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Amnon Shashua, founder and CEO of Mobileye, has insight into complex problems that he believes can be solved using AI, and that AI itself can be reformed to become more reliable. On the sidelines of building and managing his self-driving car technology company – which he took over generalthen sold to Intel, then produced again – and was considering a number of other ideas.
Now, one of those things is raising money and gaining significant momentum.
One zeroA fintech company that aims to use artificial intelligence in retail banking is in the process of raising at least $100 million, TechCrunch has learned.
Although co-founded by one of Israel’s most famous and successful founders, One Zero has not yet received much attention outside of its home market. But the company has raised about $242 million so far, and in 2023 its value reached $320 million, according to data in Pitchbook. Our sources say the valuation will be much higher in the next round.
It’s not clear who the investors are, but previous backers of the company include Tencent, OurCrowd, and SBI Ventures (the now independent company that was once part of SoftBank).
One Zero’s momentum comes amid a hectic pace of activity for Shashua, who takes on a non-executive role at the company, with Gal Bar Dea as CEO. In the past two years, Shashua has founded or co-founded startups working in the field of humanoid robotics (trainee); Alternative approaches to large language models for generative AI (AI21); Which was launched just a few weeks ago, AA-I techniques (pronounced “double AI”), which Shashua described as his effort to build an “AI world.” He is also a professor of computer science at the Hebrew University of Jerusalem.
One Zero’s equally ambitious mission is to “bring private banking to the masses,” he said in an interview. It aims to democratize the kind of high-touch advisory services that high-net-worth individuals get when they bank, in a market where the average person not only gets this kind of service today, but also stares into a future where they may… There is no physical bank, no humans to help, at all.
It addresses this ambition with a dual focus on business. In Israel, where OneZero is based, the startup has obtained a banking license and is building a full-fledged retail bank. Additionally, One Zero uses insights gained from that retail business — which Shashua described in an interview as a “sandbox” — to train its models and hone its technology in order to license that technology to banks operating elsewhere.
Shashua told TechCrunch that the retail business now has about 110,000 customers, and while it has yet to announce any licensing deals yet, the company says it has received a number of inbound requests from major banks to do so.
The cornerstone of the company so far — and the focus of where it plans to invest its funding — is a chatbot called Ella, which aims to be better than existing chatbots while offering services that human bankers can’t.
As Shashua sees it, although there have been a number of efforts to build AI into retail banking, for example around functions like spending management, they are limited in what they can do.
“You don’t see banks deploying AI to the level where they actually replace the banker,” he said.
For example, take automated communications, he said. You can ask your banking chatbot very basic questions, such as “How much money is in my account?”, or information about recent transactions, and it can usually answer. But it’s a different story if you ask anything related to accounts, like “How much money will I have in my deposit account at the end of the year based on activity so far?”, or “What’s the best way for me to buy?” A car based on my financial profile?” Not only are chatbots unable to answer such questions, most personal bankers can’t either.
“There is an opportunity here, where generative AI, it seems, can do this,” he said. “It’s more than just tracking spending.”
One Zero’s approach to building such artificial intelligence, as described by Shashua, is very ambitious and feels as difficult as autonomous driving. It focuses on the use of multiple large language models. Some models may be optimized for different tasks, but running tasks through multiple MBAs can also provide a variety of responses, which are then run through a validation process to understand when answers are misleading or wrong, he said.
If those answers aren’t verified to be useful or correct, the AI isn’t trying to say anything anyway, he said. “It’s okay (to say) I can’t solve your problem,” he said. “I can’t answer your question.” Humans also can’t answer every question, right? So it’s okay. It’s not okay to say, here’s the answer to your question, and the answer is completely false, completely false.
The system starts with more basic tasks like spending management and the plan is to add more functionality over time to help advise customers on financing large purchases or saving money more wisely.
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