下面是小编为大家整理的2020年科技、媒体和电信预测（英文）,供大家参考。
Contents
Foreword 2 Bringing AI to the device: Edge AI chips come into their own 4 Robots on the move: Professional service robots 18 set for double-digit growth Private 5G networks: Enterprise untethered 30 High speed from low orbit: A broadband revolution 46 or a bunch of space junk? The smartphone multiplier: Toward a trillion-dollar economy 58 My antennae are tingling: Terrestrial TV’s surprising staying power 72 Coming to a CDN near you: Videos, games, and much, much more 86 Ad-supported video: Will the United States follow Asia’s lead? 94 The ears have it: The rise of audiobooks and podcasting 106 Cycling’s technological transformation: 118 Making bicycling faster, easier, and safer
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Foreword
TMT Predictions 2020: The canopy effect
ELOITTE’S 2020 TMT Predictions report contains three overarching themes. First, individual technologies are no longer siloed, but are becoming ever more connected and interdependent—and their impact and value are increasing as a result. Second, most of the TMT industry’s money is coming from smartphones, computers, TVs, enterprise data centers and software, and IoT (we call these the “Big Five”). And third, many ser- vices and products that have been “just around the corner” for years are fi nally turning that corner in 2020.
Think of a forest… In prior years of TMT Predictions, we have cross-referenced chapters a handful of times. This year, however, we have done so much more frequently. Consider that edge AI chips, private 5G, and robots are all intercon- nected, while ad-supported video and antenna TV are both affected by each other as well as by low-earth-orbit broadband satellites.
Why has this cross-linking ballooned in 2020?
Think of a forest. In its youth, saplings grow meters apart from each other. Bacteria, fungi, insects, and animals coexist in a single tree, but the same organisms might not be present in the tree next to it. Each sapling is, to an extent, an island with its own ecosystem. As the forest reaches maturity, while the trunks remain meters apart at ground level, 30 meters above the branches now all touch, creating a dense canopy that may be six meters thick. This single canopy, consisting of perhaps millions of trees, is now a unified ecosystem that may span thousands of kilometers.
A parallel phenomenon is underway in the TMT industry. Only 10 years ago, for instance, each kind of AI tech- nology was its own “sapling”: Innovations in natural language processing did not lead to better visual recognition, for example. Then, new deep machine learning hardware began to accelerate all AI innovations at the same time, creating a “canopy” in which advances in one area were almost always matched by advances in the other (former) AI silos. Nor does the phenomenon stop there. Until recently, deep learning has been performed using chips that cost thousands of dollars and used thousands of watts, and that were hence largely restricted to data centers. Within just the last two years, however, new edge AI chips that cost mere dollars and require only a few watts have made it possible to perform machine learning anywhere—further expanding the canopy, to stick with our meta- phor. Thanks to this development, even more data, algorithms, information, and solutions are flowing through all parts of the ecosystem, leading to ever faster and more useful AI for consumers and enterprises.
Big money and the Big Five Just fi ve ecosystems are responsible for the bulk of the TMT industry’s revenue. The smartphone ecosystem alone is worth well over a trillion dollars per year. The TV ecosystem is worth more than US$600 billion; PC sales and ancillaries (consumer and enterprise) generate yearly revenues of about US$400 billion, enterprise data centers and software (combined) will make about US$660 billion in 2020, and IoT (accelerated by the rollout of 5G) will be worth half a trillion dollars by 2021.
If we add up other newer devices—smart watches, consumer drones, e-readers, home 3D printers, AR glasses, VR glasses, and smart speakers—their combined ecosystems generate only a small fraction of the smallest of these Big Five.
The 10 chapters of this year’s report are largely about connecting the Big Five ecosystems, advertising on them, selling accessories for them, or providing content for them. Yes, some audiobooks and podcasts will be played on smart speakers, for example—but by the end of 2020, more than half of all audiobooks will be listened to on smartphones alone. For the foreseeable future, the big bucks will gravitate toward the Big Five, with everything else being relatively niche markets.
Better late than never As the old tech joke goes: “X is the technology of the future … and always will be!” But that isn’t always strictly true. In 2020, we foresee an entire crop of previously perennially delayed technologies finally
becoming ready for prime time. TMT Predictions’ poster child for such late-blooming technologies is the deployment of low earth orbit (LEO) satellites for low-latency broadband internet.
