or maybe they don’t actually cache (fully) but lie and just don’t charge the user right now. at least half the users, who are probably also using the most similar tokens / prompts, wouldn’t really know the difference in latency (or care)
Because Jane Street is unabashed about greed, and yet they do not let that greed lead them into attempting to pollute and derive us of our attention every day.
Isn’t this sort of just “chain of thought” (i.e. the seminal https://arxiv.org/abs/2201.11903 ) where the user is helping the model 1-shot or k-shot the solution instead of 0-shot? I’ve used a similar technique to great effect. I feel things are so new / moving so fast that it’s hard to have common lingo. So very helpful to have a blog / example! But I wonder if the phenomena has been seen / understood before and just in smaller circles / different name.
While I like that you debunked the article . . . I want to hear an argument for where the SWE job market can grow in a post-Claude world. I might expect something like: “CEOs are naturally greedy. So after trimming the team, they then recognized (versus “replacing” people with AI) they could actually accomplish _more_ with more engineers, each empowered with AI.
But I do like folks calling out the OP for being AI spam.
It’s not cutting corners. Apple does most of their testing using strictly internal resources, like secret “mini malls” in the Silicon Valley area. They fail because this testing biases their sampling; users must sign draconian NDAs to participate, among other things. These samples are effectively biased due to Apple’s corporate culture regarding secrecy and competition. So, Apple actually works very hard. It’s just they culturally prefer a lot of techniques that their competitors (e.g. Google and Facebook) have throughly proven as inferior.
But is Google better? Not really, they killed a lot of good products like Reader.
But is Facebook better? Not really, Cambridge Analytica and Metaverse and .. facebook products are disposable.
But I think these Apple UX bugs are misdiagnosed. Yes they are atrocious. But think about how atrocious and non-representative and non-competitive Apple’s testing population is.
Appreciate the nature and scale of the internet... and also how it's changing though, yeah?
While I agree with much of the article's thesis, it sadly appears to ignore the current impact of LLMs ...
> it’s never been easier to read new ideas, experiment with ideas, and build upon & grow those ideas with other strong thinkers on the web, owning that content all along.
But, "ownership" ? Today if you publish a blog, you don't really own the content at all. An LLM will come scrape the site and regenerate a copyright-free version to the majority of eyeballs who might otherwise land on your page. Without major changes to Fair Use, posting a blog is (now more than ever) a release of your rights to your content.
I believe a missing component here might be DRM for common bloggers. Most of the model of the "old" web envisions a system that is moving copies of content-- typically verbatim copies-- from machine to machine. But in the era of generative AI, there's the chance that the majority of content that reaches the reader is never a verbatim copy of the original.
1) Assume the buyer/seller holds capital from sources that the majority of the market considers “illicit” and/or is legally sanctioned and/or physically frozen or restricted. Aka the capital can never be called (or at a discount that is unknowable) or the transaction could be later legally reversed or nullified by one or more legal entities. But of course the StableCoin market maker fails to communicate this risk. Therefore the real value of either side of the trade could be zero despite the non-zero StableCoins being transferred. Thus that’s not really a “trade” because there are hidden substantial risks.
2) Along the lines of Matt Levine “Stablecoin treasury strategy?” Consider that the buyer is a publicly listed company, and they fundraise based upon purchase of the digital asset. Then you are doing what most banks consider is not trading but fueling speculation (and normally you can’t expose average retail investors to these risks).
The innovation of StableCoins is much less about Capitalism and much more about re-packaging fraud. And given how lax the prosecution of fraud was during the Financial Crisis, there’s a big meta-bet that StableCoin “traders” will never face losses.
uv can also run even a beefy linux desktop out of file descriptors for larger projects. And does not have deterministic / reproducible installs. Still needs maturity.
A key idea premise is that LLMs will probably replace search engines and re-imagine the online ad economy. So today is a key moment for content creators to re-shape their business model, and that can include copyright law (as much or more as the DMCA change).
Another key point is that you might download a Llama model and implicitly get a ton of copyright-protected content. Versus with a search engine you’re just connected to the source making it available.
And would the LLM deter a full purchase? If the LLM gives you your fill for free, then maybe yes. Or, maybe it’s more like a 30-second preview of a hit single, which converts into a $20 purchase of the full album. Best to sue the LLM provider today and then you can get some color on the actual consumer impact through legal discovery or similar means.
A candidate wants a _competitive_ offer. While stock is almost impossible to compare across offers, candidates can at least stack-rank the company’s funding and check to see how the proffered percentage compares to the mean for the funding round. So if a company has high-percentile funding, and gives a high-percentile equity fraction, it’s a good sign to the candidate. But of course, the company could be WeWork, or even OpenAI could get risky if the tender offers stop (which will happen when/if the market crashes).
At the end of the day, it means a lot to the candidate if the company _wants to compete_ for a hire, especially in the current economy (layoff-friendly and SWE saturated, especially versus 10 years ago). A story like “your options could be worth $XXX in 4 years” I hope is not seen as competitive today.
Also know a non-smoker who got lung cancer, in particular a (rather rare) genetically sensitive form. Most of the damage ended up to the bones and brain versus the lungs.
Hugginface is mostly AWS, so these experiments might be done on an AWS-provided cluster? I wonder how many of the results are reproducible on "open market" clusters listed on e.g. https://gpulist.ai/
And/or try contacting a bank (one of the underwriters?) to see if they’ll loan you cash for taxes using the RSUs as collateral. A lot of early Uber employees were able to get loans to exercise and cover taxes, tho these were rather large sums. That said the shares are liquid so less risk.
It’s also important to weight dramatic changes in the White House this week, too, right? There’s the intel itself, but then there’s also the guy trying to control the news cycle.
Need to also consider the ones that had a qualified exit event and then the product got axed (e.g. aquihire or just customer acquisition). It’s a very different graveyard but in many cases has similar impact on the non-Founders (especially the IC SWEs).
https://www.npr.org/2026/01/23/nx-s1-5684185/doge-data-socia...