Boris Nikolaev

[Boris Nikolaev @botzata]

On the other hand, most advisors are either busy or not very good advisors and PhD students are left to figure it out on their own. Claude can now do for PhD students what very few advisors could in the past. So it goes both ways. Perhaps the the nature of the symbiosis will change?

[Boris Nikolaev @botzata]

@trikcode so true!

[Boris Nikolaev @botzata]

I merged Karpathy's AI jobs scores that people are calling AI slop with Eloundou et al. data from their Science (2024) paper and the new Anthropic’s measure that captures AI displacement risk.

The rank correlation of Karpathy’s scores was .82 vs human expert raters (from the Science paper) and .72 vs Anthropic's observed exposure metric.

Low scores on Karpathy index → near-zero real AI usage. High scores → 40–64% observed exposure.

Yes, this doesn't tell you whether you are going to lose your job in the future (that was not the point of his project).

But this is also not some AI generated slop or noise (even if the scores are based on a single generic prompt and derived with Gemini Flash, not even a frontier model).

To me, this is the most remarkable part of his project - that the scores are even picking something real about where LLMs are being used at work (the observed exposure metric) and track surprisingly well with the human benchmark.

This shows the practical usefulness of these tools.

One person, one lightweight LLM, and a single prompt can now produce over a weekend (as a side project) something that picks a real signal and would have taken a well-funded research team months to do a few years ago.

[Boris Nikolaev @botzata]

@vladtenev The shorts are definitely not getting squeezed in this picture. Maybe Vlad should squeeze leg day into his workout schedule though 😂

[Boris Nikolaev @botzata]

Both views can be correct and it depends how you define slop. Boris simply argued that the models are getting better and are less likely to produce sloppy code. They are already getting closer to human experts on many tasks (gpval). So if we define sloppiness by quality of output, they are getting less sloppy. In a sense, we are moving from flip phone cameras to iPhone cameras. And yes you (and karpathy) are also correct. As it gets cheaper to produce content, we make more of it. In a sense, we are entering the phase of 50 selfies a day with [inset ai output]. The quality of pictures is not as impressive anymore, just like well written posts, etc. we raise the bar. So you are right … in a word with unlimited technically perfect output what matters? After all, scarcity creates value.

[Boris Nikolaev @botzata]

Let’s say you work for Target and spend your paycheck there on groceries, clothes, toys for your kids. Target even gives you a discount to incentivize you to spend your paycheck there. Are you inflating Target’s revenue?

NVIDIA invests in AI companies → those companies buy NVIDIA GPUs they actually need to run their products → NVIDIA delivers real hardware.

Both transactions involve real products and real value. The ‘circular’ part doesn’t make either transaction fake.

Money circulates in the economy. That’s why it’s called the circular flow of income. The ‘circular’ part isn’t the problem - it’s literally how economies work! 😆

OpenAI needs massive compute infrastructure, and only 3-4 companies on Earth can provide it (Microsoft, Google, Oracle, AWS). They have deals with all of them.

The important question is “is AI demand real enough to justify the infrastructure investment?” But that’s a completely different question that the circular deals.

With 800M+ ChatGPT weekly users and real products changing how people work, the demand looks pretty real to me. The latest pew research survey shows that 30% of adult Americans now use Ai constantly and 50% use it daily.

What people are essentially debating here is whether these investments are justified. But the circular deals are not the scandal you think it is. It’s just how infrastructure investment works in emerging tech.

[Boris Nikolaev @botzata]

@Forge_Thought @AndrewYang Great point! Totally agree.

[Boris Nikolaev @botzata]

This shows basic lack of understanding how economics and finance works.

First, 50-year loans will have higher rates than 30-year loans, just like 30-year loans have higher rates than 15-year loans (currently that difference is ~ 0.75%).

This is because of arbitrage. If rates were the same, why would anyone take the shorter loan? You pick the longer loan because it gives you maximum flexibility with zero cost (you can always pre-pay the loan sooner if you want).

This is free lunch! And lenders don't offer free lunches.They charge a term premium to compensate for the risk.

If you are 35 when you buy your first home, you will pay if off when you are 85 years old. That means you have to have enough income 20 years after your retirement to do so. That's more risk too.

The outcome?

Let’s say you have a $500K house loan and conservatively assume .5% premium for the 50 year loan.

- 30-year at 7.0% -> $3,326/month, $697K total interest
- 50-year at 7.5% -> $3,201/month, $1.42M total interest

You “save” ~ $125/month but pay an extra $723K in interest (more than double).

And, no, most people are not going to invest the extra $125/month in the stock market (40% of Americans depend solely on social security for retirement).

But, and more importantly, people care largely about monthly payment affordability.

We know this from research on auto loans, which shows that for each additional year of financing, car prices increase by approximately 2.8-3%.

So, longer loan terms --> higher prices! Same will happen to housing. If monthly payments go down --> you can “afford” more --> sellers ask for more --> prices go up --> you end up with the same (possibly even higher) monthly payment but a ton more debt.

The net result is net negative for buyers. You pay more upfront, a lot more in interest, build equity slower (you are basically front loading interest payments), and you inflate the next housing bubble!

[Boris Nikolaev @botzata]

@WarrenPlatts @AndrewYang This has nothing to do with my argument. The point is about affordability. A 50 year loan should make owning a home more affordable. If you consider higher rates + higher prices, then there is no benefit at all.

[Boris Nikolaev @botzata]

That's the whole point that you are missing!

