46% CAGR over 6 years.
$RELY https://t.co/VvbQLgoaHA
tweet
Offshore
Video
God of Prompt
RT @godofprompt: Every client call I used to walk into blind.
No idea what their business does, what's broken, or what they actually need.
Now an AI agent briefs me before I even say hello.
New YT video dropped 👇
https://t.co/DHliL0hjLJ
tweet
RT @godofprompt: Every client call I used to walk into blind.
No idea what their business does, what's broken, or what they actually need.
Now an AI agent briefs me before I even say hello.
New YT video dropped 👇
https://t.co/DHliL0hjLJ
tweet
anon
RT @Basalt_Capital: I recently invested in Espec (https://t.co/8Glmwuvv0Q). Espec is the #1 producer of environmental test chambers with a global market share of 30%. These chambers assess the impact of temperature and humidity fluctuations on electronic components and systems throughout R&D. Management prioritizes higher-margin laboratory testing services over lumpy equipment sales and focuses on rapidly evolving AI semiconductors, autonomous driving, and satellite communications markets. Orders received in the target markets increased 83% YoY in the first half of 2025. Last November, Espec announced a JPY 3.5 billion stock buyback, equivalent to 4% of the total shares. I see 60-70% valuation upside. I think investors underestimate the improvements in Espec’s business model, growth opportunities, and capital allocation.
tweet
RT @Basalt_Capital: I recently invested in Espec (https://t.co/8Glmwuvv0Q). Espec is the #1 producer of environmental test chambers with a global market share of 30%. These chambers assess the impact of temperature and humidity fluctuations on electronic components and systems throughout R&D. Management prioritizes higher-margin laboratory testing services over lumpy equipment sales and focuses on rapidly evolving AI semiconductors, autonomous driving, and satellite communications markets. Orders received in the target markets increased 83% YoY in the first half of 2025. Last November, Espec announced a JPY 3.5 billion stock buyback, equivalent to 4% of the total shares. I see 60-70% valuation upside. I think investors underestimate the improvements in Espec’s business model, growth opportunities, and capital allocation.
tweet
X (formerly Twitter)
anon (@anonymous3nibrv) on X
RT @Basalt_Capital: I recently invested in Espec (https://t.co/JAOkaU78Ly). Espec is the #1 producer of environmental test chambers with a…
Offshore
Photo
Dimitry Nakhla | Babylon Capital®
RT @DimitryNakhla: Chris Hohn increased his $SPGI position by ~$313M at a reported price of $522
Yet you were afraid to buy $SPGI under $400 because $SPGI will be vibe coded by Claude… even though it can’t… https://t.co/BqUabfZVIm
tweet
RT @DimitryNakhla: Chris Hohn increased his $SPGI position by ~$313M at a reported price of $522
Yet you were afraid to buy $SPGI under $400 because $SPGI will be vibe coded by Claude… even though it can’t… https://t.co/BqUabfZVIm
Chris Hohn TCI Q4 25’ 13F (Dataroma)
Top 5 holdings: $GE $V $MSFT $MCO $SPGI
Foreign securities excluded $SAF https://t.co/EBdedJYGxo tweet
Offshore
Video
Moon Dev
Openclaw can replace your employees or give them super powers
But the way everyone is using it right now is actually more expensive then just paying people
I got the price down 95% so I can scale https://t.co/UjqtgW924W
tweet
Openclaw can replace your employees or give them super powers
But the way everyone is using it right now is actually more expensive then just paying people
I got the price down 95% so I can scale https://t.co/UjqtgW924W
tweet
anon
RT @JoeValue: NOW FREE - My highest conviction idea 🇯🇵
Tobila Systems $4441.T $4441.JP
Smoak Capital (@dsmoak98) just published an excellent summary (link below).
Daniel at Smoak Capital has an exceptional 37.4% CAGR since 2018!
Smoak Capital owns 7.3% of Tobila.
Disclaimer: Personal opinions only, not investment advice.
Links to Smoak Capital Letter and my own writeup below:
tweet
RT @JoeValue: NOW FREE - My highest conviction idea 🇯🇵
Tobila Systems $4441.T $4441.JP
Smoak Capital (@dsmoak98) just published an excellent summary (link below).
