Highlights of AT&T CFO and CTO remarks at Morgan Stanley Investor Conference

Network quality driven by significant investments in 5G and fiber:

AT&T believes that its recent and anticipated network investments will bolster its network foundation to compete as the need for high-quality connectivity only continues to increase.  At a Morgan Stanley European Investor Conference, AT&T CFO John Stephens indicated that AT&T’s integrated fiber strategy is expected to improve the company’s connectivity offering for both consumer and enterprise markets and enhance its 5G network quality in a cost-efficient manner.

COVID-19 Impact:

AT&T CTO Andre Fuetsch said:  “Obviously what happened was everyone basically started working, started schooling from home, and all of a sudden we had to readjust our lives to work from home, learn from home, and all of a sudden we had to adapt very quickly to that.  Within our homes, we had to have these different personas that we normally don’t do — whether it’s doing your day job, performing that duty, helping your children get online so they can do their schooling, and then all the other things in life. That was a blurring, in a way, of these sort of enterprise and consumer segments coming together.”

“All of this technology is great, but at the end of it, we are humans and anything we can do to help facilitate [and] build better, stronger human connections” will benefit society at large, Fuetsch added. “This year we’re really getting pushed and challenged to do that. I really think this type of technology is just going to make things better.”

Artificial Intelligence (AI) Improves Operations:

Some of these technologies, like Artificial Intelligence (AI), are already helping AT&T improve its operations, especially among its field technicians, he said, noting that AT&T’s entire routing and scheduling program relies heavily on AI.

“Any given day we have 35,000 network technicians driving around in trucks installing, and repairing, and maintaining our network. It’s essentially a very complex logistics algorithm and, as you can imagine with a company of our scale, just a single percentage improvement in efficiencies can lead to big, big dollars,” Fuetsch said.

AT&T is also trialing the use of drones with computer vision analytics to help improve inspections of its roughly 70,000 cell sites. When those drones take flight, they are scanning towers, looking for excessive heat dissipation, corrosion, loose cables, and bird nests, among other signs that indicate a required repair.

“All of this is getting fed back into a neural network, which is basically AI based,” and that program identifies the repair checklist, the technician and skill sets required, and the parts needed to remedy the problem, Fuetsch said.

AT&T’s experiences here and elsewhere gives him confidence that “the camera is still and will be the killer app” for the foreseeable future. However, the use of cameras is undergoing dramatic changes, he said.

“We carry about 400 petabytes a day across our network. About 50% of that traffic we carry is video traffic. Most of that is going out in a sort of downstream way. The future is going to be about upstream,” Fuetsch said.

Use of Video Cameras:

Fuetsch envisions new applications that “can help better manage our lives through a simple video camera” with the aid of video analytics and sensing. These advancements are occurring not just despite the scourge of COVID-19, but rather because of it in some ways as well, he said.

“This pandemic has really created some new norms here. I think the good news for operators is connectivity is so important and so relevant for everything we do. As we go into 2021, certainly with hopefully a light at the end of the tunnel here in terms of the pandemic with the latest news we’re hearing about vaccines, I’m actually very optimistic.”

“As we go into 2021, certainly with hopefully a light at the end of the tunnel here in terms of the pandemic with the latest news we’re hearing about vaccines, I’m actually very optimistic,” Fuetsch added.

References:

https://about.att.com/story/2020/john_stephens_update.html

https://www.sdxcentral.com/articles/news/att-cto-claims-covid-19-blurred-consumer-enterprise-divide/2020/11/

 

 

COVID-19 has changed how we look at telecom infrastructure, cloud and AI

by John Strand, Strand Consult, Denmark; edited for clarity by Alan J Weissberger

The coronavirus (COVID-19) crisis has proven that telecom infrastructure is critically important.  Telecommunications networks delivered service during the lockdown, enabling many to continue to work, learn, shop, and access healthcare. Policymakers will likely revisit regulation for telecom networks, not only to optimize network investment, but to improve security. Indeed, policymakers will also realize that security which has focused to date on the transport layer of networks is leaving the access and applications layers vulnerable.

While the focus on Huawei is long overdue, the discussion of network security and Huawei’s role are oversimplified. It is insufficient to address only one aspect of conventional components of networks: access, core, and transport. The bigger issues are how end-user data will be protected while stored in cloud or being processed by artificial intelligence (AI) and how connected devices on Internet of Things (IoT) networks and other applications such as smart city solutions can be secured?

Historically network connectivity was likened to the dumb pipe, the medium which transmits data. The “smart parts” of the network were the edge and the core, where users access networks and where information processing occurs. These actions have become more complex with third party providers of AI and cloud computing. Naturally, these models don’t fit 5G because intelligence must exist throughout the network.  However, telecom regulation has been associated with these three traditional functions.

Now that networks have evolved, it’s time for telecom regulation to evolve. If the goal of security measures is to reduce the risk and vulnerability of exposure to Chinese state-owned and affiliated firms, then policymakers need holistic frameworks that address the multiple aspects of network security at its various layers: application, transport, and access.

