Today we’re announcing $19.1M across our seed and Series A, with investment from @FactSet, @Zoom and @generalcatalyst. @FactSet led the Series A.
Learn more about what a financial intelligence team can make possible: https://t.co/BmXqlpghhD
Something big is about to begin at geniosAI.
We're entering an exciting next chapter, bringing financial intelligence closer to the decisions that move business forward.
More to come. Stay tuned.
@karpathy was waiting to read this one and finally did it today. the biggest question that i also wonder about is "Armed with LLMs, do generalists increasingly outperform specialists?"
imo i think it will definitely shrink the gap, and the effort to cover the gap will decrease.
[2/2] Agents aren’t completely separate from other systems, nor are they exactly the same. They sit in a unique sweet spot, blending the best of Machine Learning and Software Development.
Exciting times ahead!
Just wrapped up the live streams for @aiDotEngineer
conference and here’s what struck me:
[1/2] There’s no “one-size-fits-all” agent architecture coming our way. Agents will evolve just like any other system—and their evolution will drive overall system change.
Pragmatically, we can say that AGI is reached when it's no longer easy to come up with problems that regular people can solve (with no prior training) and that are infeasible for AI models. Right now it's still easy to come up with such problems, so we don't have AGI.