921–930 of 1000 posts
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Sure we just need next level super computers for these large models and the patience of multiple days to wait for output
Increasing the token limit without needing more resources to run the network is a solvable problem
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"The AI will absorb your words, and some small part of you will gain immortality. In some small but very real way, you'll live forever, some part of you ensconced safely for all eternity in a handful of vectors deep inside a pile of inscrutable matrices." That sounds like a sort-of-religion of the future, actually.
I did have chatGPT create a new religion for me. I have to admit, it was quite compelling.
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> Where does Google gets its information now? The feeder pipeline has died. The bar has raised now. People will ask the questions on SO whose answers they couldn't find from anywhere else including AI.
Correction: the AI will ask the questions it couldn't find a high enough confidence answer to. We are all now working for the AI to find niche scraps of knowledge that haven't been indexed.
we will all become servants to the giant AI, feeding it more and more levels of detail and obscurity
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I wonder how long till they open it up to your private data stored in Google? Eg. User: What should I be doing today? AI: You have a court appearance at 9am. Prioritize that, because failing to appear might result in an arrest warrant. Next, prioritize your mums birthday - all the other family will be there, and with your mums cancer results last week, this might be the last. If you travel between them by bus, then y…
Fun exercise for the reader: how much of this is actually possible with LLMs and how much is not.
Specifically, LLM's can generally only take into account ~8000 words of context when deciding on a response. Summarizing the question and all necessary information for the answer into 8000 words is hard when the user might have millions of words in their inbox.
Having said that, I don't think it's far off. There are already prototypes of LLM's which have information retrieval abilities (ie. it could do a keyword search of your inbox to find a few relevant documents to read to decide on a response). There are also promising efforts to make that 8000 word number far larger.
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Google already has a trackrecord of beating Microsoft. Do you remember Windows Phone? Well Google made Android in response to Windows Phone + Bing threat not in response to iPhone.
Windows Phone launched in late 2010, long after Android. Do you mean Windows CE / Windows Mobile? But if so, those weren't really a serious threat to anyone.
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Google already shows snippets from SO and has done so for years, without AI. Why would this be any different?
The difference is that the snippet points to the source. If you are like me, when I see the snippet and find it relevant I immediately go to the source, since I get access to the full context and others' comments. With a technology like chatGPT, that link is cut.
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This is the opposite of true in my experience: if you run a content-heavy site, Wikipedia is going to be one of your top traffic sources — especially for time on site since the visitors who arrive tend to have a very low bounce rate.
Look at my profile, I own content-heavy sites and have for many years. I can show you logs - Wikipedia does virtually nothing. And the content of my sites has been regurgitated by Wikipedia thousands of times.
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I don’t understand this scenario. If someone already posted the answer then asking the question again on SO has no value. If the LLM can automate giving answers then we don’t need SO as much as before.
> If the LLM can automate giving answers then we don’t need SO as much as before. This is probably the misunderstanding: the LLM can only automate giving answers because it has been trained on all of SO (or other similar communities). It's a summary of SO, not an alternative to it. When new problems arise, the LLM will need to be re-trained to include the new SO answers, it will not be able to synthesize new knowledg…
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+1 For a group of people on a site frequented by startup people, did nobody read the terms of MS's investment into OpenAI? "Microsoft would reportedly put down $10 billion for a 75% share of the profits that OpenAI earns until the money on the investment is paid back. Then when Microsoft breaks even on the $10 billion investment, they would get a 49% stake in OpenAI. These are not the terms you would take if, tomorro…
Not having read the terms in any detail, I will say this: it can be very easy to not report profits for a very long time.
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The point was not that the profits are long tailed but rather if openai thought there were massive future profits and the potential to become a google killer then they wouldn’t give away half of their company today for $10B.
But how do you know that they didn't predict that it is only by having a $10 billion that they _can_ become the next google killer, because of the initial cost outlay, and the inevitable fight back from google (which would then require a warchest, of which i'm sure this 10 billion is a part of)?
If somebody needs ten billion dollars in additional work and investment to make that a reality, how certain can they be?
OpenAI has 375 employees (according to Google). At 300,000 a head thats 110M per year in compensation. Let's say that their compute costs are enormous and go to 200M in expenses per year. 10B is fifty years of expenses. So if they need 10B in investment it becomes obvious that they believe that they have to change something about their business in a fundamental way. Maybe that is going to be enough, but if it is so certain it becomes hard to believe that they'd need this kind of investment.