{调取该文章的TAG关键词}|Deep Learning Set to Drive Computer Industry in Next 20 Years: Alphabet Chair
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Google parent Alphabet chair John Hennessy
By Huixia Sun
BEIJING, December 10 (TMTPOST) -- John Hennessy, the chair of Google parent Alphabet Inc., has asserted that dramatic breakthroughs in deep learning and machine learning are the new driver for the computer industry in the next two decades.
“We’ve come to an interesting time in the computer industry… will have a whole new driver and that driver is created by the dramatic breakthroughs that we’ve seen in deep learning and machine learning. I think this is going to make for really interesting next 20 years,” Hennessy, a former president of Stanford University, told the online audience during the 2021 T-EDGE Conference held in Beijing.
In a keynote speech delivered at the international event jointly organized by TMTPost Group, Daxing Industry Promotion Center and China New Media Development Zone, Hennessy, a veteran of the computer industry, shared his insights into past developments and future trends of the industry as well as likely solutions to pressing challenges right now.
In a simple language, he capsulated the history of the computer industry by pinpointing two major turning points, the former of which was the advent of personal computers and microprocessors.
From the 1960s to the 1980s, computer companies were largely vertically integrated ones, he said, citing IBM as an example. They did “everything”, including chips, discs, applications and databases.
Following the introduction of personal computers, a vertically organized industry was transformed into a horizontally organized industry. “We had silicon manufacturers. Intel, AMD, Fairchild and Motorola were doing processors. We had a company like TSMC, making chips for others… and Microsoft then came along and did OS and compilers on top of that. And companies like Oracle came along and built their applications, databases and other applications on top of that,” he went on to talk about the changes that took place in the late 1980s and the 1990s.
Now with dramatic breakthroughs in deep learning and machine learning, “we're at a real turning point at this point in the history of computing,” he declared.
He explained that with the breakthroughs in deep learning and machine learning, general-purpose processors are going to remain important but they will be less centric. With the fastest, most important applications, the domain-specific processor will begin to play a key role. “So rather than perhaps so much horizontal, we will see again a more vertical integration in the computing industry. We are optimizing in a different way from we had in the past,” he said.
He used a security camera as an example to explain the combination of domain-specific software and optimized hardware in a domain-specific architecture. In a specific field, lots of very specialized processors will be used for addressing one particular problem. The processor in a security camera is going to have a very limited use. The key is to optimize power and efficiency in that key use and costs. “Thus a different kind of integration is emerging now and Microsoft, Google and Apple are all focusing on this,” he said.
He also took the Apple M1 as an example to illustrate the new trend. “If you look at the Apple M1, it's a processor designed by Apple with a deep understanding of the applications that are likely to run on that processor. So they have a special purpose graphics processor; they have a special-purpose machine learning domain accelerator on there; and then they have multiple cores. But even the cores are not completely homogeneous. Some are slow low-power cores, and some are high-speed high-performance higher-power cores. So we see a completely different design approach, with a lot more co-design and vertical integration,” he said.
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