The first
LEO megaconstellation was envisioned in 1998; the first
(limited) commercial service may launch by the end of 2020, 22 years later. Other late bloomers, though not quite as delayed, are professional services robots, whose unit sales may exceed those of robot arms in 2020; bikes, particularly e-bikes, catching on in a big way for commuters around the world; and podcasts, which will have their first
billion-dollar year in 2020—16 years after the first
podcast was released.
This trio of trends may make predicting more predictable! An interconnected ecosystem with a limited number of significant players should allow us (and everyone) to foresee trends with greater accuracy and more confidence. Indeed, it may be time to retire the other old joke: “It’s tough to make predictions, especially about the future.”
In the near future, maybe it won’t be as tough.
Paul Sallomi
Global Technology, Media & Telecommunications industry leader
Paul
Lee Head of global TMT research
David Jarvis
Senior research manager US TMT Center Mark Casey
Global Telecommunications Media & Entertainment sector leader
Jeff Loucks Executive director, US TMT Center
Chris Arkenberg Research manager US TMT Center Craig Wigginton
Global Telecommunications leader
Duncan Stewart Canada TMT research director
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Bringing AI to the device
Edge AI chips come into their own
ANY PEOPLE MAY be familiar with the frustration of calling up their smartphone’s speech-to-text function to dictate an email, only to fi nd that it won’t work because the phone isn’t connected to the internet. Now, a new generation of edge arti fi cial intelligence (AI) chips is set to reduce those frustrations by bringing the AI to the device. 1
We predict that in 2020, more than 750 million edge AI chips—chips or parts of chips that perform or acceler- ate machine learning tasks on-device, rather than in a remote data center—will be sold. This number, repre- senting a cool US$2.6 billion in revenue, is more than twice the 300 million edge AI chips Deloitte
predicted would sell in 2017 2 —a three-year com- pound annual growth rate (CAGR) of 36 percent. Further, we predict that the edge AI chip market will continue to grow much more quickly than the overall chip market. By 2024, we expect sales of edge AI chips to exceed 1.5 billion, possibly by a great deal. 3
This represents annual unit sales growth of at least 20 percent, more than double the longer-term forecast of 9 percent CAGR for the overall semiconductor industry. 4
These edge AI chips will likely fi nd their way into an increasing number of consumer devices, such as high- end smartphones, tablets, smart speakers, and wearables. They will also be used in multiple enterprise markets: robots, cameras, sensors, and other IoT (internet of things) devices in general. Both markets are important. The consumer edge AI chip market is much larger than the enterprise market, but it is likely to
grow more slowly, with a CAGR of 18 percent expected between 2020 and 2024. The enterprise edge AI chip market, while much newer—the fi rst commercially available enterprise edge AI chip only launched in 2017 5 —is growing much faster, with a predicted CAGR of 50 percent over the same time frame.
By 2024, we expect sales of edge AI chips to exceed
1.5 billion, possibly by a great deal. This represents annual unit sales growth of at least 20 percent, more than double the longer- term forecast of 9 percent CAGR for the overall semiconductor industry.
HERE, THERE, AND EVERYWHERE: THE MANY LOCATIONS OF AI COMPUTING Until recently, AI computations have almost all been performed remotely in data centers, on enterprise core appliances, or on telecom edge processors—not locally on devices. This is because AI computations are extremely processor-intensive, requiring hundreds of (traditional) chips of varying types to execute. The hardware’s size, cost, and power drain made it essentially impossible to house AI computing arrays in anything smaller than a footlocker. Now, edge AI chips are changing all that. They are physically smaller, relatively inexpensive, use much less power, and generate much less heat, making it possible to integrate them into handheld devices such as smartphones as well as nonconsumer devices such as robots. By enabling these devices to perform processor-intensive AI computations locally, edge AI chips reduce or eliminate the need to send large amounts of data to a remote location—thereby delivering benefits in usability, speed, and data security and privacy. Of course, not all AI computations have to take place locally. For some applications, sending data to be processed by a remote AI array may be adequate or even preferred—for instance, when there is simply too much data for a device’s edge AI chip to handle. In fact, most of the time, AI will be done in a hybrid fashion: some portion on-device, and some in the cloud. The preferred mix in any given situation will vary depending on exactly what kind of AI processing needs to be done.
Figure 1 shows the various locations where AI computing can occ...
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