Indeed, the singular focus on Huawei in connectivity misses the fact that Huawei sells products for the other layers, and that many other Chinese state-owned firms should be scrutinized. For example, Baidu, WeChat, Alibaba, and Huawei provide AI solutions in the Applications layer; Huawei and ZTE in transport; and Huawei  smartphones and laptops by Lenovo  (the world’s leading maker of laptops as well as a leader in servers).

Strand Consult has described this in the research note The debate about network security is more complex than Huawei. Look at Lenovo laptops and servers and the many other devices connected to the internet.

The EU’s 5G Toolbox is the first step towards greater security and accountability for a discrete part of 5G network transport, but it does not address all elements of 5G security nor other layers.  In performing its security assessment, the United Kingdom looked beyond 5G mobile Radio Access Networks (RAN) and Core to other network layers, types and technology, notably wireline networks. Policymakers need a broader focus than 5G when assessing the security of telecommunications networks in the future.  Policymakers need to look at Huawei’s movement into cloud and AI solutions in the application layer as well as the many state-owned Chinese firms in the access layer like Lenovo.

In China, Huawei is vertically integrated and delivers a suite of products and services for all the layers of a network: it transports the data; it provides access through end user devices, and it provides the applications in the form of AI and cloud solutions. While European policymakers debate issues of RAN and core, Huawei is busy selling other solutions for the rest of the network: smartphones, routers, AI, and cloud solutions. As restrictions tighten on Huawei’s network products, the company will naturally push other business lines to compensate for lost revenue. A large operator in Europe works with Huawei on a joint Chinese-German cloud platform, and the reference customer for this solution is the European Organization for Nuclear Research, CERN in Switzerland. It is not logical how Huawei which can be deemed high risk for telecommunications and military networks, but somehow neutral for nuclear research. The agreement for the project is four years old; the question is whether such a project will be acceptable for political and security standards going forward.

Vertical integration was the standard model for traditional state-owned telecommunications. The government built a telephone network (the wires and switches); it delivered a single service – telephony; and it sold the end user device, typically a classic phone. Privatizing networks was about opening up the value chain to different kinds of providers. This worked well in mobile networks; different firms specialized for different parts of the value chain. However, Huawei is driving the decentralized chain back to the state-centered concept, perhaps fitting for its practice in China where it partners with the government to deliver full-service surveillance solutions.

Policymakers, regulators, and competition authorities have long been skeptical of vertical integration in telecommunications, and it was frequently a way to control traditional telecom operators by demanding that the divest certain parts of their business or by prohibiting certain acquisitions.

COVID-19 has proven that telecommunications networks are vital infrastructure at all layers and levels. It’s not just military and public safety networks that need to be secure. Everyone needs to have secure networks if we are live in a digital society. If politicians and telecom operators don’t recognize this, network users do. Change is being driven by companies which themselves are increasingly victims of cyber-attacks. Companies are putting increased pressure on telecom operators and governments to do more to make networks secure.

John Strand | New Europe

John Strand of Strand Consult

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Six big issues on the future of telecom regulation:

Strand Consult believes that governments will take a broader view about network security. Here are six categories of issues for policymakers to consider.

  1. What is critical infrastructure, and how will it be defined in the future? Historically, critical infrastructure had to do with physical and digital network assets which are required for physical and economic security, health, and safety. Indeed, there are many vital network assets deemed “critical” including those for chemicals, communications, manufacturing, dams, defense, emergency services, energy, financials, food/agriculture, government facilities, healthcare, information technology, nuclear reactors, transportations systems, and water/wastewater. Are these networks equally prioritized? What are the security concerns and protocols for each, both on the physical and cyber fronts? Do some have greater security than others? How does this change in the COVID-19 world?
  2. What are the government’s responsibilities to ensure the security of communications infrastructure?What are the minimum requirements to restrict a vendor? How is this balanced with requirements for fair and open processes for bids and tenders?
  3. What are the relevant communications networks to secure? Is it enough to focus on 5G mobile RAN and core or should security requirements apply to wireline networks, satellite, Wi-Fi, 3G/4G and so on?
  4. Is it sufficient only to address the transport element of network security? How will security be ensured for the storage and processing of data, for example on the computers, laptops, and servers provided by Chinese state-owned Lenovo where China’s rules for surveillance and espionage also apply? What about apps like TikTok and Huawei’s AI and cloud solutions?
  5. Who should perform the security assessment? Telecom operators, military departments, intelligence agencies, private security consultants, law enforcement, or some other actor?
  6. How will shareholders account for increased security risk in networks? Have shareholder asked relevant questions about operators’ security practices and the associated risk?

Strand Consult believes it is dangerous for telecom operators to make the decision about Huawei themselves without involving the authorities.

There are a lot of arguments for why telecommunications companies should involve the competent and relevant authorities. Telecom operators must understand that If telecommunications companies assume responsibility as those who assess each supplier in relation to national security, they will be held responsible when things go wrong.

When you take on a responsibility, you also take on risk. Thus, shareholders are exposed to increasing risk when using high risk vendors. The historical facts show that telecommunications companies have been wrong in the past when assessing cooperation with partners which have proven to be corrupt. Some partnerships have cost shareholders billions of euros. In practice, operators are limited in their ability to judge whether partners and vendors are trustworthy.

