Intel Corp has agreed to purchase the Israeli artificial intelligence (AI) startup firm Habana Labs for $2 billion. The news was announced on Monday by Intel, and the purchase will take the company further into the AI industry.
Habana Labs was founded in 2015 in Israel, and it focuses on AI chips. They have raised a total of $75 million, and one of those investors was Intel Capital.
“This acquisition advances our AI strategy, which is to provide customers with solutions to fit every performance need–from the intelligent edge to the data center,” Navin Shenoy, Intel’s executive vice president and general manager of the Data Platforms Group, said in the news release. “More specifically, Habana turbo-charges our AI offerings for the data center with a high-performance training processor family and a standards-based programming environment to address evolving AI workloads.”
Intel predicts that the AI chip market will be greater than $25 billion by the year 2024. Not only will the market price get larger, but the actual technology will continue to be extremely important in the economy and society. Because of this, any big company like Intel is jumping in. Their AI-driven revenues have risen 20% from 2018, and they are now more than $3.5 billion.
Intel’s growing interest in this area is also a result of PC sales stagnating, and the company now relies heavily on sales to data centers.
Intel was involved in various other AI-related acquisitions in the past few years. They picked up Movidius, Nervana, Altera and Mobileye.
While much of the focus in the AI industry is on software, chips are arguably just as important. Intel and other companies know this, and that is why there have been recent developments in chip innovation.
Mike Leone is a senior analyst at ESG.
“Satisfying AI workload requirements is a growing challenge for many organizations,” he said. “Traditional compute is simply unable to keep up with the orders of magnitude improvements organizations are looking for in their respective compute infrastructure. And it’s a losing proposition to just keep throwing more and more processing power at the problem. It’s too expensive. It’s too big of a footprint. And it’s too power hungry. We’re seeing an increase in the need for specialized compute to address the different workloads in the AI space, mainly training and inference. Training addresses the algorithm creation process, by feeding a model data so it can learn. Inference refers to the stage where the trained model gets leveraged to make predictions based on new incoming data. Of the two, training is far more resource intensive. And while GPUs, for example, can address both types of workloads, the emergence of specialized compute based on the AI workload—that is, training vs. inference—has emerged and amassed a surprising number of startups looking to add their IP and approach into the mix.”
Mukesh Khare, the vice president of IBM’s AI Hardware Research Center, also believes in the importance of AI chips.
“Today, AI applications are being executed on systems designed for other, non-AI purposes. The rapid escalation in AI deployments is straining the capabilities of these systems, and expected overall improvements in general-purpose computing systems cannot keep up with this escalation in demand. For example, the compute needed for AI training is doubling every 3.5 months. To address this AI compute demand growth and opportunity, heterogeneous systems and AI accelerator chips, designed specifically and from scratch for AI, are required.”
With the acquisition, Habana will become a major player in this space. The acquisition also follows a pattern of increasing consolidation in the AI chip market. This will jump-start major competition in developing these computing chips in order to help with AI technology.