In any case, reading summaries (and occasionally following up by reading the full article) is more enjoyable and you learn more per unit of time. Most articles are mostly garbage. And even insightful and informative articles can often be compressed with minimal loss of conveyed insight and information. Typical example is some of Paul Graham essays (I say some because only some are worth reading).
There are generally two major reasons why programmers don't like what's happening. One is about jobs and money, the other is about craft, meaning, enjoyment. Somewhere in the middle is social status and perceived value of intelligence.
I wonder what's the ratio of these 2 on Hacker News and similar spaces, many posts and comments seem kind of vague about this.
For me, it's mainly about jobs and money. If I was retired or in a safe job, I would watch all of this with excitement. Don't get me wrong, I can fully empathize with the other stuff. I love thinking, creating and inventing stuff that is high quality technically and UX-wise and makes people's lives better.
But at the end of the day, job and money is easily at the top of the "Maslow's hierarchy". I can easily have a similarly happy life without programming or without building products (I don't enjoy programming at work anyway).
Well what I'm worried about is that as AI gets better, everyone will be able to use AI to produce things. Just describe the product, or just point to an existing product, and that's it. In other words, AI could became better than every developer while being cheaper. So you won't be able to get paid for your work as a developer and will need to either retire or find another source of income.
I do think we need solutions like UBI, universal housing and universal healthcare. I'm fortunate enough to have the skills and mindset that I feel comfortable in the direction we're going. Just like with all technology, those who are excited and having fun with it are better positioned than those who fear or resist it.
Well this is what I was hinting at in my original comment. The main determinant of how people feel about AI is whether it threatens their source of income because at the end of the day, that's far more important than everything else.
Sure, you will be slightly better positioned if you're excited about this tech, but the impact will be typically marginal, IMHO.
Not sure about UBI. There will be enough jobs for the foreseeable future, AI only threatens the "sitting behind a computer" class of comfy jobs. But this is a tangential topic...
Correct me if I'm wrong but I think that a few years old version of Stockfish running on a modern MacBook Air with 1 min per move is unbeatable if the game starts from the initial position.
Even if the opponent is the latest Stockfish with 1000x more time per move, it will always be a draw.
I asked about this a few years ago in a Stockfish Discord and the above claim is what someone implied, if I remember correctly.
This sounds plausible. But otherwise, there are "tournaments" like the TCEC which is for bots only and the way it works is, the bots are adjusted to play a specific opening and they're on their own after the Nth move.
Stockfish has been dominant for a long time. And a later version of Stockfish would outperform an earlier version given the same time control.
Basically this optimization means that stockfish will sometimes take a bad read from a cache (so it will take an evaluation of the position from cache which was calculated for a different position).
It's fairly random when this will trigger a bad play, but if you brute force vs any deterministic setup you will find it eventually.
But even withtout it - you can just implement a kind of a brute-force heap of positions using stockfish's own eval and you can find wins from almost any position even on fairly high playout count.
I got as far as 32M from different even starting positions, but I spent compute to find as many games as possible rather than as deep as possible.
That point about Elo is irrelevant. Games on Fishtest use bullet-like time controls (60+0.6). Significantly shorter than 1 min per move.
As originally suggested, when running modern Stockfish at 60 seconds per move the games overwhelmingly tend to draw. Even when the older engines make slightly worse moves.
A faster engine is still very useful in practice, for example for position evaluations in game review.
Not that an engine evaluation will always be helpful (the line in question making a position strong or weak might be effectively unplayable/impossible to find by a human), but it’s useful for studying nevertheless.
I'm starting to think that a ChatGPT moment for robotics would require abandoning the current brute force approach to artificial intelligence. ChatGPT's trick was simply more data and compute. A stochastic parrot will eventually become very impressive. But we don't have an equivalent of billions of lines of code for robotics.
It's because existing models are a brute-force approach to intelligence. With enough data and compute, a stochastic parrot will become very impressive.
But with robotics, there's no pre-made dataset that can be parroted. Notice that these datasets, e.g. how to fold clothes, need to be created by humans. That's as if humans needed to write algorithms like quicksort to teach LLMs how to code.
In basic economic theory, high wages mean that there's insufficient supply. So I wonder why don't the "truly unemployed" people learn whatever the market rewards and compete with the highly paid workers.
If it is because they can't for whatever reason, 4 day working week doesn't solve anything.
(Genuine question, I'm not making some kind of a right-wing point.)
Because learning involves being effectively unemployed for multiple years, and is only available to those who did well in school. Then, on the other side, you're still not guaranteed a job. Add to all of that the fact that you'll probably have to move and effectively restart your life elsewhere.
My fiancée is currently in the middle of this. I don't know if she would've been able to go through it alone.
A homeless person usually isn't able to learn what is needed to become a neurosurgeon. So the issue isn't that we don't have enough highly paid jobs - it's that we don't have enough people able to do those jobs. Which makes sense, if everybody could easily become a neurosurgeon, it wouldn't be a highly paid job.
Solar + battery is very land inefficient, that's basically the main argument.
Edit: Per ChatGPT's calculation, nuclear is significantly cheaper than solar + battery in my country (Czech Republic) if we're talking about adding new reactors to existing power plants.
Land is cheap. Even in Europe, the cost of land onto which renewables are put is small compared to the cost of the renewable energy equipment itself. Here in the US, it's common for the land to be just a few percent of the project cost.
But batteries can be very distributed and stabilize and prop up the grid in ways a huge plant can't without building out distribution. (Situation dependent of course.)
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