Strand Consult’s research shows that is not only government, intelligence, and security officials who are concerned about companies like Huawei. Nor is it just telecom operators which build and run networks. It is the small, medium, and large enterprises that use networks that fear that their valuable data will be surveyed, sabotaged, or stolen by actors associated with the Chinese government and military. Consequently, it is the clients of telecom operators which push to restrict Chinese made equipment from networks. This is described in this research note, The pressure to restrict Huawei from telecom networks is driven not by governments, but the many companies which have experienced hacking, IP theft, or espionage.

What the future looks like – just ask the banks:

If you want to see the future of the telecom industry, look at what happened with banking. European banks have been required to implement Anti-Money Laundering (AML) and the Counter Terrorist Financing (CFT). About 10% of European banks employees are today working with compliance. Telecom authorities, defense officials, and other policymakers and will likely see cybersecurity is vital for Europe and that telecom infrastructure is critically important. So just as the banks have been put under a heavy regulatory regime to address corruption and financial crimes, the telecom industry will be required to implement deterrence of cyberattacks.

In practical terms, the authorities in the EU and in each nation state will likely make some demands that challenge the network paradigm that telecommunications companies operate today. The rules will likely be so rigid that they will effectively eliminate Huawei and other Chinese companies from being vendors without making explicit bans. However, it won’t be governments alone driving the charge. Corporate customers of telecom networks, companies that have experienced hacking, IP theft, or espionage, will also join the effort. This is described in this research note, The biggest taboo in European telecom industry is the cost of cybersecurity – just ask the banks.

Copyright 2020. All rights reserved

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About Strand Consult:

Strand Consult, an independent company, produces strategic reports, research notes and workshops on the mobile telecom industry.

For 25 years, Strand Consult has held strategic workshops for boards of directors and other leaders in the telecom industry. We offer strategic knowledge on global regulatory trends and the experience of operators worldwide packaged it into a workshop for professionals with responsibility for policy, public affairs, regulation, communications, strategy and related roles.

Learn more about John Strand: www.understandingmobile.com

Learn more about Strand Consult: www.strandreports.com

Strand Consult
Gammel Mønt 14
Copenhagen 1117 K
Denmark
info@strandconsult.dk

Juniper Research: Network Operators to Spend Billions on AI Solutions

A new study from Juniper Research has found that total network operator spending on AI solutions will exceed $15 billion by 2024; rising from $3 billion in 2020. The research identifies network optimisation and fraud mitigation solutions as the most highly sought-after AI based services over the next 4 years. AI-based solutions automate network functionalities including routing, traffic management and predictive maintenance solutions.

For more insights, download our free whitepaper, How AI Analytics will Boost Operators’ Revenue.

Network Optimisation & Fraud Prevention Driving Adoption in Developed Markets

The new research, AI Strategies for Network Operators: Key Use Cases & Monetisation Models 2020-2024, found that operators in developed regions, such as North America and Europe, would account for over 40% of AI spend by 2024, despite only accounting for less than 20% of global subscribers. It predicts that growing demand for operational efficiencies will drive operators in these regions to increase their overall investment into AI over the next 4 years.

The research urges operators to embrace a holistic approach to AI implementation across service operations, rather than applying separate AI strategies to individual use cases. It suggests network operators leverage AI to unify internal data resources and encourage cross-functional insight sharing into network efficiencies to maximise the benefits of collaboration across internal teams.

Image result for pic of ai in telecommunications

The research predicts that AI spend by Emerging Markets operators will exceed $5 billion by 2024, rising from only $900 million in 2020. It found that this growth will be driven largely by operators exploring early use cases of AI before expanding the presence of AI in their networks to include more comprehensive services.

The report forecasts that Indian Subcontinent and Africa & Middle East will experience the highest growth in spend on AI services, with operator spend in both regions forecast to grow over 550% over the next 4 years. It anticipates that operators in these regions will initially invest in AI-based CRM (Customer Relationship Management) solutions that yield immediate benefits.

Related post:

Market Research Firms say Telcos Need to Invest in AI now!

 

 

Market Research Firms say Telcos Need to Invest in AI now!

Due to ever increasing demand for data, saturated mobile markets, and stiff opposition from cloud companies,  global telecom network providers are facing difficult times. These market pressures have led to vicious price wars for mobile services and, as a result, declining average revenue per user (ARPU).  This is especially true in India where Vodafone Idea and Bharti Airtel have recently announced huge losses, write-downs as their share prices collapsed.

Mobile revenue

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Artificial Intelligence (AI) use in Telecommunications:

For many global telecoms, shoring up market share under today’s pressures while also future-proofing operations means having to invest in AI. The telecom industry is expected to invest $36.7 billion annually in AI software, hardware, and services by 2025, according to Tractica.

Through its ability to parse large data sets in a contextual manner, provide requested information or analysis, and trigger actions, AI can help telecoms cut costs and streamline by digitizing their operations. In practice, this means leveraging the increasingly vast gold mine of data generated by customers that passes through wireless networks — the amount of data that moves through AT&T’s wireless network has increased 470,000% since 2007, for example.

