China Targets $150 Billion Artificial Intelligence Ecosystem by 2030

Governmental policies designed to foster a particular industry are not unusual in East Asia or elsewhere, so it is not too surprising that artificial intelligence (AI) now is the target for China, as the State Council has set a goal of becoming a “global innovation center” for AI  by 2030.

The value of artificial intelligence industries should surpass 1 trillion yuan ($147.80 billion) by that point, the State Council says. That is an ambitious goal, given some current projections of total market size by 2024, if only AI software and systems are counted.

But the State Council forecast clearly includes the value of all economic output driven by AI, not just the value of AI itself. That is akin to valuing the impact of e-commerce by adding up the retail value of all products and goods moved through that channel. You can get big numbers pretty quickly.

https://www.techemergence.com/valuing-the-artificial-intelligence-market-graphs-and-predictions/

By 2020, almost every new software product and service will incorporate artificial intelligence features, Gartner predicts.

Though it remains unclear how much business impact might eventually be derived, some early adopters already find AI contributes.

Amazon uses robotics to automate “picking and packing” activities in its warehouses, McKinsey notes. The “click to ship” cycle time, which ranged from 60 to 75 minutes with humans, fell to 15 minutes after applying robotics, while inventory capacity increased by 50 percent. Operating costs fell an estimated 20 percent, McKinsey argues.

Netflix uses AI to personalize recommendations. Netflix found that customers, on average, give up 90 seconds after searching for a movie. By improving search results, Netflix projects that they have avoided canceled subscriptions that would reduce its revenue by $1 billion annually.

Baidu and Google spent between $20 billion to $30 billion on AI in 2016, McKinsey says.

Healthcare, financial services, and professional services are seeing the greatest increase in their profit margins as a result of AI adoption, McKinsey argues.

The McKinsey Global Institute Study on Artificial Intelligence, The Next Digital Frontier also estimates that total annual external investment in AI at between $8 billion to $12 billion in 2016, with machine learning attracting nearly 60 percent of that investment.

Robotics and speech recognition are two of the most popular investment areas.

source: McKinsey

An Industry You Might Not Recognize is Coming

A world and an industry you might not recognize is coming.

New Censtorship Threats to Internet

Though the relationship is not entirely linear or always obvious, commercial freedom is related to political freedom.

Consider network neutrality. The original thinking by the U.S. Federal Communications Commission was that internet freedom (commercial freedom of app and content providers) required “no blocking” of all lawful content.

Ironically, some might argue, later extensions of network neutrality actually work to suppress the commercial freedom of some entities to promote the “freedom” of others (app providers “win,” access providers “lose”)

Now court decisions are highlighting another problem: actual blocking of content that might be lawful in one country, because it is unlawful in another (or potentially in another country).

The Google v. Equustek Solutions case in Canada started out as a “simple” trademark case, in which Equustek claimed that another company was infringing on its trademarks online.

But a Canadian court ruled that Google (not a direct party in the case) had to block entire sites worldwide, even if some content is, in fact, not unlawful in Canada.

In 2015, an appeals court upheld that decision, and earlier today the Canadian Supreme Court agreed with both lower courts.

Now a similar issue is arising in the European Union, where a French court has aid Google has to  censor content links globally, to follow French law.

The larger point is that threats to content or app freedom can come from multiple sources. Some seem to worry most about potential danger from commercial sources (zero rating, toll-free service, quality of service mechanisms).

But the biggest danger will always be action by governments, either in the form of governments outlawing whole apps and types of content, or governments outlawing apps or content in one country because some other government has done so.

By 2020, Most Software Products will Use Artificial Intelligence

By 2020, almost every new software product and service will incorporate artificial intelligence features, Gartner predicts.

Though it remains unclear how much business impact might eventually be derived, some early adopters already find AI contributes.

Amazon uses robotics to automate “picking and packing” activities in its warehouses, McKinsey notes. The “click to ship” cycle time, which ranged from 60 to 75 minutes with humans, fell to 15 minutes after applying robotics, while inventory capacity increased by 50 percent. Operating costs fell an estimated 20 percent, McKinsey argues.

Netflix uses AI to personalize recommendations. Netflix found that customers, on average, give up 90 seconds after searching for a movie. By improving search results, Netflix projects that they have avoided canceled subscriptions that would reduce its revenue by $1 billion annually.

