111–120 of 283 posts
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Mostly because the marginal cost of microwaves was not close to zero.
Mostly because they were not making claims that sentient microwaves that would cook your food for you were just around the corner which then the most respected media outlets parroted uncritically.
YC doesn't care whether it "makes sense" to use an LLM to design chips. They're as technically incompetent as any other VC, and their only interest is to pump out dogshit startups in the hopes it gets acquired. Gary Tan doesn't care about "making better chips": he cares about finding a sucker to buy out a shitty, hype-based company for a few billion. An old school investment bank would be perfect. YC is technically i…
Second, want to give any examples of "shitty, hype-based compan[ies]" (I assume you mean companies with no real revenue traction) getting bought out for "a few billion".
Third, investment banks facilitate sales of assets, they don't buy them themselves.
Maybe sit out the conversation if you don't even know the basics of how VC, startups, or banking work?
Earlier quoted context omitted.
Mostly because they were not making claims that sentient microwaves that would cook your food for you were just around the corner which then the most respected media outlets parroted uncritically.
I mean, they were at one point making pretty extravagant claims about microwaves, but to a less credulous audience. Trouble with LLMs is that they look like magic if you don’t look too hard, particularly to laypeople. It’s far easier to buy into a narrative that they actually _are_ magic, or will become so.
- LLMs are extremely competent at surface-level pattern matching and manipulation of the type we'd previously assumed that only AGI would be able to do.
- A large fraction of tasks (and by extension jobs) that we used to, and largely still do, consider to be "knowledge work", i.e. requiring a high level of skill and intelligence, are in fact surface-level pattern matching and manipulation.
Reconciling these facts raises some uncomfortable implications, and calling LLMs "actually intelligent" lets us avoid these.
They want to throw LLMs at everything even if it does not make sense. Same is true for all the AI agent craze: https://medium.com/thoughts-on-machine-learning/langchains-s...
That is one spicy article, it got a few laughs out of me. I must agree 100% that Langchain is an abomination, both their APIs as well as their marketing.
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If feels like the entire world has gone crazy. Even the serious idea that the article thinks could work is throwing the unreliable LLMs at verification ! If there's any place you can use something that doesn't work most of the time, I guess it's there.
This happens all the time. Once it was spices. Then poppies. Modern art. The .com craze. Those blockchain ape images. Blockchain. Now LLM. All of these had a bit of true value and a whole load of bullshit. Eventually the bullshit disappears and the core remains, and the world goes nuts about the next thing.
I don’t mind LLMs in the ideation and learning phases, which aren’t reproducible anyway. But I still find it hard to believe engineers of all people are eager to put a slow, expensive, non-deterministic black box right at the core of extremely complex systems that need to be reliable, inspectable, understandable…
You mean, like humans have been for many decades now. Edit: I believe that LLM's are eminently useful to replace experts (of all people) 90% of the time.
Experts capable of critical thinking and reflecting on evidence that contradicts their world model (and thereby retraining it on the fly)? Most likely not, at least not in their current architecture with all its limitations.
They want to throw LLMs at everything even if it does not make sense. Same is true for all the AI agent craze: https://medium.com/thoughts-on-machine-learning/langchains-s...
please dont post a link that is behind a paywall !!
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https://archive.is/dLp6t It is a registration wall I think.
Same result. Information locks are verboten.
I don't know anything about chip design, but like any area in tech I'm certain there are cumbersome and largely repetitive tasks that can't easily be done by algorithms but can be done with human oversight by LLMs. There's efficiency to be gained here if the designer and operator of the LLM system know what they're doing.
I know nothing about chip design. But saying "Applying AI to field X won't work, because X is complex, and LLMs currently have subhuman performance at this" always sounds dubious. VCs are not investing in the current LLM-based systems to improve X, they're investing in a future where LLM based systems will be 100x more performant. Writing is complex, LLMs once had subhuman performance, and yet. Digital art. Music (se…