AI applications in the telecommunications industry use advanced algorithms to look for patterns within the data, enabling telcos to both detect and predict network anomalies, and allowing them to proactively fix problems before customers are negatively impacted.

Image result for images: AI in telecommunications

Some forward-thinking telcos have focused their AI investments on four main areas:

  • Network optimization
  • Preventive maintenance
  • Virtual Assistants
  • Robotic process automation (RPA)

In these areas, AI has already begun to deliver tangible business results, according to blogger Liad Churchill

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Meanwhile, a Tractia report on AI for Telecommunications Applications identifies the following functions which will benefit from AI:

  • Network Operations Monitoring & Management
  • Customer Service & Marketing VDAs (Voluntary Disclosure Agreements)
  • Intelligent CRM Systems
  • Customer Experience Management
  • Cybersecurity & Fraud Mitigation
  • Other Use Cases

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Here are a few takeaways from the AI in Telecommunications report by Business Insider Intelligence:

  • Telecoms have long struggled with their customer experience image: In 2018, telecommunications had the lowest average Net Promoter Score (NPS), a measure of how favorably a company is viewed by customers, of any industry.
  • Companies that use advanced analytics, which can be accessed via AI, to improve this image and the overall customer experience are seeing revenue gains and cost reductions within a few years of adoption.
  • Most (57%) executives believe that AI will transform their companies within three years, per Deloitte’s State of AI in Enterprise.
  • Overall, telecoms should focus on a hybrid organizational model to move beyond pilots to launch full-scale AI solutions that can have the biggest impact on their companies.

References:

https://www.businessinsider.com/the-ai-in-telecommunications-report-2019-7

https://techsee.me/blog/artificial-intelligence-in-telecommunications-industry/

Artificial Intelligence for Telecommunications Applications

 

GSMA, China Telecom & Huawei on 5G; GSMA says 40% of the world’s population will be on 5G by 2025

Mats Granryd, the Director General of the telecom trade organisation GSMA talked up  5G and AI in a keynote speech on “intelligent connectivity” at Huawei’s MBB 2018 event at London’s ExCel.  Granryd said those two emerging technologies will be key enablers for what the telecom industry has to offer in the years to come.  Granryd discussed the potential of 5G to drive inclusion, growth and sustainable development, especially in the developing world. He also touched on the impact of “smart” capabilities like artificial intelligence and network capabilities, and how such networks and technologies must be secure to drive the growth not only of smart cities, but all cities. He said intelligent management will be key with “the development of a rich and vibrant digital economy.”

In addition to predicting that 70% of the world’s population, or roughly 6 billion people will be on mobile internet, GSMA forecast 40% of the world population will be on 5G networks. When it comes to AI, on top of improving individual experience (e.g. Personal Assistants) and serving new industry needs (e.g. network slicing), Granryd highlighted what the combined AI capabilities can do for society. The GSMA’s “Big Data for Social Good” initiative has launched in seven countries around the world. Mobile operators in those markets have worked with local partners to enable air pollution warning, malaria spreading prediction, and natural disaster preparedness, using big data and machine learning and prediction capabilities.

Guiqing Liu, EVP of China Telecom, the world’s largest integrated operators in the world by subscriber number, then took the stage to share what China Telecom saw as the biggest opportunity for telecom operators to undertake the digital transformation, especially with the ascendancy of industry markets. Liu included four key capabilities the industry in particular the operators need to master to succeed in the transformation. They are:

  • End-to-end slicing to cater to different user and industry needs;
  • FMC (Fixed to Mobile Convergence) edge computing to deliver seamless experience;
  • 5G+Cloud based network and services to provide flexible and special customization; and
  • 5G+AI to both optimise service delivery and network management.

Liu also outlined the key challenges the industry is facing before 5G can become a real commercial success. He conceded that use cases now are still very much focused on eMBB, and the industry has not thought through how to change business models in the new era, including how to bill customers for the new use cases. On network challenges, in addition to the CAPEX and OPEX and skill gap, Liu also pointed the indoor coverage weakness intrinsic of the high frequency bands most 5G networks will be built on.  For 5G to truly be transformative and improve people’s lives, Liu said that companies will need to work together and collaborate – even if they’ve traditionally been rivals.

Ken Hu, deputy and rotating chairperson of Huawei stressed the importance 5G was already playing in shaping the future of not only business, but humanity, adding Huawei has been working on 5G for more than 10 years. “We believe 5G will make a big contribution to our society.”  Hu also said 5G was leading to the integration of previously separate technologies and services not unlike individual pieces of Lego bricks being combined to make something larger – fundamentally changing the definition of what a telco or technology company is. The user experience will be redefined by 5G.”

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Outside the main presentation halls, a number of booths showcased both Huawei technologies and those from  Huawei partners. A “5G bus” drove people around the surrounding Docklands area. The demo drive showed that 5G connections, download speeds and more could all be achieved while physically moving across large distances at a high speed and in poor weather (this being London, it was fittingly rainy, windy and cold). Tents erected outside ExCel London were also stuffed with 5G use case demonstrations.

