immortal3

There's another angle to this comparison. Groq and Cerebras use custom chips, but I'm not sure about Together. In this case, Together is sharing results based on the B200 GPU. Another important point is the accuracy of these speed-ups compared to the baseline model. It's known that such tricks reduce accuracy, but by how much? Kimi has already benchmarked several providers. https://x.com/Kimi_Moonshot/status/1976926483319763130

Is it possible that US or any other government has participated in the round which might be the reason?

Honestly, it doesn't matter for the end user if there are more tokens generated between the AI reply and human message. This is like getting rid of AI wrappers for specific tasks. If the jump in accuracy is actual, then for all practical purposes, we have a sufficiently capable AI which has the potential to boost productivity at the largest scale in human history.

After the acquisition, I think Wiz would have to only focus on Google Cloud which might be a major limiting factor in the company's future. But other than that, It surprises me that, a $23B offer is rejected from the perspective of Employees. IPO won't provide the same level of liquidity opportunities.

I have used Octa and it's a decent platform, not a magical one. Creating a similar platform for Google Cloud should be feasible with the level of Google resources.

To add further, i do not know what is end goal of hugging face. 1. They have inference API but all cloud provider can implement those in next year. 2. They offer subscription but market-size of subscription is questionable. 3. I hope this new set of funding don't bring problem to them because making money with open source is hard and at this scale of funding it might be even harder. It see what happens in next set of years.

You can view ipython notebook easily with nbviewer. (sometime github rendering fails for large notebooks)

This year AOC 2021: https://nbviewer.org/github/norvig/pytudes/blob/main/ipynb/A...

I have been thinking about these a lot lately. There is lot more scope on improving current search results.

I believe simple two stage system might be enough to produce decent system. Stage - 1. query expansion and reverse index based retrieval Stage - 2. re-ranking based on few combination of heuristics. (page rank + word embedding + query analysis)

Would you like to talk more about this ? I have email address in my profile.