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Earlier quoted context omitted.
To me, the vast majority of "consumers" as in B2C only care about price, specifically free. Pro and enterprise customers may be more focused on the capabilities you listed, but the B2C crowd is vastly in the free tier only space when it comes to GenAI.
You may be forgetting that ChatGPT has 10M paying customers. Not to mention everyone that pays for Claude Pro, Perplexity Pro, and so on.
According to who?
the hype will never die. all the smartest people in industry and government believe that there is a very high probability that this technology is near the edge of starting the AGI landslide. you dont need AGI to start the AGI landslide, you just need AI tools that are smart enough to automate the process of discovering and building the first AGI models. every conceivable heuristic indicates that we are near the edge.…
Earlier quoted context omitted.
> when VCs were funding all kinds of ride share, bike share, food delivery, cannabis delivery, and burning money so everyone gets subsidized stuff while the market figures out wtf is going on I’m reminded of slime molds solving mazes [1]. In essence, VC allows entrepreneurs to explore the solution space aggressively. Once solutions are found, resources are trimmed. [1] https://www.mbl.edu/news/how-can-slime-mold-solv…
VC is the worst possible way to fund entrepeneurs. Except for all the others.
Plenty of entrepreneurship is low to moderate risk, bootstrappable and/or unscalable. That describes where VC is a raw deal. It also does not describe AI.
the hype will never die. all the smartest people in industry and government believe that there is a very high probability that this technology is near the edge of starting the AGI landslide. you dont need AGI to start the AGI landslide, you just need AI tools that are smart enough to automate the process of discovering and building the first AGI models. every conceivable heuristic indicates that we are near the edge.…
The recent advances are truly jaw dropping. It absolutely merits being investigated to the hilt. There is a very good chance that it will end up being a net profit.
But intuitively they don't feel to me like they're getting more human. If anything I feel like the recent round of "get it to reason aloud" is the opposite of what makes "general intelligence" a thing. The vast majority of human behavior isn't reasoned, aloud or otherwise.
It'll be super cool if I'm wrong and we're just one algorithm or extra data set or scale factor of CPUs away from It, whatever It turns out to be. My intuition here isn't worth much. But I wouldn't be surprised if it was right despite that.
the hype will never die. all the smartest people in industry and government believe that there is a very high probability that this technology is near the edge of starting the AGI landslide. you dont need AGI to start the AGI landslide, you just need AI tools that are smart enough to automate the process of discovering and building the first AGI models. every conceivable heuristic indicates that we are near the edge.…
Earlier quoted context omitted.
You may be forgetting that ChatGPT has 10M paying customers. Not to mention everyone that pays for Claude Pro, Perplexity Pro, and so on.
> OpenAI has 10M paying customers According to who?
https://www.theinformation.com/articles/openai-coo-says-chat...
Earlier quoted context omitted.
To me, the vast majority of "consumers" as in B2C only care about price, specifically free. Pro and enterprise customers may be more focused on the capabilities you listed, but the B2C crowd is vastly in the free tier only space when it comes to GenAI.
You may be forgetting that ChatGPT has 10M paying customers. Not to mention everyone that pays for Claude Pro, Perplexity Pro, and so on.
Earlier quoted context omitted.
You may be forgetting that ChatGPT has 10M paying customers. Not to mention everyone that pays for Claude Pro, Perplexity Pro, and so on.
> OpenAI has 10M paying customers According to who?
[1] https://www.bloomberg.com/news/articles/2024-09-05/openai-hi...
The idea that you need huge amounts of compute to innovate in a world of model merging and activation engineering shows a failure of imagination, not a failure to have the necessary resources.
PyReft, Golden Gate Claude (Steering/Control Vectors), Orthogonalization/Abliteration, and the hundreds of thousands of Lora and other adapters available on websites like civit.ai is proof that the author doesn't know what they're talking about re: point #2.
And I'm not even talking about the massive software/hardware improvements we are seeing for training/inference performance. I don't even need that, I just need evidence that we can massively improve off the shelf models with almost no compute resources, which I have.