References:

http://telecoms.com/493703/40-of-the-worlds-population-on-5g-by-2025-says-gsma/

https://www.commsmea.com/technology/18549-what-we-learned-at-day-one-of-huaweis-5g-focused-global-mbb-forum-in-london

 

SVIEF Kai-Fu Lee Keynote: Era of AI, Rise of China, U.S. vs China, etc & All Star Panel Session (?)

Well respected technologist, entrepreneur, writer and AI researcher Kai-Fu Lee, PhD presented a powerful and very incisive keynote speech on September 29th at the SVIEF conference in Santa Clara, CA.  The title of his talk was all encompassing and compelling:  “Era of AI, the Rise of China, and the Future of Work.”

Author’s Note: I was so impressed with Kai-Fu’s talk, I’ve ordered his latest book, AI Superpowers, which is already on Amazon’s best selling book list.

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Here are several important highlights of Dr. Lee’s SVIEF keynote:

1.    Deep Learning (DL) is the biggest technological improvement in the 60+ year history of artificial intelligence (AI).  DL is a network of highly connected neurons in thousands of layers that can, in a single domain, take a huge amount of data and train to recognize, predict and decide and synthesize at a much higher accuracy than humans.

2.    DL is not human intelligence, it cannot think or cross domainsIt has no strategic or creative thinking capabilities. But in a single domain, with a huge amount of data, it is beating humans in almost every task imaginable. For example, AlphaGo (a computer program that plays the board game Go) has beaten Go champions. In addition, we’ve seen DL used effectively for speech recognition (e.g. Amazon Alexa, Google voice search, Microsoft Cortana, etc.) and facial recognition. There are new beginnings  of DL diagnosis of how to read  MRIs and doing a better job of that than radiologists. 

3.   This amount of improvement is leading to what are four waves of artificial intelligence:

  • Wave 1: Internet AI started in 1998. The Internet has more data than any other domain. With so much data, it enables Amazon to predict what you might want to buy. It powers Facebook to predict what you might want to read on-line.   Similarly, all the American and Chinese companies (Alibaba, Baidu, Tencent, etc) , all the great AI companies of today are all Internet companies, because they have the most labeled data.
  • Wave 2: Business AI started in 2004. Take banks, insurance companies, hospitals –they have amassed a lot of data in the past, they viewed data as a call center, as a legal requirement to archive. But now data has become a goldmine for them in various ways.
  • Wave 3: Perception AI started in 2011- the ability to see and hear.  Examples include: computer vision, speech recognition, speech synthesis, understanding all combined together. It also can be viewed as digitizing the physical world.
  • Wave 4: Autonomous AI (self driving cars, autonomous robots, etc) started in 2015.  In this wave 4, AI becomes autonomous in its ability to move around and manipulate sort of like having hands and feet. That will usher in an era of autonomous vehicles and robotics. Autonomous vehicles will bring about a huge transformation, especially the dis-incentive to own a car.  With safer autonomous vehicles, the natural next step is humans won’t be allowed to drive anymore.

4.    To make AI work, we need the following things:  a lot of data that is tagged within a single domain, a lot of compute power, and some AI experts to work on it.

AI is not perfect you can’t make it do perfectly unsupervised learning. You can’t make it learn on very little data. You can’t do AI with very little compute power.  

But once you have those in place, AI can be effectively applied.  

5.   U.S. Leads China in Top Researchers, Patents, and AI Talent (and will likely continue to lead in AI research in the near future).

6.    Chinese Miracle of Last 10 Years with fast product/service iteration, intense competition, user acquisition, accelerated growth, high return on investment in a huge market.

7.   In 2018: U.S. and China Have Become Parallel Universes:

US Model: Breakthrough Technologies, Vision-driven, Light, Globalized.

China Model: Fusion + speed, Applications, Result-driven, Heavy, Localized.

8.  Investment in China:   A lot of money and capital investment went into China with smart VCs helping smart entrepreneurs build products and companies. And those products actually are so attractive they brought more Chinese users on the internet. And this loop kept going and going for the last 10 years taking China from 150 million users to about 800 million users by far the largest user base in the world. And this loop has created something that we never thought possible — a system that parallels the Silicon Valley.

9. The only way to succeed in China is to find a business model that is impregnable. In other words, build a business that’s uncomfortable.  Chinese companies kept improving going from copying from the U.S. to inspired by us and then leapfrogging the U.S.  For example, WeChat (messaging app) is better than WhatsApp and way better than Twitter.  But even more exciting is the third ladder where Chinese companies are brand new innovation, this Chinese model of building impregnable businesses have reached new heights, so that these brand new companies are being built.

10.   China Advantages over U.S. in AI:

Advantage 1: Chinese Product Innovation has Caught up with U.S.  Pure Chinese Innovations Have Arrived

Advantage 2: Tough Market Begets Tough Entrepreneurs

Advantage 3: China’s AI Capital Leads the World.  48% of global AI investments were made in China; 38% in U.S., 13% other countries. SOURCE: CB Insights 2017 Global Artificial Intelligence Investment

Advantage 4: AI Moves into Era of Implementation

Advantage 5: China is the world leader in amount of Data  (like Saudi Arabia is the country with the most oil for export).  Massive Data is Critical for AI Product Success– even more important than algorithms.  AI algorithms are generally shared, and it is up to the speed, execution, and size of the data that determines how companies will benefit from AI implementations.

