Intel announced late last week that it has formed a new AI group to consolidate a number of its programs and acquisitions. It’s headed by Naveen Rao, the former head of Intel acquisition Nervana. This means Intel is making sure is has a major seat at the table as artificial intelligence and machine learning branch out to touch virtually everything — from autonomous driving to IoT to enhancing corporate systems — over the next 5-7 years.
In the short term, the group will focus on research related to its software and hardware (Nervana, Xeon/Lakecrest chips and subsequent families) to deliver AI for drones and autonomous vehicles, smart cities, health care, personal appliances, etc. But I expect a longer-term play. Intel will be putting together a complete set of products to bring to traditional manufacturers in its chip business across the full breadth of edge computing to big data center platforms for things like Xeon Phi based AI solutions that power financial models, biological research/modeling, and scientific research. For example, plans for Intel’s Mobileye and Nervana acquisitions will fall under this group’s charter. Mobileye is known as an enabler of vision for cars and drones, but its vision based models, together with AI and ML could prove highly valuable in fields like security, visual analysis of health-related issues, and real-time forecasting.
Additional technologies like Saffron (with its AI-as-a-Service model), which Intel acquired in 2015, have already started to give the Intel visibility into customer needs, enabling it to learn about future requirements and experiment on solutions. Nervana gives Intel the ability to experiment with optimized architectures in addition to Xeon Phi massively parallel processing systems that will power next generation AI systems. And Intel’s close alliance with the research and open source communities gives it the ability to learn as well as influence future directions in AI/ML. But the company will also deploy customized solutions through its consulting services and will eventually offer these as off-the-shelf enterprise cognitive computing toolsets for verticals like financial modeling, genetic research, transportation best routing, etc. The ultimate target: compete head to head with IBM Watson in particular and other up and coming solutions in general.