So frustrating.
"We hope VideoPrism paves the way for future breakthroughs at the intersection of AI and video analysis, helping to realize the potential of ViFMs across domains such as scientific discovery, education, and healthcare."
... for those of us internal to Google Research, and possibly large corporate clients when we choose.
Custom internal dataset, no model weights, no API access, just "FYI, this works pretty well when you have our data."
I do appreciate publishing of successful architectures, genuinely, and VP looks like it has some nice ideas, and it is very useful to know that training such a thing is probably not a dead end, so for all that, thanks.
At the end of the day, with large competitors committed to open models/weights, I think momentum is on the side of needing to push out open weights at least, but my guess is GOOG will be the last to transition to this of the big tech cos. I could understand it as a business decision if they were quickly opening this stuff up on their cloud, and competing that way, but they still seem to be in this world where the DeepMind crew continues to push out novel and interesting research projects, and the cloud crew struggles to deliver a competitive LLM at the same time.
I wonder where they'll be in a year. I'd like to hope up to competitive standards so that we've got an additional player, but progress seems slow to me right now.
"We hope VideoPrism paves the way for future breakthroughs at the intersection of AI and video analysis, helping to realize the potential of ViFMs across domains such as scientific discovery, education, and healthcare."
... for those of us internal to Google Research, and possibly large corporate clients when we choose.
Custom internal dataset, no model weights, no API access, just "FYI, this works pretty well when you have our data."
I do appreciate publishing of successful architectures, genuinely, and VP looks like it has some nice ideas, and it is very useful to know that training such a thing is probably not a dead end, so for all that, thanks.
At the end of the day, with large competitors committed to open models/weights, I think momentum is on the side of needing to push out open weights at least, but my guess is GOOG will be the last to transition to this of the big tech cos. I could understand it as a business decision if they were quickly opening this stuff up on their cloud, and competing that way, but they still seem to be in this world where the DeepMind crew continues to push out novel and interesting research projects, and the cloud crew struggles to deliver a competitive LLM at the same time.
I wonder where they'll be in a year. I'd like to hope up to competitive standards so that we've got an additional player, but progress seems slow to me right now.