Daniel at Smoak Capital has an exceptional 37.4% CAGR since 2018!
Smoak Capital owns 7.3% of Tobila.
Disclaimer: Personal opinions only, not investment advice.
Links to Smoak Capital Letter and my own writeup below:
tweet
anon
So many pitches on JP stocks recently. Learned early on that pitches should start with quick valuation overview (p/b, RE booked at cost, cross-shares, ev/ebit, margins, or whatever is your pet peeve) and then why you think earnings are inflecting and by when. It's that simple.
tweet
So many pitches on JP stocks recently. Learned early on that pitches should start with quick valuation overview (p/b, RE booked at cost, cross-shares, ev/ebit, margins, or whatever is your pet peeve) and then why you think earnings are inflecting and by when. It's that simple.
tweet
Offshore
Photo
anon
RT @OpulentVocation: - George Soros interaction with Tatsuro Kiyohara (one of Japans greatest investors)
Anyone trying to raise capital needs to take this into serious consideration!! 👌🏽👌🏽👌🏽 https://t.co/0SmLpqwgRi
tweet
RT @OpulentVocation: - George Soros interaction with Tatsuro Kiyohara (one of Japans greatest investors)
Anyone trying to raise capital needs to take this into serious consideration!! 👌🏽👌🏽👌🏽 https://t.co/0SmLpqwgRi
tweet
God of Prompt
RT @godofprompt: Are call centers cooked?
This tool builds a voice agent in <10 mins for any website.
Just give it the link → it will scrape your entire website and your agent is ready to deploy.
tweet
RT @godofprompt: Are call centers cooked?
This tool builds a voice agent in <10 mins for any website.
Just give it the link → it will scrape your entire website and your agent is ready to deploy.
tweet
anon
Tatsuro Kiyohara: "The market is always on the side of the minority. If you trade with the same thinking as the majority, you are likely to suffer big losses when wrong, but if you trade with minority thinking, your losses are smaller."
I suck because I follow trends (period).
tweet
Tatsuro Kiyohara: "The market is always on the side of the minority. If you trade with the same thinking as the majority, you are likely to suffer big losses when wrong, but if you trade with minority thinking, your losses are smaller."
I suck because I follow trends (period).
why do i suck so much tweet
X (formerly Twitter)
anon (@anonymous3nibrv) on X
why do i suck so much
Moon Dev
Why Your $600 Mac Mini Is a 300K Mistake: The $10 Server Alpha for Scaling 500 AI Agents
if you were about to spend three hundred thousand dollars on hardware to run your trading business, you would probably feel like a king until you realized a ten dollar server could do the exact same thing. saving a quarter million dollars before breakfast isn't just a clickbait headline, it is the reality of what happens when you stop following dogma and start looking at the data.
there is a very specific reason why most people who try to automate their trading fail within the first forty eight hours, and it has nothing to do with their strategy. most people get trapped in the hardware loop or the technical overwhelm of the terminal, but i am going to show you how to bypass all of that and build an army of five hundred ai agents
my name is moon dev i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading so i learned to code as in the past i spent hundreds of thousands on devs for app, thinking i would not be able to code myself. w/ bots you must iterate to success so i decided to learn live on youtube, and now we are here, fully automated systems trading for me instead of getting liquidated
the journey started with me standing in costco buying mac minis because i thought the only way to scale my openclaw setup was to have physical machines sitting in my apartment. i was sitting there on the couch ready to order three more and a bunch of portable monitors until i realized i was about to build a clunky physical farm that would be a nightmare to manage.
i have been roasting people for months about why they buy mac minis when they could just use apis, but then i realized i needed different environments to run these agents independently. it was not until i hopped on a private zoom with some data dogs that the real alpha started to leak out
this is where jane the hosting queen enters the story and completely shatters my perspective on what it costs to scale an automated trading business. she has been running hosting companies for over twenty years and dropped a truth bomb that saved me over two hundred racks in a single afternoon.