11.  U.S.  Advantage over China in AI:  Early Adopters, Expert is King  (vs China which is Application Driven and Data is King)

12.  Who’s ahead in AI, mobile and Internet:  Dr. Lee thinks that generally U.S. is a little bit ahead today. But China will probably be ahead in four or five years. This is not about research. This is about implementation. 

U.S. will continue to be ahead in research for the next 10 or 15 years, because that lead is very difficult to overcome.

But this is not a zero sum game. U.S. VCs fund U.S. companies that develop products for us customers, whereas Chinese VCs fund Chinese companies who develop products for Chinese customers (domestic market).  The two countries are not going after the same market.  

“When a Chinese company wins, a  U.S. company does not lose.  When a U.S. company wins, a Chinese company does not lose. So I think the sentiment behind the current some of the current rhetoric is not correct. This is truly not a zero sum game. This is merely a keeping score of how far ahead each technology might get. So with China and us both pushing forward AI, I think AI will make a lot more progress than internet and mobile because those only had one engine the U.S. pushing forward. And there are a bunch of other reasons such as the seven cloud giants (Amazon, Google, Facebook, Microsoft, Alibaba, Baidu, Tenent) hiring people, and training people with large amounts of data VCs being devoted to AI.”

 

Concluding take-aways:

  1.  Embrace AI – it saves us from repetitive work and pushes us to do what human is called for.
  2.  AI cannot create ideas or thoughts. We are the masters and should be responsible of how to use AI.
  3.  (via Twitter) How U.S. can stay ahead in AI: 1) double AI funding, 2) increase AI professors pay, 3)offer green cards to all AI PhD’s.

Closing Quotes:

“So going forward, I think AI is electricity in the next 20 years, there will be huge opportunities and challenges. But I want to take us a moment into (the next) 50 years. When we look back ignore for the moment all these job displacement opportunities, I like to leave you with two thoughts. The first thought is that AI is serendipity. It is here to take away the routine jobs so we can really spend time on what we love and what human beings are on this earth for. And secondly, for those worry about AI causing problems. Just keep in mind AI is just a tool.  It possesses no creativity. We (humans) are the Masters.  We are the ones that have free will. And it’s going to be up to us humans to write the ending to the story of artificial intelligence. Thank you.”

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In a post SVIEF conference email exchange related to AI’s use in telecommunications applications, Kai-Fu wrote this author:

“Thanks — this is not my major area of expertise.  But clearly communications in autonomous vehicles, IoT, and 5G, when combined with AI, will be a great combination.”

“On China catching up, it will be in technology related to the Internet, Mobile, and AI.”

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SVIEF All Star Panel:

Kai-Fu Lee: “I feel a sense of social responsibility to tell people that as AI advances, job displacement is a serious issue. And I think I thought very hard about various solutions. I looked at universal basic income, I don’t think that’s going to work. I don’t really know what will work. But I do think generally, it’s in the direction of creating more empathetic jobs, because there should be a large enough pool of them, if only we would care about them, pay more for them. And that can hopefully lead us to a good ending.”

SVIEF All-star panel with VC Tim Draper, AI Rock Star Kai-Fu Lee, and Stanford Physics Prof. Shoucheng Zhang

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Author’s Note:

Due to time and space constraints the above panel session may be summarized in a follow on article, provided there is sufficient reader interest.

Please email me at: alan.weissberger@ieee.org if you’d like me to write such an article.

References:

Transcript of Kai Fu Lee’s keynote (via speech recognition):

https://otter.ai/shared/conversation/5342b3f76e67477c958742982795ffec

https://www.nytimes.com/2018/09/22/opinion/sunday/ai-china-united-states.html

 

 

Nokia & China Mobile collaborate on 5G and AI; Nokia & Tencent on 5G in China

Nokia and China Mobile Collaboration Summary:

Nokia and China Mobile have signed an agreement (MoU) to investigate the potential of artificial intelligence (AI) and machine learning to optimize future wireless networks and enable the delivery of new edge cloud computing and “5G” services.

As part of the collaboration, the two companies will jointly establish a research laboratory in Hangzhou, China to develop a demo system to verify technology use cases using Nokia’s 5G Future X architecture.   Meanwhile, China Mobile will lead the research of scenario selections, requirements confirmation, open API specifications and solution definition. Nokia and China Mobile will also conduct technology field trials and demonstrations.

The companies’ will also work together to research applications for AI and machine learning.  The objective is to ensure any changes in data traffic demand are predicted and network resources are automatically allocated to meet all service demands with consistent high quality and reliability.

The collaboration is intended to foster an open RAN and 5G ecosystem as Nokia and China Mobile work with third parties to leverage AI and machine learning. A goal is to optimize next generation wireless networks for the delivery of high bandwidth, low latency services such as cloud virtual reality based gaming.  The companies’ research will leverage Nokia AirScale Cloud RAN, AirFrame OpenRack, open edge server and ReefShark chipsets, as well as Nokia-developed AI middleware to access embedded intelligence.

