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The physical and computing foundations that make AI possible, from chip design and hyperscale cloud to data center power, cooling, and connectivity. Experts here help clients understand what it takes to build and scale AI at the infrastructure level.
The models, architectures, and engineering work behind modern AI systems, including large language models, agentic systems, and AI product development. Experts here help clients separate real technical capability from hype.
The competitive, financial, and go-to-market forces shaping the AI industry, from frontier labs to enterprise vendors and investors. Experts here help clients read the market and make sharper strategic and investment decisions.
The financial mechanics of running AI at scale, including compute and infrastructure spend, model performance versus cost trade-offs, and budgeting for AI initiatives. Experts here help clients make sharper build, buy, and spend decisions as AI costs scale with use.
How organizations measure and capture the return on their AI investments, from cost savings and productivity gains to new revenue creation. Experts here help clients move past pilot-stage excitement to prove and defend measurable business impact.
Since September, full time; before that, part time. Self-Attention Ventures backs enterprise GenAI: development, alignment, evaluation, compliance, and agent infrastructure that moves ARR, investing pre-seed/seed.
Building FailureModes.ai to help enterprises assess, recover, operationalize, and continuously improve agentic AI systems, leading AI engineering across data center agent architecture.
Directed a cross-functional engineering and research team embedded inside OpenAI, serving as Microsoft's lead for the strategic MS-OpenAI integration.
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