RC_ITR

https://www.reddit.com/r/TheSilphRoad/comments/8i7byi/pokemo...

I always ask people, in the past year, how many AI-coded apps have you 1) downloaded 2) paid for?

https://matharena.ai/?view=problem&comp=aime--aime_2026

As for MMLU, is your assertion that these AI labs are not correcting for errors in these exams and then self-reporting scores less than 100%?

As implied by the video, wouldn't it then take 1 intern a week max to fix those errors and allow any AI lab to become the first to consistently 100% the MMLU? I can guarantee Moonshot, DeepSeek, or Alibaba would be all over the opportunity to do just that if it were a real problem.

This pattern of considering 90% accuracy (like the level we've seemingly we've stalled out on for the MMLU and AIME) to be 'solved' is really concerning for me.

AGI has to be 100% right 100% of the time to be AGI and we aren't being tough enough on these systems in our evaluations. We're moving on to new and impressive tasks toward some imagined AGI goal without even trying to find out if we can make true Artificial Niche Intelligence.

https://www.booking.com/Share-Wt9ksz

Maybe he really is tied to $600 as his absolute upper limit, but also seems like something a few years from AGI would think to check elsewhere.

Typing 'Find me reservations at X restaurant' and getting unformatted text back is way worse than just going to OpenTable and seeing a UI that has been honed for decades.

If your old process was texting a human to do the same thing, I can see how Clawdbot seems like a revolution though.

Same goes for executives who vibecode in-house CRM/ERP/etc. tools.

We all learned the lesson that mass-market IT tools almost always outperform in-house, even with strong in-house development teams, but now that the executive is 'the creator,' there's significantly less scrutiny on things like compatibility and security.

There's plenty real about AI, particularly as it relates to coding and information retrieval, but I'm yet to see an agent actually do something that even remotely feels like the result of deep and savvy reasoning (the precursor to AGI) - including all the examples in this post.

Any reasonably informed person realizes that most AI start-ups looking to solve this are not trying to create their own pre-trained models from scratch (they will almost always lose to the hyperscale models).

A pragmatic person realizes that they're not fine-tuning/RL'ing existing models (that path has many technical dead ends).

So, a reasonably informed and pragmatic VC looks at the landscape, realizes they can't just put all their money into the hyperscale models (LP's don t want that) and they look for start-ups that take existing hyperscale models and expose them to data that wasn't in their pre-Training set, hopefully in a way that's useful to some users somewhere.

To a certain extent, this study is like saying that Internet start-ups in the 90's relied on HTML and weren't building their own custom browsers.

I'm not saying that this current generation of start-ups will be successful as Amazon and Google, but I just don't know what the counterfactual scenario is.

I know linguistics is descriptive not prescriptive, but it's truly amazing to me the lengths people will go to swear.

https://fred.stlouisfed.org/series/PINCOME

Parsing tax or SS payments for what a "job" is would be a logistical nightmare, because that's not what the system is designed for (unlike the BLS's system, which is designed to count jobs).

Manufacturing and mining are becoming much less correlated to the overall jobs market (likely, as you point out, b/c the government smooths the other sectors).

https://fred.stlouisfed.org/graph/?g=1Mc3I

This is despite being a relatively flat % of employment since 2010 (after a long period of decline).

https://fred.stlouisfed.org/graph/?g=1Mc4f

As mentioned, there is also the weirdness of SWE's going from 'better than the overall market' to 'worse than the overall market'.

https://fred.stlouisfed.org/graph/?g=1Mcer

Retail employment is also dislocating.

Those are just the examples I can think of with no research, I'm sure there are others.

A high-level is that 80% of the economy is very easy to track b/c it's not very volatile (teachers, for example).

What we have seen is a huge surge in unpredictability in the most volatile 20% of jobs (mining, manufacturing, retail, etc.). The BLS can't really change their methods to catch up with this change for classic backwards compatibility and tech debt reasons.

Part of the reason 'being a quant' is so hot right now is that we truly are in weird times where volatility is much higher than most people realize across sectors of the economy (i.e. AI is changing formerly rock-solid SWE employment trends, tariffs/electricity are quickly and randomly changing domestic manufacturing profitability, etc.). This means that if you can build systems that track data better than the old official systems, you can make some decent money investing against your knowledge.