First, 50-year loans will have higher rates than 30-year loans, just like 30-year loans have higher rates than 15-year loans (currently that difference is ~ 0.75%).

This is because of arbitrage. If rates were the same, why would anyone take the shorter loan? You pick the longer loan because it gives you maximum flexibility with zero cost (you can always pre-pay the loan sooner if you want).

This is free lunch! And lenders don't offer free lunches.They charge a term premium to compensate for the risk.

If you are 35 when you buy your first home, you will pay if off when you are 85 years old. That means you have to have enough income 20 years after your retirement to do so. That's more risk too.

The outcome?

Let’s say you have a $500K house loan and conservatively assume .5% premium for the 50 year loan.

- 30-year at 7.0% -> $3,326/month, $697K total interest
- 50-year at 7.5% -> $3,201/month, $1.42M total interest

You “save” ~ $125/month but pay an extra $723K in interest (more than double).

And, no, most people are not going to invest the extra $125/month in the stock market (40% of Americans depend solely on social security for retirement).

But, and more importantly, people care largely about monthly payment affordability.

We know this from research on auto loans, which shows that for each additional year of financing, car prices increase by approximately 2.8-3%.

So, longer loan terms --> higher prices!

Same will happen to housing. If monthly payments go down --> you can “afford” more --> sellers ask for more --> prices go up --> you end up with the same (possibly even higher) monthly payment but a ton more debt.

The net result is net negative for buyers. You pay more upfront, a lot more in interest, build equity slower (you are basically front loading interest payments), and you inflate the next housing bubble!

[Boris Nikolaev @botzata]

You are not helping buyers, you are subsidizing sellers and banks.

People care about monthly affordability. What we know from the auto loan market is that for each extra year of financing car prices increase around 3%.

Same thing with housing prices. Monthly payments drop—> home prices rise to match —> buyers pay way more total debt for the same house.

Result is higher prices for everyone, decades more interest, zero real affordability gain.

https://t.co/6WVaQDN3hM

[Boris Nikolaev @botzata]

I don’t believe you. Share the task, the prompt and which AI you use. The fact that you are being so vague shows you have no clue what you are doing. For example, ChatGPTs agent mode is where you will get the best chance to complete this task. I recently asked it to extract all information from 12 months of utility bills, organize it into a spreadsheet, and then do an analysis to tell me how much I would save if I get a battery for my solar system. There was absolutely no mistakes in extracting the data and the analysis was very close to my own.

[Boris Nikolaev @botzata]

But that's a silly statement, don't you think?

If you don't have PhD-level skills, you stand no chance to evaluate what LLMs' PhD-level abilities actually are (the Dunning-Kruger effect).

That's precisely why LLMs feel like magic to so many people—it's like having 1000s of PhDs in the same room.

And if you do have a PhD? Well, then why make a big deal of something you find so unimpressive in the first place? 😂

[Boris Nikolaev @botzata]

Very interesting!

How did you guys control for gig workers using AI?

In your limitations section, you say the projects were completed in the past five years. So, it seems that your "human baseline" isn't necessarily purely human.

Also, I noticed agents had up to 1 hour to self-correct within their session. But in the real world, humans provide feedback between iterations ("fix this," "try a different approach").

I recreated your World Happiness Dashboard with Claude - took about 1 hour with some minimal instruction on my end.

The gap between "AI with very minimal human feedback" and "fully autonomous AI" seems much larger than the 2.5% automation rate suggests.

Did you consider measuring how much human interaction is needed to get acceptable results for most of these projects? That might be the more economically relevant benchmark.

Awesome work! :)

[Boris Nikolaev @botzata]

You've got some framing issues here! :)

The “blindly use”part is a strawman. Most people aren’t advocating blindly using AI for deep expert work.

The “test on your expertise” advice has a sampling problem. You are literally selecting for the domains where you are most likely to catch errors. This tells you almost nothing about the 99.9% of topics where you are not an expert and may need LLM help.

You are missing the counterfactual. For a non-expert, the real comparison isn’t “LLM vs. having deep expert knowledge.” It’s “LLM vs. spending 2 hours Googling through SEO spam vs. asking their semi-informed friend vs. giving up.”

In many cases, even an imperfect LLM is the best tool available.

The jagged frontier matters. LLMs are superhuman at some tasks and terrible at others. A blanket “don't trust them” ignores this.

Of course, healthy skepticism is warranted! So I agree with you there!

[Boris Nikolaev @botzata]

What was interesting about the article is that overall we haven’t seen an ai job apocalypse.

And it’s mostly graduates from mid-tier universities that have been hit the hardest.

Why the middle?

Companies keep top-tier grads for specialized expertise and bottom-tier for lower cost.

The middle is where AI slots in perfectly.

From the Stanford paper that came earlier this year on the same topic (and why see the effect mostly on junior positions):

“AI replaces codified knowledge, the ‘book-learning’ that forms the core of formal education. AI may be less capable of replacing tacit knowledge, the idiosyncratic tips and tricks that accumulate with experience.”

[Boris Nikolaev @botzata]

https://t.co/5eOng7JwG1

[Boris Nikolaev @botzata]

So let me get this straight. The goal is to stay away from screens to be productive so we can .... doom-scroll guilt-free one day?! 🤣

[Boris Nikolaev @botzata]

@SpencerHakimian What’s over? If you actually take the time to read the study, you will find out that after the initial surge of ai content, we’ve seen a plateau for over a year. In other words, the market is self correcting and algorithms reward quality over slop. I say really good news 😂