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I think what you say would have be fair if Elon's and his fanboys' stance was "we need more data" rather than "we will be able to scale self-driving cars very quickly, very soon".

There's a somewhat niche game publisher that had very gamer-friendly practices. At some point they released older games for free, and for new popular ones they were relatively friendly to mods. Now they only operate a lootbox game. The sad reality of commerce.

> I have to learn their processes/tools/etc from reading the docs. > So I'm probably coming in at like 20% better than junior.

There are firms that take that to heart, and there is indeed a lot of truth in it. A large amount of skills and knowledge just aren't transferable when switching jobs. But I think it's not hard to create more than 20% of the value. And even if it really is 20% of the value, the profit generated from the work might actually be more than the salary gap anyway, and the 1-year growth curve might be faster for a senior than a junior.

Anthropic and OpenAI are essentially betting that a somewhat small difference in accuracy translates to a huge advantage, and continuing to be the one that's slightly but consistently better than others is the only way they can justify investments in them at all. It's natural to then consider that an agent trained to use a specific tool will be better at using that tool. If Claude continues to be slightly better than other models at coding, and Claude Code continues to be slightly better than OpenCode, combined it can be difficult to beat them even at a cheaper price. Right now, even though Kimi K2 and the likes are cheaper with OpenCode and perform decently, I spend more than 10x the amount on Claude Code.

Their bosses are likely happier for the lower downtime required to run the software anyway.

At some point velocity will slow down too. Figuring out edge cases in production to add or subtract a few lines, or backtracking from a bad change.

I suspect depreciation will be a bit slower for a while, because there is a supply crunch.

The replacement of employment income tax with corporate or dividend income tax is not fully efficient. In the sense that the tax rates are different, they benefit different governments, through different time horizons (in case of dividends). While I agree it would be practical to rely on earnings tax when AI broadly replaces labor, we can still answer the obviously rhetorical question (similar to how "drinking ones own cerebral fluid" is obviously rhetorical) of "should AI pay taxes" - that there may need to be a tax reform.

Yeah, apologies if it was too harsh. I was more irked by someone else who kept trying to asset it's an easy problem, and confused it with your display of raw curiosity, which is something I don't wish to discourage.

Cheaters don't have to play like normal people to avoid detection. They just have to make it expensive to police them. For example, the game developer may be afraid of a even a 10% false positive ban rate, and as a result won't ban anyone except perhaps a small number of clean-cut cases.

Throwing in ML jargon and going straight to modelling before understanding the problem reduces your credibility as a data scientist in front of engineers and stakeholders.

As always, one of the most difficult parts is getting good features and data. In this case one difficulty is measuring and defining the reaction time to begin with.

In Counter Strike you rely on footsteps to guess if someone is around the corner and start shooting when they come close. For far away targets, lots of people camp at specifc spots and often shoot without directly sighting someone if they anticipate someone crossing - the hit rate may be low but it's a low cost thing to do. Then you have people not hiding too well and showing a toe. Or someone pinpointing the position of an enemy based on information from another player. So the question is, what is the starting point for you to measure the reaction?

Now let's say you successfully measured the reaction time and applied a threshold of 80ms. Bot runners will adapt and sandbag their reaction time, or introduce motions to make it harder to measure mouse movements, and the value of your model now is less than the electricity needed to run it.

So with your proposal to solve the reaction time problem with KL divergence. Congratulations, you just solved a trivial statistics problem to create very little business value.

Micron cuts off the business because there is a much more profitable place to deploy their capacity. The real reason Micron has a resource crunch that forces them to exit a steady business is that enterprise now places a huge premium on things didn't use to be that important.

This massive tide floats all boats and there will be smaller players filling the gap. With slightly worse chips at first yes, but historically DRAM had been a cyclical businesss where new manufacturing capabilities were brought online en masse after a boom.

Sure, I stand corrected.

It will probably increase the number of people deemed useless by the economy and the death rate of those people will be high.

1% of the world is over 800m people. You don't know if the net impact will be an improvement.

Just speculating, but if your cardiovascular function degrades due to cholesterol, it should have an impact on the brain.

The point is that risks of the circularity cannot be established well if one leg isn't quite dangerous. Nvidia's direct exposure is much more limited than it seems. Additionally in your example, Coreweave is tiny. It's mainly companies like OpenAI that are highly leveraged.

>Nvidia has invested billions in previous rounds of OpenAI raises also. Pretty sure it is not nothing.

Ok I stand corrected, but the main point is that the "circular" risk more refers to the recent 100B "investment", and that is quite misleading.

The statement here that Nvidia invests in OpenAI is a bit misleading. Nvidia would pay out nothing to OpenAI if OpenAI turns out to be too poor to pay for capacity. So they are not that exposed to the death of OpenAI specifically. They would be more at risk of making too many GPUs to prepare for the deals.

Oracle takes a lot more risk, but in case OpenAI fails to grow quickly, it can still probably find buyers for its capacity in the next 5 years. There are many rich firms that will continue to invest in AI whether or not AI makes money.

This is a poor analogy. Magnus Carlsen stays because chess consumers decide to pay for humans even though they are inferior to Stockfish. BigCorp will always pick machine over you if they can.

Einstein published his relativity papers originally in German.

It's a bit of an aside but I believe this is one reason Zuckerberg's vision for establishing the superintelligence lab is misguided. Including VCs, too many people get distracted by rock stars in this gold rush.

Also ironically their Chinese made car is said to have better build quality than the US made one.

The only reason US doesn't have an EV cheaper than that is a >100% tariff on Chinese EVs.

Then the question becomes why would they help a company that competes with their portfolio companies. And even stronger case that they got some shares in return.

On one side, you have an agent calculating the revenue.

On the other side, you have an SQL that calculates the revenue

Compare the two. If the two disagree, get the AI to try again. If the AI is still wrong after 10 tries, just use the SQL output.

But why would tesonet spend resources to help a competitor to start? I'd be surprised if there wasn't at least an equity deal.

I simply don't use a headset or a webcam with my home Linux setup, because it's often been a hassle to deal with, and my work setup is separate. For screen-sharing type coding interviews, I have a perfectly functional remote SSH setup from my windows laptop, which took less time to setup than the last time I fiddled with a bad headset connection on Linux a long time ago. I find the "not using all of screen real estate" accusation to be strange as well, because usually screen-sharing is ergonomically limited to 1 screen, but people may usually work with two screens and not have developed habits to make 1 screen work.

Yeah, seems I'd be doomed for doing interviews on my Windows laptop for the webcam and the compatibility with my bluetooth headset rather than my linux desktop. Tunnel vision and a lack of empathy are negative signals, so you could say I'd have dodged a bullet, but unfortunately in these situations I'd need the job more than the job would need me.

You can choose to invest 350 billion in the real economy, or 350 million in TrumpCoin.

Yeah, Nvidia has trillions at stake, Intel a mere 100B. It's more in the interests of Nvidia to interfere with Intel's GPU business than to help it, and the only things they want from Intel are the fabs.