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RantyDave 58 minutes ago [-]
Right. But ... this would limit you to either extremely small models or extremely large FPGA's, yes? If there's a simple machine learning task that requires a sub microsecond latency I can see the point but otherwise??
ag2718 42 minutes ago [-]
Yes, this work is focused on accelerating very small models, typically for real-time systems that require extremely low power or low latency.
I'm not in HFT, but I assume this is also an interesting applicable domain?
ag2718 28 minutes ago [-]
Yes, definitely: this type of work is applicable in domains where software run on general-purpose processors cannot meet latency or power requirements.
jansan 9 minutes ago [-]
Financial trading or real time control systems could be an application.
Animats 49 minutes ago [-]
This guy will be hired by a high-frequency trading firm, and the next time we hear about him, he will have a net worth in 9 figures.
One primary application of this work is in high-energy physics (https://home.cern/smarter-decisions-at-the-speed-of-collisio...). Ultrafast and real-time learning is also very applicable for problems in quantum computing, plasma control, etc. (https://arxiv.org/pdf/2602.02005).
p.s. Thanks for posting this and welcome to HN!