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As demand for large-scale AI deployment skyrockets, the lesser-known, private chip startup Positron is positioning itself as a direct challenger to market leader Nvidia by offering dedicated, energy-efficient, memory-optimized inference chips aimed at relieving the industry’s mounting cost, power, and availability bottlenecks.
“A key differentiator is our ability to run frontier AI models with better efficiency—achieving 2x to 5x performance per watt and dollar compared to Nvidia,” said Thomas Sohmers, Positron co-founder and CTO, in a recent video call interview with VentureBeat.
Obviously, that’s good news for big AI model providers, but Positron’s leadership contends it is helpful for many more enterprises beyond, including those using AI models in their workflows, not as service offerings to customers.
“We build chips that can be deployed in hundreds of existing data centers because they don’t require liquid cooling or extreme power densities,” pointed out Mitesh Agrawal, Positron’s CEO and the former chief operating officer of AI cloud inference provider Lambda, also in the same video call interview with VentureBeat.
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Venture capitalists and early users seem to agree.
Positron yesterday announced an oversubscribed $51.6 million Series A funding round led by Valor Equity Partners, Atreides Management and DFJ Growth, with support from Flume Ventures, Resilience Reserve, 1517 Fund and Unless.
As for Positron’s early customer base, that includes both name-brand enterprises and companies operating in inference-heavy sectors. Confirmed deployments include the major security and cloud content networking provider Cloudflare, which uses Positron’s Atlas hardware in its globally distributed, power-constrained data centers, and Parasail, via its AI-native data infrastructure platform SnapServe.
Beyond these, Positron reports adoption across several key verticals where efficient inference is critical, such as networking, gaming, content moderation, content delivery networks (CDNs), and Token-as-a-Service providers.
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