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TimPC

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Pangram’s market claims are very different from independent validations of the platform. The 99.98% rate is on a toy dataset not resembling reality.

Even if 2/10000 is true that’s nowhere near accurate enough to make aggressive accusations that create anxiety at levels people need to medicate with potentially fatal consequences.

I think pop musicians are capable of doing greater works later, but the perception of pop works are so heavily influenced by the image/presentation of the artist that we view the works as lesser. I don't think there is something fundamentally different about pop music that leads to best works being earlier relative to other genres of music beyond that.

It's easier to define safeguards and the definition of inside information for stock markets than for prediction markets though. There is plenty of information that should ban someone from prediction markets that also wouldn't meet the definition of material non-public information.

OpenAI is a bet on LLMs replacing a large chunk of the labour force in whatever sector it’s best at replacing. It’s essentially looking to get companies to pay $5k-$10k a month to have coding agents replace the output of a single software engineer.

If the S-curve levels off below that level OpenAI will be an unsuccessful company.

Big tech likes this because there are a lot more face recognition technologies in the wild in real life and being able to connect all real life data to online data is quite valuable. It's also quite possibly the largest training set ever for face recognition if ids are stored and given how ids and images are sold across many companies it seems very high probability that some company will retain the data rather than delete after use.

I think more than ever programmers need jobs where performance matters and the naive way the AI does things doesn't cut it. When no one cares about things other than correctness your job turns into AI Slop. The good news right now is that AI tends to produce things that AI struggles to do well with so large scale projects often descend into crap. You can write a C-compiler for $20,000 with an explosive stack of agents, but that C-compiler isn't anywhere close to efficient or performant.

As model costs come down that $20,000 will become a viable number for doing entirely AI-generate coding. So more than ever you don't want to be doing work that the AI is good enough at. Either jobs where performance matters or being able to code the stack of agents needed to produce high quality code in an application context.

This seems like the single worst way to measure this because by looking at chronological data you get all kinds of temporal effects. A better baseline would be to look at the difference between pre-cell phone ban scores and post cell-hone ban scores compared to other districts where the cell phone ban didn't occur.

I find it completely unremarkable that test scores went up post-COVID and feel it's very hard to tell what is causing what.

I feel like this is an inside view from the BPO community and the only part of AI they see is the part that affects BPO. But for most businesses AI strategy is not about AI for internal use but AI to either improve customer funnels or launch new products. Most of the companies I've talked to in the past year wanted a strategy for customer facing AI not internal AI.

Psychological wellbeing contributes some amount of money though in systems that pay for healthcare (especially when that includes psychiatry). It's also to a degree one of the key things government spending is hoping to produce so if it is actually producing that it's a good use of funds.

I do agree the program needs to make it doable to get the funds in order to become an artist since otherwise it's exclusively for rich artists who can be an artist while waiting for eligibilty.

The article fails to cover the main point. It's not just about putting the south at the top of the map but doing the projection from the south instead of the north which makes the south appear bigger and the north appear smaller rather than vice versa. I think top vs bottom for good vs bad is weaker than the bigger is better piece they fail to even mention.

People should be worried because right now AI is on an exponential growth trajectory and no-one knows when it will level off into an s-curve. AI is starting to get close to good enough. If it becomes twice as good in seven months then what?

I think the problem is do you want to give the AI access to prod. See the recent example where AI wiped a DB despite instructions not to (because AI sometimes does things more often when you tell it not to do something because the negative from not is not always reliably picked up)

It sounds like the Credit Card Processing system at the cashier had internet for processing credit cards etc. but the waiter app has no internet dependencies since it can transfer the order to the cashier system.

Salary inflation is much trickier to measure because it is confounded by years of experience increasing, getting promotions, etc. The distribution of the working population by seniority also changes over time so it's not self-correcting across the distribution. Assuming you have a good way of measuring it, (salary inflation/price inflation) would be an interesting Financial Quality of Life measure.

How about the silly treadmill where we waste billions of compute to compute useless proof of work type behaviours and whenever more compute gets thrown at the problem we just make it harder to ensure there isn't better output. I believe it was called buttcoin or something silly like that.

Parts of this do align well with how to maximize profits. Shared walls, progressively smaller units over time and removing balconies have been the story of condo buildings over the last generation. The area that doesn’t line up is the low end apartment fixtures. It turns out people will pay $15k for $10k better of appliances and countertops.