It is an interesting divide. "German" is both an ethnicity and a citizenship, and it's possible to become one but not the other. "American" on the other hand is purely a citizenship, and so it is possible to become an American after immigrating.
I have high hopes that America will be one of the few countries on earth to resist the tendency towards a surveillance state. Just because it’s such an individualistic anti-government culture in many parts.
There are so many reasons why adding cameras helps with policing, safety, public order. But it has to be resisted on principle because the government can’t always be trusted and rules aren’t always right.
AI is automating all the easier tasks in people’s jobs, leaving them to spend 8 hours a day on the hardest problems which AIs cannot yet solve.
Software engineers are probably already familiar with the feeling of burnout from thinking too hard. The reality is very few people can work on the hardest problems they’re capable of for 8 hours a day.
Writing routine Python code for some system you know well is not that mentally taxing. Managing an agent that rapidly finishes tasks but needs careful review and big-picture planning is much more exhausting, and has higher returns on intelligence and deep careful thought.
I think this points towards the opposite conclusion of the OP. It’s not realistic to expect 8 hours of hard work out of a knowledge worker. Remote work naturally allows this transition, as employees can work a bit less but still overachieve with AI.
This won’t be able to run any of the cutting edge models. And the models it can run can be served from cloud providers for very cheap - like <$1 per million tokens for the latest deepseek.
It’d take many years to break even on your $6000 investment, meanwhile better and better models will come out that the DGX can’t run.
It's also shockingly twitter-nerd-coded. "The cure for token anxiety", it advertises. To be honest it's hard to see why anyone would buy this product so maybe they decided to take a wild swing with the marketing. The only use is people who really, really, want to run models locally vs getting a much cheaper and higher performance result from a cloud host.
I think this is a great idea. Wouldn't have guessed this would be possible so I looked into how it'd actually be implemented.
I guess this is done on the device as a VPN via Apple's NetworkExtension config. But instead of a normal VPN where traffic goes through a server, the app just locally applies rules based on the app the packet came from and then routes them normally to their destination.
I think it's probably too soon to say. I certainly still feel that large coding tasks are getting better and better with each model. I'd guess lawyers, doctors, etc feel similarly.
It feels like the only way to push the limits of newer models is with really long context questions that require reasoning. Any short request will naturally just be within the distribution of all the recent models so there isn't a performance difference there.
I think the near future is looking like a bunch of business-critical tasks that scale infinitely with better reasoning, all being done on whatever the most advanced model is at a high cost. Trading stocks, running a business, looking for tax dodges, writing high-performance code. These are all things where there's a tangible return on each jump in reasoning.
I feel like this is one of the most advantaged times in history in terms of regular citizens having access to cutting edge tools.
Looking online it seems like the low end estimate might be $30k a year for such math researchers? And ChatGPT pro or whatever you want will run $100 a month, and should be coverable by grants. I’m quite sure matlab alone cost more in the past
Such suspicious phrasing lol. So you’re saying Paul Graham and his wife Jessica have 800 MILLION dollars worth of OpenAI stock, and that’s not so significant?
Price targeting can help the poor in some cases and hurt them in others. For essentials where the need to purchase is high and the provider has a semi-monopoly, dynamic pricing leaves everyone worse off. For instance, think of groceries where there is only one store nearby or medicines with only one producer.
On the other hand, for something like a Netflix subscription, price discrimination DOES tend to help the poor users out. Netflix is 10x cheaper in third world countries for the exact same product. If they were forced to charge the same price everywhere, they would just charge everyone the US price and foreign users would be left out.
Yeah I just don't buy that it would somehow help AI companies for everyone to be existentially afraid of their technology. It seems much more reasonable to think that they really believe the things they're saying, than that it's some kind of 4d chess.
Additionally Dario has just been really accurate with his predictions so far. For instance in early 2025 he predicted that nearly 100% of code would be written with AI in 2026.
I disagree. While their core products have stayed similar, they keep getting better at ads after Apple's privacy changes in 2021 hurt their efficiency. And Instagram has changed quite a bit, with reels growing to half of total IG usage. (Of course these are dystopian products but I'm just trying to be objective here).
To me a company at FB's scale is inevitably going to be optimizing around the margins. I mean you could argue any of Google, Amazon, FB, have had basically the same cash cows for 10+ years now.
It's surprisingly simple to switch. I mean both products offer basically identical coding CLI experiences. Personally I've been paying for Claude max $100, and ChatGPT $20, and then just using ChatGPT to fill in the gaps. Specifically I like it for code review and when Claude is down.
I'd guess AI has made the average SWE around twice as productive at this point. This is a sort of efficiency shock, where companies suddenly need to find twice as much productive work to do or start firing employees. FB probably had a bunch of slack to absorb this but ultimately it's just hard to find that much work all at once.
I predict that tech companies will hire back a lot of this lost headcount over time. Although AI will keep getting better, so there's more downward pressure coming. Facebook, Amazon, and Google have had flat headcount since 2022, and this layoff will reduce FB's size back to 2021 levels.