China Mobile Research Institute (CMRI) deputy general manager Yuhong Huang said the wireless telco giant has been paying attention to the application of artificial intelligence for a long time, and is working to build an open and collaborative 5G+AI ecosystem.

“With the signing of this MoU, we are pleased to initiate the collaboration on the research of big data and machine learning technologies applying to 5G RAN network. [We will also] make joint effort in the O-RAN alliance which was kicked off recently to enhance the intelligence of 5G networks, reduce the complexity, and explore the new capabilities of the network,” Huang said.

“The use of AI and machine learning will enable myriad new services opportunities and we are pleased to leverage the capabilities of our 5G Future X architecture to support China Mobile’s AI research to optimize future networks and the delivery of many innovative new services,” said Marc Rouanne, Nokia’s President of Mobile Networks.

Teaming with Tencent to explore 5G initiatives in China

In a separate announcement, Nokia said it has struck a partnership with Chinese internet giant Tencent to jointly conduct R&D work to explore the potential of 5G that “will benefits billions of internet users in China.”

The two companies will establish a joint lab in Shenzhen that provides an end-to-end 5G test environment leveraging 5G technologies, products and solutions, including centralized and decentralized split architecture using Nokia Airscale Radio Access Network, 5G Core, MEC framework and third party devices.

Nokia and Tencent will conduct verification on service key performance indicators and develop new 5G and IoT use cases.   Those two companies will also leverage the AI and automation management capabilities to promote international standards (which one’s were not specified), and to foster an open-source ecosystem that will expand the development of new services.

The pair will also be conducting 5G applications research by making use of technologies like edge computing, which will be of great advantage for a number of vertical markets, including transportation, finance, energy, intelligent manufacturing and entertainment.

This will potentially open up the widespread introduction of applications such as cellular vehicle-to-everything (C-V2X) communications and enhance the delivery of services such as cloud-based gaming and entertainment, the companies said.

References:

https://www.nokia.com/en_int/news/releases/2018/07/06/nokia-and-china-mobile-to-set-up-joint-ai5g-lab-for-further-research-using-artificial-intelligence-and-machine-learning-in-5g-networks

https://telecomtimes.com.au/2018/07/07/nokia-china-mobile-join-forces-in-ai-5g-research-push/

https://techblog.comsoc.org/2018/07/05/nokia-tencent-working-together-on-5g-applications/

Artificial Intelligence (AI) and Internet of Things (IoT): Huge Impact on Tech Industry

Overview:

The biggest themes at IoT DevCon today in Santa Clara, CA are the following: AI will be pervasive in every industry during at least the next decade; voice is replacing the keypad/keyboard as the preferred human interface, IoT will fulfill its promise and potential once the cyber security and privacy issues have been solved.

As these innovative and cutting edge technologies fuse together experts in the market are forecasting exponential growth over the next seven years while revolutionizing everyday products with amazing potential.

Grand View Research projects the wireless mesh network alone will be worth north of $11 billion globally by the year 2025. One of the significant factors driving market growth is the variety of applications across multiple industries for these platforms, ranging from traditional business projects to emergency services. The inclusion of IoT and AI are expected to expedite the process, allowing for more efficient and effective operations of MESH applications and networks.  AI not only involves massive parallel computing, but also lots of data movement is needed to come up with results.

Here are a few of the IoT DevCon sessions I attended today (please contact the author if you’d like details on any of them):

09:00-09:30                   General Remarks and Notes on the Internet of Intelligent Things. ME1941»
TIRIAS Research
09:30-10:00 KEYNOTE: Surviving the IoT Device Security Wild West ME1916»
Arm
10:00-10:30 KEYNOTE ADDRESS: Wireless Connectivity (IoT) Testing Challenges and Considerations ME1859»
Rohde & Schwarz
10:30-11:00 Morning Break – Day 1
11:00-11:30 KEYNOTE ADDRESS: Edge Computing Revolution ME1930»
NXP
11:30-12:00 The Future of IoT from a Venture Capital Perspective ME1841»
Bessemer Venture Partners

 

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Gopher Protocol Inc Decentralized MESH System:

Gopher Protocol, a company specializing in the creation of Internet of Things (IoT) and Artificial Intelligence enabled mobile technologies, today announced that it has completed the first phase of its Decentralized MESH system architectural functionality simulation. These simulations tested Gopher’s unstructured MESH network, performing node and gateway communication scenarios while observing timing and performance. The team was able to successfully simulate “node to node” and “node to gateway” network communication, within a defined range.

From the company’s website:

Gopher Protocol (GOPH) Core Technology is a revolutionary new platform with products that will change the way people interact with technology and each other, because we believe that improving communications will benefit the modern world.

GOPH Microchips communicate via a private, secured protocol and can interact with internal states –  microchips communicate with other microchips –  and external environments – microchips interact with cell phones, mobile apps, computers, tablets, tracking devices and many other digital devices with access to conventional networks (WiFi and Cellular).

