"Intel Corp. is reworking its artificial-intelligence strategy as it tries to gain ground on Nvidia Corp., the leader in the market for chips designed to excel at AI computations.
Over the past year, under new chief executive Pat Gelsinger, Intel has added staff and introduced new AI software for its expanding lineup of chips to improve AI-driven chatbots, facial recognition and movie recommendations, among other applications.
Intel is known mainly for its dominance in the market for central processing units, the brains behind personal computers and the servers that run corporate networks and the internet. But it has lost some of its sheen for investors over the past decade as Nvidia gobbled up the market for chips specifically designed for AI purposes, especially chips that train AI models.
Nvidia now accounts for about 80% of revenue from AI-specific computation in big data centers, according to Informa PLC's Omdia unit, a British research and consulting firm, although that doesn't account for any AI calculations done on Intel's general-purpose CPUs. That dominance in AI-specific chips helped Nvidia surpass Intel as the most valuable chip company in the U.S. by market capitalization two years ago.
AI chips are a relatively small but rapidly growing segment of the overall chip market. Rising demand for faster, more efficient AI computation has spawned dozens of chip startups, while the leading chip makers have invested heavily. The AI chip market was worth around $8 billion in 2020, but is expected to grow to nearly $200 billion by 2030, according to a report from Allied Market Research, based in Portland, Ore.
Intel's strategy is to build a stable of chips and open-source software that covers a broad range of computing needs as AI becomes more prevalent. For instance, it could sell customers a package that would allow them to hand off some tasks to specialist chips that excel at things like image recognition, while handling other work on general-purpose chips.
Intel hopes the efficiency of that kind of division of labor could help companies optimize performance for their specific AI tasks and save money by cutting power consumption. That could make sense for customers that have a lot of data and do a lot of AI processing -- big corporations and well-funded startups -- although Intel also hopes to capture demand for AI computation through sales to the large cloud-computing providers and even products for individual consumers.
One important change Intel has made in pursuit of that strategy is the addition of graphics processing units to its product line. Unveiled more than two years ago, those chips could help it stack up better against Nvidia, which specializes in GPUs initially developed for computer gaming but adapted for machine-learning tasks. Intel in 2019 bought Israeli startup Habana Labs, which makes chips designed specifically for training AI models -- systems that spit out realistic-sounding sentences, for example -- and for generating output from those models.
Another change is in the way Intel knits together its AI products for customers.
"It isn't even a question of do we have to invest more -- we invest quite a bit in AI," says Sandra Rivera, a longtime Intel executive whom Mr. Gelsinger tapped to head the data-center business and AI strategy last summer. "But we haven't gotten the leverage of those investments when we have different strategies and different execution priorities" for various products.
Since taking her new role, Ms. Rivera has brought in several new executives, including Kavitha Prasad, who came from a machine-learning startup she co-founded after an earlier stint at Intel. Ms. Prasad, who directly oversees the AI strategy, is leading a shift in focus she says is centered on using AI to reach customers' business goals, rather than offering a menu of chips and letting customers figure out the rest.
"Intel has all these technologies, but what is bringing it together to make it cohesive from a customer perspective, so that the customers are able to deploy it at a much faster rate, so that they're able to get to their business outcomes faster?" she says. "It is not about having the solutions, but it's about meaningfully bringing them together to make it happen."
Bringing it all together is largely the job of Intel's software architects, led by Chief Technology Officer Greg Lavender, whom Mr. Gelsinger hired from VMware Inc., where Mr. Gelsinger was previously CEO.
Success, of course, isn't a sure thing. Nvidia, already far ahead of Intel and the rest of the competition, is moving quickly with its own chips, announcing a new generation of superfast processors in March. While analysts say Intel's strategy could help make it a more formidable competitor to Nvidia, its ability to tap the AI market hinges on delivering AI-targeted chips and related software on schedule. Recent history suggests that could be a challenge. Intel has stumbled in chip-manufacturing technology in recent years, leaving it behind South Korea's Samsung Electronics Co. and Taiwan Semiconductor Manufacturing Co. in the high-stakes race to make chips with the smallest transistors and best performance. Some of its latest CPU chips for servers have been delayed.
Mr. Gelsinger aims to reverse that trajectory by rededicating the company to manufacturing -- he's announced tens of billions of spending on new chip factories over the next several years -- and building up a business making chips on contract according to others' designs. Whether the company can execute on Mr. Gelsinger's plan to retake the technological lead from its Asian competitors in the next few years is an open question.
"There are a lot of things they haven't executed on over the last five or six years," says Matt Bryson, an analyst at Wedbush Securities. "Clearly under Pat Gelsinger Intel is investing more in product development, and if you put more money into development, you should have a better ability to execute, but it comes back to how do you know until you are showing products and starting to see traction?"
Ms. Rivera says Intel is ready to make that leap. "We have the customer relationships, we have the market position, we have the unique differentiation -- we just need to execute our strategy," she says." [1]
1. Artificial Intelligence (A Special Report) --- Inside Intel's AI-Chip Strategy: The company has lagged behind Nvidia in the fast-growing segment. It's determined to reverse that.
Fitch, Asa.
Wall Street Journal, Eastern edition; New York, N.Y. [New York, N.Y]. 11 Apr 2022: R.6.
Komentarų nėra:
Rašyti komentarą