151–160 of 173 posts
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https://en.wikipedia.org/wiki/BonziBuddy My god. If we hit that bullseye, the rest of the dominoes will fall like a house of cards. Checkmate.
She's built like a clippy, but she handles like a HAL.
ChatGPT was announced November, 2022 - 8 months ago. Time flies. Question for HN: Where are we in the hype cycle on this? We can run shitty clones slowly on Raspberry Pi's and your phone. The educational implementations demonstrate the basics in under a thousand lines of brisk C. Great. At some point you have to wonder... well, so what? Not one killer app has emerged. I for one am eager to be all hip and open minded…
https://en.m.wikipedia.org/wiki/AI_winter
This concept of hype and decline has been happening for literally decades. Yet people don't realize it even when it's literally on the first google page for anything to do with AI.
The people spouting this AI nonsense seriously need to fuck off and read a book.
ChatGPT was announced November, 2022 - 8 months ago. Time flies. Question for HN: Where are we in the hype cycle on this? We can run shitty clones slowly on Raspberry Pi's and your phone. The educational implementations demonstrate the basics in under a thousand lines of brisk C. Great. At some point you have to wonder... well, so what? Not one killer app has emerged. I for one am eager to be all hip and open minded…
It's also super useful for things like "convert this fish shell snippet to bash" or "rewrite this Python class as a single function". It tends to really nail these sorts of grounded questions, and it legitimately saves me time.
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> Not one killer app has emerged. I'll say that I pretty firmly disagree with this. I've been using Github Copilot for about six months for my own work and it has fundamentally changed how I write code. Ignoring the ethics of Copilot, if I just need to read a file with some data, parse it, and render that data on screen, Copilot just _does_ most of that for me. I write a chunky comment explaining what I want, it writ…
My friend made a great comparison that seems to agree with your take: chatGPT for coding is like when ruby on rails came out. Or wordpress. felt magical and boosted (a certain kind of) productivity through the roof. We don't think of rails as the second coming though. same with code editors. of course a rails for all of code is cool. but iono, it's a code editor. i still use sublime.
ChatGPT was announced November, 2022 - 8 months ago. Time flies. Question for HN: Where are we in the hype cycle on this? We can run shitty clones slowly on Raspberry Pi's and your phone. The educational implementations demonstrate the basics in under a thousand lines of brisk C. Great. At some point you have to wonder... well, so what? Not one killer app has emerged. I for one am eager to be all hip and open minded…
A surprising amount of work can tolerate a percentage of errors in a non-deterministic way, even before considering that humans make even more errors that way usually. :-)
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My friend made a great comparison that seems to agree with your take: chatGPT for coding is like when ruby on rails came out. Or wordpress. felt magical and boosted (a certain kind of) productivity through the roof. We don't think of rails as the second coming though. same with code editors. of course a rails for all of code is cool. but iono, it's a code editor. i still use sublime.
How did WordPress boost productivity? Fussing with hosting, CMS, plug-ins is a mess. I just went back to good old hand written HTML with pico.css. Got my site down from 8mb to 100kb
How do you do science on LLMs? I would imagine that is super important, given their broad impact on the social fabric. But they're non-deterministic, very expensive to train, and subjective. I understand we have some benchmarks for roughly understanding a model's competence. But is there any work in the area of understanding, through repeatable experiments, why LLMs behave how they do? Do we care?
There's a field called Interpretability (sometimes "Mechanistic Interpretability") which researches how weights inside of a neural network function. From what I can tell, Anthropic has the largest team working on this [0]. OpenAI has a small team inside their SuperAlignment org working on this. Alphabet has at least one team on this (not sure if this is Deepmind or Deepmind-Google or just Google). There are a handful…
That’s a little depressing.
Great summary. I’ve been reading a pop neuroscience book called Incognito (2011). In it, the author talks about how the brain is a group of competing sub-brains of many forms, and the brain might have several ways of doing the same thing (e.g. recognizing an object). The author also posited that the lack of AI progress back then was due to the fact that there are no constantly competing sub-brains. Our brains are alw…
> Transformers can read the entire sequence at once and learn to “pay attention to” only the values that came earlier in time (via “masking”) Unless the text fits into the model’s context window, this is incorrect. The self-attention layers will train via a sliding window over the text. Learning to attend only to previous tokens is also not correct. There are a lot of ways to train a transformer. BERT is bidirectiona…
You had me at "Crypto VCs & ”builders” making a hard left into AI"