Intel Has Now Invested $1bn In AI Startups

Having largely missed the boat on mobile, Intel’s commitment to developing the platforms that will support artificial intelligence (AI) has been significant.

Its focus has been on creating the chips and infrastructure that will support AI applications, including autonomous vehicles. Earlier this year, Intel splashed out £12.3 billion on driverless car specialist Mobileye, while it also forked out £19 million for Nervana Systems in 2016.

Both acquisitions are now significant parts of Intel’s AI portfolio and the company says it wants to offer as much choice as possible to customers through investments and partnerships with businesses, governments and researchers.

Intel AI

Indeed, CEO Brian Krzanich says it has now invested $1 billion in AI startups, including Might AI, Data Robot and Lumiata through its capital investment fund.

“At Intel, we have an optimistic and pragmatic view of artificial intelligence’s  (AI) impact on society, jobs and daily life that will mimic other profound transformations – from the industrial to the PC revolutions,” he said.

“Our belief is that AI will bring significant new opportunities to transform business – from retail to healthcare to manufacturing – and have an immensely positive impact on society.

“AI will make the impossible possible: advancing research on cancer, Parkinson’s disease and brain disorders; helping to find missing children; and furthering scientific efforts in climate change, space exploration and oceanic research.”

Among Intel’s recent AI innovations is the Movidius Neural Compute Stick, a USB-based kit which runs AI algorithms trained on a central system with massive data sets for use on the edge of networks.

And Intel’s equipment has been used by partners like Microsoft, whose Project Brainwave was demonstrated using Intel’s new 14 nm Stratix 10 FPGA.

“I believe Intel will be the AI platform of choice, offering unmatched reliability, performance, security and integration,” added Krzanich. “We are 100 percent committed to creating the roadmap of optimized products to support emerging mainstream AI workloads.

“AI is still in its infancy, and as this space evolves, we’ll continue to advance disruptive approaches in compute that support the complex workloads of today and tomorrow.”

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