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AI Weekly: $102 million and machine learning’s theory of general relativity

Author: Blaise Zerega / Source: VentureBeat

What’s $102 million among friends? That was the question last week as Element.ai raised this hefty sum in a Series A funding. Investors included Microsoft, Nvidia, and Intel Capital, all of whom have their own AI ambitions.

Element aims to make AI easy for businesses to use by connecting them with machine learning experts.

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And while Element may have brought together competitors Microsoft and Intel, the rivals have been fiercely staking their own claims with a flurry of investments and acquisitions.

While these moves point to AI one day becoming ubiquitous for business tasks, Google’s release of an academic paper called “One Model to Learn Them All” shows another route for machine learning to become commonplace. The paper describes a single machine learning template — dubbed the MultiModel — that can perform multiple tasks exceptionally well. As Blair Hanley Frank writes, “Google doesn’t claim to have a master algorithm that can learn everything at once,” but implicit in this statement is the ambition of eventually discovering one or more such algorithms, the AI equivalent of a theory of general relativity.

For AI coverage, send news tips to Blair Hanley Frank and Khari Johnson, and guest post submissions to John Brandon — and be sure to bookmark our AI Channel.

Thanks for reading,
Blaise Zerega
Editor in Chief

P.S. Please enjoy this video of Recode’s Walt Mossberg interviewing Amazon CEO Jeff Bezos about the “gigantic” potential of AI.

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