Databricks共同創業者が権威あるACM賞を受賞、「AGIは既に到来している」と発言
Databricks共同創業者のMatei Zaharia氏がACMの最高賞を受賞した。現在は研究用AIの開発に取り組んでおり、「AGIは単に誤解されている」と主張している。
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Databricks共同創業者が権威あるACM賞を受賞、「AGIは単に誤解されているだけ」と語る
Matei Zaharia氏は、米国計算機学会(ACM)から最高の栄誉を受賞した。現在、研究用AIの開発に取り組んでおり、人工汎用知能(AGI)は単に誤解されているだけだと述べている。
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Databricks co-founder and CTO Matei Zaharia almost missed the email telling him that he was the 2026 recipient of the ACM Prize in Computing. “Yeah, it was a surprise,” he told TechCrunch.
Back in 2009, the tech Zaharia developed for his PhD at UC Berkeley, under the tutelage of famed professor Ion Stoica, was launched into Databricks.
Zaharia had created a way to dramatically speed the results of slow, clunky, big data projects and released it as an open source project called Spark. Big data was in those days what AI is today and Spark turned the tech industry on its ear. The 28-year-old Zaharia became a tech celeb.
Since then, he has helmed the engineering at Databricks, growing it into a cloud storage giant and now a data foundation for AI and agents. Along the way the company has raised over $20 billion — valuing it at $134 billion — and hit $5.4 billion in revenue run rate. The Silicon Valley dream.
On Wednesday, the Association for Computing Machinery issued him the award for his collective contributions. The award comes with a $250,000 cash prize that he is donating to an as-yet-to-be-determined charity.
Zaharia, who in addition to his CTO duties is also an associate professor at UC Berkeley, is looking forward, not back. Like everyone else in the Valley, the future he sees is filled with AI.
“AGI is here already. It’s just not in a form that we appreciate,” he told TechCrunch. “I think the bigger point of it is: We should stop trying to apply human standards to these AI models.”
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A person, for instance, can only pass the bar exam to be a lawyer if they’ve integrated vast amounts of knowledge. But an AI can ingest vast amounts of facts easily. If it answers knowledge questions correctly, that doesn’t equate to general knowledge.
This tendency to treat AI like a human can have some profoundly negative impacts. He offers the example of the popular AI agent OpenClaw.
“On the one hand, it’s awesome. You can do so many things with it. It just does them automatically,” he said. But it’s also “a security nightmare” because it’s designed to mimic a human assistant that you trust with things like passwords. That leads to the risk of being hacked, or the agent spending unauthorized money from your bank because your browser is logged in.
“Yeah, it’s not a little human there,” he says.
As a professor and product engineer, Zaharia is most excited about how AI can help automate research on everything from biology experiments to data compilation.
Just like how vibe coding made prototyping and programming accessible to anyone, he thinks that accurate, no-hallucinations AI-powered research will someday become universal.
“Not that many people need to build applications, but lots of people need to understand information,” he said. Eventually we’ll make AI work better for us by having it lean into its strengths: telling us what every rattle in our car means, or scanning beyond text and images to include radio and microwaves, or, what he’s seeing students do now, simulate molecular-level changes and predict their effectiveness.
“The thing that I’m most excited about is what I’d call AI for search, but specifically for research or engineering,” he said.
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