"Two former Google DeepMind researchers who worked on the company's Nobel Prize-winning AlphaFold protein structure prediction AI as well as its AlphaEvolve code generation system have launched a new company, with the mission of democratizing access to advanced algorithms. The company, which is called Hiverge, emerged from stealth today with $5 million in seed funding, led by Flying Fish Ventures with participation from Ahren Innovation Capital and Alpha Intelligence Capital."
"The company has built a platform it calls "Hive" that uses AI to generate and test novel algorithms to run vital business processes-everything from product recommendations to delivery routing- automatically optimizing them. While large companies that can afford to employ their own data science and machine learning teams do sometimes develop bespoke algorithms, this capability has been out of the reach of most medium and small businesses."
"The Hive system also promises the potential to discover unusual algorithms that may produce superior results that human data scientists might never be able to develop through intuition or trial-and-error, Alhussein Fawzi, the company's cofounder and CEO told Fortune. "The idea behind Hiverge is really to empower those companies with the best, best-in-class algorithms," he said. "You can apply [the Hive] to machine learning algorithms, and then you can apply it to planning algorithms," Fawzi explained."
Hiverge, founded by two former Google DeepMind researchers, emerged from stealth with $5 million in seed funding led by Flying Fish Ventures and participation from Ahren Innovation Capital and Alpha Intelligence Capital, with Jeff Dean as an investor. The company developed Hive, a platform that uses AI to generate and test novel algorithms to run and optimize business processes such as product recommendations and delivery routing. Hive aims to provide bespoke algorithmic solutions to small and medium businesses that lack in-house data science teams. The system can discover unconventional algorithms that may outperform human-designed approaches and applies to both machine learning and planning algorithms.
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