711–720 of 851 posts
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There are two perspectives on this. What you said is definitely a good one if you're a business planning to add AI to whatever you're selling. But personally, as a user, I want the opposite to happen - I want AI to be the product that takes all the current products and turns them into tools it can use.
I agree, I want a more intelligent voice assistant similar to Siri as a product, and all my apps to be add-ons the voice assistant could integrate with.
As an Ex-OpenAI employee I agree with this. Most of the top ML talent at OpenAI already have left to either do their own thing or join other startups. A few are still there but I doubt if they'll be around in a year. The main successful product from OpenAI is the ChatGPT app, but there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free an…
> there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free and ads would become the main option to make money out of chatbots. So... I don't think this is certain. A surprising number of people pay for the ChatGPT app and/or competitors. It's be a >$10bn business already. Could maybe be a >$100bn business long term. Meanwhile... making mo…
It's funny how the vibe of HN along with real world 's political spectrum have shifted together.
We can now discuss Ads on HN while still being number 1 and number 2 post. Extremism still exists, but it is retreating.
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To be fair to thunderbird120, the author of this piece made edits at some point. See https://archive.is/K4n9E . No discussion of the recent TPU releases, or TPUs for all, for that matter.
You are correct. I misjudged.I thought I had read the article early, it must have been just after the edits.
Several people have suggested that LLMs might end up ad-supported. I'll point out that "ad supported" might be incredibly subtle/insidious when applied to LLMs: An LLM-based "adsense" could: 1. Maintain a list of sponsors looking to buy ads 2. Maintain a profile of users/ad targets 3. Monitor all inputs/outputs 4. Insert "recommendations" (ads) smoothly/imperceptibly in the course of normal conversation No one would…
You ask two different corporate LLMs and compare answers.
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TPUs (short for Tensor Processing Units) are Google’s custom AI accelerator hardware which are completely separate from GPUs. I remember that introduced them in 2015ish but I imagine that they’re really starting to pay off with Gemini. https://en.wikipedia.org/wiki/Tensor_Processing_Unit
Believe it or not, I'm also familiar with Wikipedia. It reads that they're optimized for low precisio high thruput. To me this sounds like a GPU with a specific optimization.
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> there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free and ads would become the main option to make money out of chatbots. So... I don't think this is certain. A surprising number of people pay for the ChatGPT app and/or competitors. It's be a >$10bn business already. Could maybe be a >$100bn business long term. Meanwhile... making mo…
> No guarantees that Google discover a meaningful business model here... I don't understand this sentiment at all. The business model writes itself (so to speak). This is the company that perfected the art of serving up micro-targeted ads to people at the moment they are seeking a solution to a problem. Just swap the search box for a chat bot. For a while they'll keep the ads off to the side, but over time the ads wi…
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I don’t understand why this is happening. Why is everyone buying into this hype so strongly? It’s a bit like how DEI was the big thing for a couple years, and now everyone is abandoning it. Do corporate leaders just constantly chase hype?
Yes corporate leaders do chase hype and they also believe in magic. I think companies implement DEI initiatives for different reasons than hype though. Many are now abandoning DEI ostensibly out of fear due to the change in U.S. regime.
I personally know an engineering manager who would scoff at MLK Day, but in 2020 starting screaming about how it wasn’t enough and we needed Juneteenth too.
AI isn’t hype at Nvidia, and DEI isn’t hype at Patagonia.
But tech industry-wide, they’re both hype.
As an Ex-OpenAI employee I agree with this. Most of the top ML talent at OpenAI already have left to either do their own thing or join other startups. A few are still there but I doubt if they'll be around in a year. The main successful product from OpenAI is the ChatGPT app, but there's a limit on how much you can charge people for subscription fees. I think soon people expect this service to be provided for free an…
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And yet google's main structural disadvantage is being google. Modern BERT with the extended context has solved natural language web search. I mean it as no exaggeration that _everything_ google does for search is now obsolete. The only reason why google search isn't dead yet is that it takes a while to index all web paged into a vector database. And yet it wasn't google that released the architecture update, it was…
This would be like claiming in 2010 that because Page Rank is out there, search is a solved problem and there’s no secret sauce, and the following decade proved that false.
Today a consumer grade >8b decoder only model does a better job of predicting if some (long) string of text matches a user query than any bespoke algorithm would.
The only reason why encoder only models are better than decoder only models is that you can cache the results against the corpus ahead of time.
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And yet google's main structural disadvantage is being google. Modern BERT with the extended context has solved natural language web search. I mean it as no exaggeration that _everything_ google does for search is now obsolete. The only reason why google search isn't dead yet is that it takes a while to index all web paged into a vector database. And yet it wasn't google that released the architecture update, it was…
> Modern BERT with the extended context has solved natural language web search. I doubt this. Embedding models are no panacea even with a lot simpler retrieval tasks like RAG.
Unlike the natural language queries that RAG has to deal with, Google searches are (usually) atomic ideas and encoder-only models have a much easier time with them.