the secret is not in the hardware you can touch, but in the specific way you set up a cheap ubuntu server to behave like a high end mac. most people are terrified of the linux command line because it feels like staring into the abyss, but there is a bridge that makes it as easy as using your own laptop
if you want to follow the jim simons approach, you have to do things that others are not doing. while everyone else is debating whether they should run local ai or use the anthropic api, i am focused on launching five hundred independent agents that work twenty four seven for me
most traders are stuck in their own heads living with the results of other people's thinking, which is exactly what steve jobs warned us about. i decided to test every environment: the mac mini, the windows vps, and the ubuntu desktop to see which one actually lets you move at the speed of light
the mac mini experience is luxury, there is no denying that. you plug it in, run a few commands like xcode select install and curl the nvm setup, and you are basically in the game
but if you are trying to scale to hundreds of bots, paying six hundred dollars a pop is a three hundred thousand dollar mistake when you could be paying nine dollars and fifty cents per machine. the windows vps is the middle ground that everyone thinks is a good idea, but it is actually a trap that will eat your time and sanity
trying to work in a windows terminal is a janky experience that makes simple tasks like copying an api key feel like a final boss battle. i almost capitulated on the entire project because the windows vps was so frustrating and slow compared to the mac experience
this leads us to the real alpha that art dropped in the chat about a hidden tool called open code z[...]
Why Your $600 Mac Mini Is a 300K Mistake: The $10 Server Alpha for Scaling 500 AI Agents
if you were about to spend three hundred thousand dollars on hardware to run your trading business, you would probably feel like a king until you realized a ten dollar server could do the exact same thing. saving a quarter million dollars before breakfast isn't just a clickbait headline, it is the reality of what happens when you stop following dogma and start looking at the data.
there is a very specific reason why most people who try to automate their trading fail within the first forty eight hours, and it has nothing to do with their strategy. most people get trapped in the hardware loop or the technical overwhelm of the terminal, but i am going to show you how to bypass all of that and build an army of five hundred ai agents
my name is moon dev i believe that code is the great equalizer because through losing money with liquidations and over trading i knew i had to automate my trading so i learned to code as in the past i spent hundreds of thousands on devs for app, thinking i would not be able to code myself. w/ bots you must iterate to success so i decided to learn live on youtube, and now we are here, fully automated systems trading for me instead of getting liquidated
the journey started with me standing in costco buying mac minis because i thought the only way to scale my openclaw setup was to have physical machines sitting in my apartment. i was sitting there on the couch ready to order three more and a bunch of portable monitors until i realized i was about to build a clunky physical farm that would be a nightmare to manage.
i have been roasting people for months about why they buy mac minis when they could just use apis, but then i realized i needed different environments to run these agents independently. it was not until i hopped on a private zoom with some data dogs that the real alpha started to leak out
this is where jane the hosting queen enters the story and completely shatters my perspective on what it costs to scale an automated trading business. she has been running hosting companies for over twenty years and dropped a truth bomb that saved me over two hundred racks in a single afternoon.
the secret is not in the hardware you can touch, but in the specific way you set up a cheap ubuntu server to behave like a high end mac. most people are terrified of the linux command line because it feels like staring into the abyss, but there is a bridge that makes it as easy as using your own laptop
if you want to follow the jim simons approach, you have to do things that others are not doing. while everyone else is debating whether they should run local ai or use the anthropic api, i am focused on launching five hundred independent agents that work twenty four seven for me
most traders are stuck in their own heads living with the results of other people's thinking, which is exactly what steve jobs warned us about. i decided to test every environment: the mac mini, the windows vps, and the ubuntu desktop to see which one actually lets you move at the speed of light
the mac mini experience is luxury, there is no denying that. you plug it in, run a few commands like xcode select install and curl the nvm setup, and you are basically in the game
but if you are trying to scale to hundreds of bots, paying six hundred dollars a pop is a three hundred thousand dollar mistake when you could be paying nine dollars and fifty cents per machine. the windows vps is the middle ground that everyone thinks is a good idea, but it is actually a trap that will eat your time and sanity
trying to work in a windows terminal is a janky experience that makes simple tasks like copying an api key feel like a final boss battle. i almost capitulated on the entire project because the windows vps was so frustrating and slow compared to the mac experience
this leads us to the real alpha that art dropped in the chat about a hidden tool called open code z[...]