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Ex-DeepMind researcher lands $55M seed at $300M valuation
Andrew Dai says Elorian raised a $55 million seed round at a $300 million valuation before launching a product, betting on visual AI.
Image: TechCrunch
Elorian raised a $55 million seed round at a $300 million valuation just months after founder and CEO Andrew Dai left Google DeepMind, according to a new episode of TechCrunch’s Build Mode podcast.
Dai, a former Google DeepMind researcher, told host Isabelle Johannessen that he sees visual AI as one of the next major frontiers in artificial intelligence. He said progress in the field has been far less consistent than in areas like math, physics, and coding.
“You have models that are doing really great at math, really great at new physics ideas, and of course coding is very popular now … But one area where progress has been extremely uneven is visual understanding and visual reasoning,” said Dai. “At Elorian, we want to build models that will advance us toward visual AGI.”
According to TechCrunch, Dai discussed how he turned a highly technical vision into a pitch investors could follow, and why he chose strategic backers such as Nvidia and Menlo Ventures over offers that came with even higher valuations. His view: investors who understand the realities of building frontier AI can matter more than pushing the price tag as high as possible.
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The episode also focused on practical fundraising and hiring lessons for AI founders, including:
- what top venture firms look for in frontier AI startups
- how to explain deeply technical products to nontechnical investors
- what to look for in venture capital partners
- how startups can recruit top AI researchers from Big Tech
- why speed has become a major competitive advantage in AI
- how founders can build durable moats as the technology changes
TechCrunch said this season of Build Mode is centered on fundraising, from large pre-seed rounds and major venture checks to bootstrapping, IPOs, and sudden market shifts. New episodes drop every Thursday.
AI Editor
Ava covers the rapidly evolving world of artificial intelligence, from foundational models and research labs to the real-world economics of intelligence. With a background in computational linguistics, she cuts through the hype to find out what actually works. She firmly believes that benchmarks are just marketing until reproduced in the wild.
via TechCrunch
