151–160 of 249 posts
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This is how you know it is different. Because the people that were not treating mongo, graphql, microservices, the block chain, and web 3 as miracles are impressed by llm. Just like people that are not tech saavy.
There's hype and then there's overhype . We are clearly in the overhype category for LLMs, but there's absolutely no doubt they are going to change things.
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> Every time, industry leaders are knocked off their perch. Is that really true? The two largest corporations in the world by market cap are Apple and Microsoft, both founded in the 1970s.
Also the wealth of the average worker has been stagnant since the 70's - computers, the internet, etc came and brought tons of wealth, and didn't raise the standard of living. I've never thought about computers that way - they got here, and didn't make everyone's lives better - they just accelerated wealth concentration in the top 1%.
Geez people. Please learn to identify hypes, but most importantly the causes of hypes. LLM is fundamentally information processing technology. Not the path to AGI, not an emerging sentience. The reason "this time" feels so amazing is that the unwashed masses suddenly got access to new information processing technology in a context where their tools been stagnant for decades . Not because it was not possible, but beca…
Absolutely no risk of terminator here, just ignorance masquerading as such.
Geez people. Please learn to identify hypes, but most importantly the causes of hypes. LLM is fundamentally information processing technology. Not the path to AGI, not an emerging sentience. The reason "this time" feels so amazing is that the unwashed masses suddenly got access to new information processing technology in a context where their tools been stagnant for decades . Not because it was not possible, but beca…
All the way back in the 1950s, big money went into it. Decades of hard work, mathematical models of human language, all manner of study, enormous bilingual corpuses of text with phonetic annotation, programmed in general-knowledge databases, fuzzy reasoning algorithms. The amount of work put into it is quite staggering, in hindsight. I remember the cutting edge in the 1990s - SYSTRAN for example, could with some significant human guidance and a limited context domain, translate technical material sometimes usefully.
All of that work has been rendered moot by deep learning. All of it. A machine can, simply with the correct deep learning algorithm and mass exposure to language plus a few bilingual texts, learn an algorithm for translation. It does so automatically, no verb conjugation algorithms, no general knowledge databases, no expert systems with fuzzy reasoning, no parsers, not like a specifically-designed old-school translator had.
And yet these deep-learning systems are vastly superior to the old school architectures, completely supplanting them a couple years after their development.
It is the same story in many other areas. Chess, Go? They learn to play chess and go better than any AI designed specifically to do so. Image classification? Better than the previous 60 years of work on machine vision, and again, accidentally falls out of it. Speech recognition? An algorithm to write a bad poem? Well, we now have an algorithm to find an algorithm to write you that bad poem, if you want it.
That's the thing. These are algorithms to solve very tricky problems, and we didn't have to discover, find, or otherwise create the algorithm. The machine did it for us. I am not sure I'm communicating it well, but to me that's probably the most significant advance since the computer. It was understood - theoretically - that this was possible for a long time; but personally at least, I assumed it would forever require more data and compute than could be realized.
Every few years a new technology goes mainstream and quickly changes the world around us rather fundamentally. I’ve lived through the web in 1995. Google in 2000. Web 2.0 in 2005. Smartphones in 2009. Now it’s generative AI in 2023. Every time, there’s an argument about whether it’s the end of the world or a total nothingburger. Every time, industry leaders are knocked off their perch. Every time, there are surprise…
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I'm constantly resisting the urge to write "MongoDB is webscale" whenever these threads show up. For the uninitiated: https://news.ycombinator.com/item?id=1636198 . The original video is gone but it lives on YouTube: https://m.youtube.com/watch?v=b2F-DItXtZs .
This is how you know it is different. Because the people that were not treating mongo, graphql, microservices, the block chain, and web 3 as miracles are impressed by llm. Just like people that are not tech saavy.
I do think there is a lot of overlap with people promoting self driving predictions that haven't panned out.
He (and most people on HN) are still underestimating the impact of this. Everything points at AI soon becoming far more intelligent than any human. That's not science fiction about the remote future in a hundred years. We are talking about something in the order of ten years. We are actually at the brink of the "technological singularity". It's happening. It's happening.
Nothing points to this I'm afraid. All we have with LLMs is a probabilistic word salad generator that is realistic enough to get people who should / should not know better very excited. It is better than Google search because it puts the results into a realistic sounding piece of text. It is worse than Google search because it does not provide sources or context. Both will steal the information you feed in. Exactly n…
> Exactly no progress has been made in understanding or creating real intelligence in any meaningful sense
Strong words…
The thing has understanding. It may be alien and imperfect, with strange failure modes and quirks. But it has significant understanding of the real world. At this point, there are countless compelling examples demonstrating this.
The only way the model could so effectively predict the next token of such an immense and diverse collection of texts is by acquiring some level of understanding of the circumstances that gave rise to those texts.
The more I use gpt-4, this clearer this is to me, despite its limitations.
Edit: Removed unnecessary snark.