Meta question: what's with all of the naming overlap in the AI world? Triton (Nvidia, OpenAI) and Gro{k,q} (X.ai, groq, OpenAI) all come to mind
"PS: The name Triton was coined in mid-2019 when I released my PhD paper on the subject. I chose not to rename the project when the "TensorRT Inference Server" was rebranded as "Triton Inference Server" a year later since it's the only thing that ties my helpful PhD advisors to the project."
I think you have to prefix the query with "@Meta AI", hope this helps
Now with LLMs it is what human evaluators feel about the LLM output?
Would have loved to try it when they released it, but I'm apparently in the wrong country. I think it's not available outside the US (?). OpenAI and DeepSeek have no such issues. It's a bummer really, I'm happy paying for this but they don't want me to.
We found in our experience it is pretty hard to force LLM to do something in proper depth, and OAI's deep research definitely feels like one of the first examples from big labs on how this can be done. What we typically see is that it is not even the "agent" part that is hard to do, but how to force model to not "forget" to go deep...
They seem to be ok with outsourcing any and all creativity to a language model, so it’s not surprising that they can’t come up with unique names themselves.