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I do think that the AI space can easily be taken by a player ready to invest heavily in the space. Just imagine what training data could look like using gpt4 a

I do think that the AI space can easily be taken by a player ready to invest heavily in the space. Just imagine what training data could look like using gpt4 and how you can become a 10X Data Scientist because of it. That is exactly what a lot of startup AI's actually do right now. Also think that with the current state of kubernetes there is NOTHING in the way of rolling out massive datacenters of "Ai Trainers" just to throw stuff against the wall and see what sticks. IMHO Microsoft invested so OpenAI stays on azure and that marketing has already more than paid off, because they would love you to train all your models on their cloud. But truth be told, there are still many gpus left. And Nvidias recent mega gpu shows that there is still room for domination

SilverBirch 4y ago
I really don't understand why you think this, every large tech company is piling billions into AI projects now they've seen what ChatGPT can do, OpenAI is absolutely killing it, dozens of engineers from Google's AI teams have left over the last few years to do start ups and there's literally dozens of start ups in the AI space getting funded. Not to mention all the incumbents who are now jealously guarding their training data, there's no free lunch on training sets. This is probably the most difficult industry to compete in right now, not the easiest.
- jhoelzel 4y ago
  There are papers on it from people more knowledgeable than me but what it comes down to in ML is always the dataset. A machine that is already ready to generate datasets for you improves the quality many times. That means with every Version of ChatGPT, the datasets for other companies grow richer. My personal take is that it takes many AI's in combination with a kubernetes like control loop to reach AGI not a single big one. Take for instance programming. Given enough iteration and therefore money AutoGPT can reach "somewhat usable" code and just like in regular development the whole deal comes down to testing of what you desire. Therefore if you can find a way to "test" your dataset you can iterate automatically and that's easier for some task and more difficult for other but still possible. The common thought is that an AI model needs to "know it all" but as they thought me in business psychology, that's actually not even true for humans themselves. Furthermore, i have mentioned the new "cards" from NVIDIA who are even more powerful than what we had before So yeah i think the space is still wide open.

SilverBirch 4y ago

I really don't understand why you think this, every large tech company is piling billions into AI projects now they've seen what ChatGPT can do, OpenAI is absolutely killing it, dozens of engineers from Google's AI teams have left over the last few years to do start ups and there's literally dozens of start ups in the AI space getting funded. Not to mention all the incumbents who are now jealously guarding their training data, there's no free lunch on training sets. This is probably the most difficult industry to compete in right now, not the easiest.

jhoelzel 4y ago
There are papers on it from people more knowledgeable than me but what it comes down to in ML is always the dataset. A machine that is already ready to generate datasets for you improves the quality many times. That means with every Version of ChatGPT, the datasets for other companies grow richer. My personal take is that it takes many AI's in combination with a kubernetes like control loop to reach AGI not a single big one. Take for instance programming. Given enough iteration and therefore money AutoGPT can reach "somewhat usable" code and just like in regular development the whole deal comes down to testing of what you desire. Therefore if you can find a way to "test" your dataset you can iterate automatically and that's easier for some task and more difficult for other but still possible. The common thought is that an AI model needs to "know it all" but as they thought me in business psychology, that's actually not even true for humans themselves. Furthermore, i have mentioned the new "cards" from NVIDIA who are even more powerful than what we had before So yeah i think the space is still wide open.