I think this is a bad state of affairs, but I don't have a good solution. Any private company won't release their data b/c it's too valuable and I am reluctant to encourage the BLS to rip up their methods when backwards compatibility is a feature worth saving.

Reels isn't powered by Transformers per se (likely more of a complex mix of ML techniques), but it is powered by honest-to-goodness SOTA AI/ML running on leading-edge Nvidia GPUs.

I think, because they're so impressive, people assume Transformers = AI/ML, when there's plenty of other hyperscale AI/ML products on the market today.

I get your point, but a 1,000x+ difference in quantity cannot be ignored.

They do the same exact thing in terms of 'slowing wind down' and 'preventing the sun's energy from reaching the ground'.

This idea is understandable, but it falls apart for the same reason the wind turbine bird death concern does (the number of birds that have died due to humans liking windows is 1,000,000x the number that have died in turbines).

We do - People employed part time for Economic Reasons.

If what your looking for is 'People with salaries below the highest they've ever earned', then you're just going to get a very noisy metric of sales people on bad commission years, etc.

As you point out, there's no purchase level data about what's imported vs. not.

The way this is handled is that this quarter's imports are set against this quarter's consumption - basically the method assumes the import/domestic mix of business inventories stays the same (true enough in the long run, very incorrect in short term shocks).

That's why extremely disingenuously the AP says:

>Trade deficits reduce GDP. But that’s just a matter of mathematics. GDP is supposed to count only what’s produced domestically, not stuff that comes in from abroad. So imports — which show up in the GDP report as consumer spending or business investment — have to be subtracted out to keep them from artificially inflating domestic production.

Answer: What happened here[1] is that the BLS makes a bunch of assumptions to get data out in time (preliminary figures based on historical seasonal trends, etc.) but this quarter, their assumptions about consumer spend were far too aggressive.

It happens all the time, especially in strange times like 1Q was, but there's also career/political incentive to be aggressive on the advanced data, since that's what drives the big headlines.

[1]https://www.bea.gov/system/files/gdp1q25-3rd-chart-02.png

This is prima fascia false. Credit, especially artificially low interest rate credit like this, can be used for a ton of reasons, including 'beating inflation.'

I bring this up because so many diligent savers in 2019/2020 got screwed by waiting to buy big tickets items.

What I am ultimately trying to say is that the large majority of people on this forum see the symptom of a broken society (homelessness and drug addiction) and for whatever reason, refuse to believe that a complex network of problems is actually the thing that should draw our 'hacker' focus.

Like sure, you clearly had a negative experience with permitting that caused you to have an expensive fine and feel resentment that other people do 'worse' things 'scot-free'.

Would fining a homeless person more money actually solve your or the city's problems? No. The person would just not pay, because again, they have nothing to lose.

Ultimately, I think where we agree is that the idea of law needs to evolve to include both punishment and state funded / enforced humanitarian care.

The reason that I think this will never happen in America is because we are an inherently vengeful people with a dark history of race-based hatred and a fundamental disdain for paying taxes that fund public goods.

All three things were illegal. All three things were frowned upon.

What you are actually saying is that there are many people on the streets of San Francisco who are otherwise excluded from American society and therefore have almost 'nothing to lose.' Those people often break laws, largely because the social contract has excluded them from the benefits of society (for example, knowing you have access to indoor plumbing).

This article is about a change for the fortunate ones like you and me who do feel like we get a fair shake from the social contract and therefore follow most laws (I assume).

Sure, if you want to get into theoretical finance, OpenAI could have sold these new shares for cash, so technically there's no difference, but OpenAI is only spending opportunity cost cash, rather than fiat.

OpenAI's fiat likely still goes to the things you'd expect, like training models and paying for inference.

A driverless car can very easily do things and make money while I'm waiting for it.

In some scenarios, people rent out their owned cars during the day to avoid this massive opportunity cost, but I doubt that will be the most efficient model.

In what other asset class ever has it made sense for the capital owners to be an extremely long tail of people, rather than a large corporate owner? Especially something as high velocity and fungible as cars.

We don't even know if tiny doses or artificial radiation are good or bad for you.

That's the straw that just pushed me to live my life.