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About Silkon Labs

We're a team of researchers and engineers building the silicon foundation for AGI — one rigorous experiment at a time.

Mission

Artificial intelligence should be powerful, accessible, and grounded in rigorous science. At Silkon Labs, we build models that reason, explain, and scale — without shortcuts.

Values

Rigor first

Every claim is backed by measurement. We ship models that are reproducible and verifiable.

Open science

We publish benchmarks, training details, and model cards so the community can build on our work.

Scalable design

From 400M to 1T parameters, the same architecture principles apply. Consistency compounds.

Responsible development

Safety evaluations, red-teaming, and bias audits are part of every release pipeline.

Leadership

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Alex Chen

Chief Executive Officer

Former research lead at DeepMind. PhD in machine learning from MIT.

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Maya Patel

Chief Technology Officer

Built distributed training infrastructure at Meta AI. Stanford CS.

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Jonas Müller

Head of Research

15+ years in NLP and transformer architectures. Former Google Brain.

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Sarah Kim

Head of Engineering

Scaled inference platforms to 100M+ users. ex-Amazon AWS.

Timeline

2023

Silkon Labs founded with a focus on dense transformer efficiency.

2024

Silkon 7B released. Open-weight model adopted by 10K+ developers.

2025

Silkon 1T training completed. State-of-the-art on 6 major benchmarks.

2026

Expanded to 100+ languages. Enterprise API launched.

Join the team

We're hiring researchers, engineers, and operators who want to build the future of AI.