Our goal for GopherInsight Microchips is that they will potentially be installed in billions of mobile devices by the year 2020. This will allow GOPH to create its own private communication network, which will enormously benefit the user from behind the scenes. We utilize this private network to improve the computing power, database management, internal memory, and security of mobile devices equipped with GopherInsight Microchips! The potential is enormous and we are constantly developing more advanced features.

A wireless mesh network is a communications network made up of radio nodes (telephones or other connected devices) organized in a mesh topology (random dispersion across a given area). MESH refers to rich interconnection among devices or nodes. Wireless mesh networks typically consist of mesh clients(users) and gateways (internet access points). Other companies that have wireless mesh networks for IoT include Microchip’s MiWi™  (based on IEEE 802.15.4 – low-rate wireless personal area networks or LR-WPANs) and the Wirepas mesh network (based on Low Power Bluetooth).

 

MIWI Dev Env Block thumb

Above illustration courtesy of Microchip

MiWi supports operation the IEEE 802.15.4 radio PHY in the sub-GHz and 2.4 GHz ISM bands.  Developed to enable low-cost, commercial and smart home networks, MiWi is used in applications such HVAC systems and alarm sensors where reliable self-healing mesh networking is needed.

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The Gopher Decentralized MESH network will be a mobile network, which adds additional complexity as the nodes move frequently. The main challenge of developing Gopher’s MESH network is updating routes of data considering that nodes are moving within the MESH. Managing these nodes is achieved by our time division based electronic hardware combined with Gopher’s Avant! Artificial Intelligence engine that is cognitively learning about the dynamic GEO locations of nodes and gateways in order to control the unstructured mesh network.

“This is a very significant stage for us” stated Danny Rittman, Gopher’s CTO. “We successfully conducted a node hopping simulation which we believe is one of the key technological hurdles in creating a MESH network. In addition, we also performed “node to gateway” communications and multiple “node hopping” all the way to a gateway. The results were successful for a defined range and beyond. We are now constructing testing boards to further analyze the technology in order to identify methods of improvements and advancements.”

“We are also working on our Avant! AI engine, providing it with the mathematical knowledge with the goal of developing it to a point to control the entire system. Unstructured networks are particularly difficult to control without the involvement of highly mathematical models and algorithms” continued Dr. Rittman. Gopher believes the development of a mesh network and technology is crucial to the creation of a communications network that disrupts the incumbent Internet and data providers that are the gatekeepers of communication access for the developed world. Gopher intends to bring connectivity to the hundreds of millions that cannot easily afford the current global cost of connectivity and to make the rapidly growing internet of things more affordable for all.

Read more about GOPH at http://www.marketnewsupdates.com/news/goph.html 

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Other related developments in IoT and AI include:

1.  Microsoft Corporation recently announced a strategic partnership to deliver new technology developments and go-to-market initiatives that accelerate enterprise AI and IoT application development. As part of this partnership, the companies will create a “better together” solution, comprising the C3 IoT Platform™, a low-code, high-productivity PaaS for scaling AI and IoT across enterprises, fully integrated to operate on Microsoft Azure. C3 IoT will leverage Microsoft Azure as a preferred cloud platform and tap into the power of its intelligent capabilities. The companies will conduct co-marketing and co-selling strategies that rapidly scale distribution globally, as well as intensive training for dedicated teams to speed customers’ time to value. Close collaboration between Microsoft and C3 IoT will help enable customers to more rapidly develop and deploy AI-based applications for transformative use cases, such as AI predictive maintenance, dynamic inventory optimization, precision healthcare and CRM.

2. Naveen Rao, vice president and general manager of the Artificial Intelligence Products Group at Intel Corporation said in advance of the company’s upcoming AI DevCon:

This is an exciting week as we gather the brightest minds working with artificial intelligence (AI) at Intel AI DevCon, our inaugural AI developer conference. We recognize that achieving the full promise of AI isn’t something we at Intel can do alone. Rather, we need to address it together as an industry, inclusive of the developer community, academia, the software ecosystem and more. So as I take the stage today, I am excited to do it with so many others throughout the industry.

This includes developers joining us for demonstrations, research and hands-on training. We’re also joined by supporters including Google*, AWS*, Microsoft*, Novartis* and C3 IoT*. It is this breadth of collaboration that will help us collectively empower the community to deliver the hardware and software needed to innovate faster and stay nimble on the many paths to AI. Indeed, as I think about what will help us accelerate the transition to the AI-driven future of computing, it is ensuring we deliver solutions that are both comprehensive and enterprise-scale. This means solutions that offer the largest breadth of compute, with multiple architectures supporting milliwatts to kilowatts.

Enterprise-scale AI also means embracing and extending the tools, open frameworks and infrastructure the industry has already invested in to better enable researchers to perform tasks across the variety of AI workloads. For example, AI developers are increasingly interested in programming directly to open-source frameworks versus a specific product software platform, again allowing development to occur more quickly and efficiently.

Mr. Rao’s AI Devcon 2018 presentation is at:

https://s21.q4cdn.com/600692695/files/doc_presentations/2018/05/AI_Devcon_RAO_Final.pdf