311–320 of 870 posts
Imagine taking career advice from people who will never need to be employed again in order to survive.
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> The "hitting a wall" / "plateau" people will continue to be loud and wrong. Just as they have been since 2018[0]. Everybody who bet against Moore's Law was wrong ... until they weren't. And AI is the reaction to Moore's Law having broken. Nobody gave one iota of damn about trying to make programming easier until the chips couldn't double in speed anymore.
This is exactly backwards: Dennard scaling stopped. Moore’s Law has continued and it’s what made training and running inference on these models practical at interactive timescales.
However, most people don't know the difference between the proper Moore's Law scaling (the cost of a transistor halves every 2 years) which is still continuing (sort of) and the colloquial version (the speed of a transistor doubles every 2 years) which got broken when Dennard scaling ran out. To them, Moore's Law just broke.
Nevertheless, you are reinforcing my point. Nobody gave a damn about improving the "programming" side of things until the hardware side stopped speeding up.
And rather than try to apply some human brainpower to fix the "programming" side, they threw a hideous number of those free (except for the electricity--but we don't mention that--LOL) transistors at the wall to create a broken, buggy, unpredictable machine simulacrum of a "programmer".
(Side note: And to be fair, it looks like even the strong form of Moore's Law is finally slowing down, too)
> The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. If current LLMs are ever deployed in systems harboring the big red button, they WILL most definitely somehow press that button.
US MIC are already planning on integrating fucking Grok into military systems. No comment.
> It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. Somewhere, there are GPUs/NPUs running hot. You send all the neces…
This quote stuck out to me as well, for a slightly different reason. The “tenacity” referenced here has been, in my opinion, the key ingredient in the secret sauce of a successful career in tech, at least in these past 20 years. Every industry job has its intricacies, but for every engineer who earned their pay with novel work on a new protocol, framework, or paradigm, there were 10 or more providing value by putting…
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The value extortion plan writes itself. How long before someone pitches the idea that the models explicitly almost keep solving your problem to get you to keep spending? Would you even know?
The free market proposition is that competition (especially with Chinese labs and grok) means that Anthropic is welcome to do that. They're even welcome to illegally collude with OpenAi such that ChatGPT is similarly gimped. But switching costs are pretty low. If it turns out I can one shot an issue with Qwen or Deepseek or Kimi thinking, Anthropic loses not just my monthly subscription, but everyone else's I show th…
Switching costs are currently low. Once you're committed to the workflow the providers will switch to prepaying for a year's worth of tokens.
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Aren't you still better off than the rest of us who found what they love + invested decades in it before it lost its value. Isn't it better to lose your love when you still have time to find a new one?
Depends on if their new love provides as much money as their old one, which is probably not likely. I'd rather have had those decades to stash and invest.
Writing code in many cases is faster to me than writing English (that is how PLs are designed, btw!) LLM/agentic is very “neat” but still a toy to the professional, I would say. I doubt reports like this one. For those of us building real world products with shelf-lives (Is Andrej representative of this archetype?), I just don’t see the value-add touted out there. I’d love to be proven wrong. But writing code (in code, not English), to me and many others, is still faster than reading/proving it.
I think there’s a combination of fetishizing and Stockholm syndroming going on in these enthusiastic self-reports. PMW.
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There is an old saying back home: an idiot never tires, only sweats. Claude isn't tenacious. It is an idiot that never stops digging because it lacks the meta cognition to ask 'hey, is there a better way to do this?'. Chain of thought's whole raison d'etre was so the model could get out of the local minima it pushed itself in. The issue is that after a year it still falls into slightly deeper local minima. This is fi…
> it lacks the meta cognition to ask 'hey, is there a better way to do this?'. Recently had an AI tell me this code (that it wrote) is a mess and suggested wiping it and starting from scratch with a more structure plan. That seems to hint at some meta cognition outlines
I think in less than a year writing code manually will be akin to doing arithmetic problems by hand. Sure you can still code manually, but it's going to be a lot faster to use an LLM (calculator).
People keep using these analogies but I think these are fundamentally different things. 1. hand arithmetic -> using a calculator 2. assembly -> using a high level language 3. writing code -> making an LLM write code Number 3 does not belong. Number 3 is a fundamentally different leap because it's not based on deterministic logic. You can't depend on an LLM like you can depend on a calculator or a compiler. LLMs are t…
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That's just sad. Right when I found love in what I do, my work has no value anymore.
Aren't you still better off than the rest of us who found what they love + invested decades in it before it lost its value. Isn't it better to lose your love when you still have time to find a new one?