[ej88]

seems to be a pattern:

[Company that's getting disrupted by AI: Fiverr, Duolingo]: rush to adopt internal AI to cut costs before they get undercut by competition

[Company that's orthogonal: Box, Ramp, HFT]: build internal tools to boost productivity, maintain 'ai-first' image to keep talent

[Company whose business model is AI]: time to go all in

[entropyneur]

Reading this thread suggests being "AI-first" is hardly a talent magnet.

[ej88]

ai-first via mandate: throes of a company trying to appear cutting edge

ai-first via the actual technology being built: talent magnet despite the HN bubble appearing otherwise

[gowld]

Why wouldn't HFT be disrupted by AI? AI-enhanced trading algo designs are likely to be competitive? AI disrupts everything on the computer from the low-end on up. The higher end requires more expensive or custom models that aren't as easy to obtain yet.

[lossolo]

Because HFT is about adversarial play with a lot of hidden information.

Relevant article from two days ago https://www.latent.space/p/adversarial-reasoning

[_se]

HFT is about the last technical domain that could possibly be touched by LLMs. There is next to no good training data and there is zero margin for error.

[yencabulator]

I could see analyzing news getting easier with LLMs. They have a history of using NLP there for sentiment analysis.

[ej88]

i mean llms

happy to be corrected but im not aware of any direct improvements llms bring to ultra low latency market making, time to first token is just too high (not including coding agents)

from talking to some friends in the space theres some meaningful improvements in tooling especially in discretionary trading that operate on longer time horizons where agents can actually help w research and sentiment analysis