Jonathan Siddharth

@Jonsid

Founder and CEO, Turing. Accelerating superintelligence to drive real economic progress.

Palo Alto, CA

turing.com

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Jonathan Siddharth
@Jonsid
Sep 9
Can an AI agent run part of a company? We built an entire company to test it. Cirrus Sleep, Inc. is a fully simulated firm: one complete fiscal year, 1,100+ files across 9 systems, a year of internal Slack. Conflicting numbers, governance constraints, ambiguity by design. No
Turing
@turingcom
Sep 8
Today, Turing is announcing CEO Bench, a new evaluation of whether frontier AI agents can complete the complex, long-horizon financial and operational work that companies depend on.
Article
CEO Bench: Can AI agents handle real company work?
Today, Turing is announcing CEO Bench, a new evaluation of whether frontier AI agents can complete the complex, long-horizon financial and operational work that companies depend on. Most benchmarks...
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Jonathan Siddharth
@Jonsid
23h
Congrats @ecekamar 👏
Turing
@turingcom
Sep 15
Proud to see our CTO, @ecekamar named one of the Top Women in AI 100 for 2026. Ece’s leadership continues to shape what responsible, human-centered AI can become. We’re proud to see her recognized among the women building the future of AI. Congrats, Ece!
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Jonathan Siddharth
@Jonsid
Sep 13
To get to ASI we likely need auto-meta-research, not just auto-research. Auto-research hill climbs within the current recipe. Minimize pretraining loss, maximize post-training evals. Auto-meta-research defines new objectives. An outer loop that searches across paradigms.
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Jonathan Siddharth
@Jonsid
Sep 12
Lesson from the DeepSeek-V4.1 technical report: "...the marginal return of engineering the data and environment pipeline substantially exceeds that of algorithmic novelty in post-training." My 2 cents. The interesting part isn't data > algorithms. It's that the distinction is
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Jonathan Siddharth
@Jonsid
Sep 11
Data as a lever is becoming increasingly important for advancing the models.
Jasper Lu
@lu__jasper
Sep 10
This is notable. DeepSeek, a lab usually first to pioneer novel algorithms and architectures, is saying that at this point, the ROI of improving data quality far exceeds that of working on novel post-training algorithms. I think this has already been true for some time for