Baidu and Google spent between $20 billion to $30 billion on AI in 2016, McKinsey says.

Healthcare, financial services, and professional services are seeing the greatest increase in their profit margins as a result of AI adoption, McKinsey argues.

The McKinsey Global Institute Study on Artificial Intelligence, The Next Digital Frontier also estimates that total annual external investment in AI at between $8 billion to $12 billion in 2016, with machine learning attracting nearly 60 percent of that investment.

Robotics and speech recognition are two of the most popular investment areas.

source: McKinsey

source: McKinsey

An Industry You Will Not Recognize, Within a Decade

You might not recognize the telecom industry within a decade.

The industry is likely to earn less revenue than at present. The only issue is how much less will be earned. So the industry will contract.

There might be 85 percent fewer telecom companies in business. There might be only five global carriers. Revenue growth might not be lead by new subscribers or even any of the access services (voice, messaging, data).

Services sold to humans might not drive revenue growth, either. And where growth has been driven by consumers, growth might in the next phase be driven by enterprises.

The changes will come fast.

No matter how you look at it, “eras” in the telecom industry are coming faster, and ending just as fast.

Consider voice: the era of traditional voice lasted more than a century. The “VoIP” era arguably lasted 25 years. The era we now are in will not even be characterized by “voice.”

Going forward, the internet, mobility and over-the-top apps are the ways to understand where we are. But even that will change.

The recent decade has been dominated by mobile revenues--subscription growth in developing markets and mobile internet access in developed markets. In the 5G era, the industry should not even be lead by mobile data.

The reason is simple: in the digital era, about every decade, the growth drivers have changed. In the 2G era, subscriber growth was the driver. In the 3G era, messaging, email access and mobile web drove incremental growth.

In the 4G era, mobile web and apps, internet access and video consumption have been key. In the 5G era, it is expected that services for non-human internet of things apps will drive incremental revenue growth.

Another way to characterize industry history is to note that fixed networks once represented the whole industry. Today, fixed line revenue and subscribers are fractions of mobile revenue and subscribers.

Industry structure also has passed through eras, from monopoly to mobile duopoly to competition. Many analysts now predict an era of vast consolidation will follow, within the next decade. How vast?

How about a reduction of global service providers from 800 to about 100, over the next seven years? That is what Bell Labs now predicts.

All those fast-coming, momentous developments are why the Pacific Telecommunications Council has created a new “Industry Transformation Boot Camp” from its existing Spectrum Futures and PTC Academy programs.

The week-long boot camp will provide industry professionals with a concentrated look at what changes are coming, why they are coming, what key business challenges exist and what strategic options firms face.

source: e-strategyblog

source: Karel

source: Quartz

Edge Computing a Mobile Operator Opportunity?

Many telcos have argued that owning data center assets would be a good way to complement connectivity services. Some have found the synergies less than truly compelling. The issue now is whether mobile edge computing will be different.

AT&T hopes so, thinking that its existing real estate portfolio (central offices, macro towers and small cells will provide locations for edge computing.

So AT&T will outfit those facilities with high-end graphics processing chips and other general purpose computers, to create new edge computing facilities.

AT&T believes it could someday embed these systems in everyday items like traffic lights and other infrastructure as well.

The point is that edge computing could provide a way for telcos to leverage existing assets to create new roles in the computing fabric and ecosystem that some might argue have eluded them in the centralized computing era.

Will Most IoT Connections Use Fixed Network Access (Wi-Fi and other)?

In the past, long-range, low-power networks have had leading share of market (55 percent) for machine-to-machine applications, with short-range solutions such as Wi-Fi having perhaps 35 percent share, with mobile networks having about 10-percent share.

How that might change as internet of things use cases proliferate is one issue. Maravedis, for example, believes that mobile platforms ultimately will have the largest share. Others believe low power wide area networks will do better than that, connecting perhaps 16 percent of IoT devices, while mobile networks connect some seven percent of devices.

That suggests most IoT devices will use other methods, such as Wi-Fi. That matters, in part, because it means most IoT connections might not increase the amount of revenue earned by access providers in a direct way.

source: Maravedis

source: Analysys Mason  

Short-range connection technologies will continue to represent the overwhelming percentage of internet of things connections through 2022, Ericsson predicts.

source: Ericsson