China could surpass the US in artificial intelligence tech. Here's how
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China could surpass the US in artificial intelligence tech. Here's how

Artificial intelligence has the potential to transform many industries: Cars that drive themselves, facial recognition that enhances security, or systems that could detect cancer better than a doctor.In fact, global GDP is set to increase by 14 percent because of AI, according to PwC. The tech's deployment in the decade ahead will add $15.7 trillion to global GDP, with Chinapredicted to take $7 trillion and North America $3.7 trillion, according to the multinational company."Data is the new oil, so China is the new Saudi Arabia," Kai-Fu Lee, venture capitalist and author of "AI Superpowers: China, Silicon Valley, and the New World Order," told CNBC's "Squawk Box.""If you measure by research — basic research papers published, excellence of research — U.S. is and will be ahead for the next decade," he said. "But if you measure by value created, how much market capitalization, how many users, how much revenue, China probably is already ahead."Lee said AI could replace 40 to 50 percent of all jobs in the U.S. in the next 15 years.China's development planAI development reached a symbolic moment in May 2017 during a match of Go, considered to be the world's most complex game.Ke Jie, a Chinese player known as the world's best, competed against a program from Google parent company Alphabet in a three-game match. The young pro lost all three games.Less than two month after the defeat, China's central government announced its ambitious plans to build its AI capabilities, where it aims to create "a next generation artificial intelligence development plan."The plan is broken up into three benchmarks: Keep pace with AI technologies by 2020, achieve AI breakthroughs by 2025, and to actually be the world leader in AI by 2030.In 2017, Chinese venture capital investors poured record sums of money into AI — making up 48 percent of all AI venture funding globally.Chinese start-ups raised $4.9 billion in 2017 made up of just 19 investments, while their U.S. counterparts raised $4.4 billion from 155 investments.Some critics have said, however, that the sector is over-invested and they've expressed skepticism about the industry's ability to monetize.Data and regulationChina has several advantages when it comes to the artificial intelligence field, but chief among them is Chinese companies' access to troves of data."(China has) done a fantastic job of moving its economy to cashless and when you can pay with everything with your phone, you amass a huge amount of data," author and columnist Thomas Friedman told CNBC."When you can get these giant data sets, and then apply artificial intelligence to them," he said. "You're going to see better and better and more deep insight patterns than anyone else and I think it'll be a great advantage for China."On top of that, China doesn't have the same restrictive privacy laws as many other countries, making it easier for companies to collect data. Its government buys technologies to capture unprecedented amounts of information on its citizens.The talent raceStill, China is not yet the dominant force in the world of AI."The innovation is still coming from the U.S. and that's thanks to, obviously, a huge network of universities that are fed by the world's greatest talent — not just Chinese engineers coming to the U.S., and computer scientists, but also from India and everywhere else," Ben Harburg, managing partner at MSA Capital, told CNBC at the East Tech West conference last month. "That advantage, for the next few years at least, stays with the U.S."Still, Harburg noted China's large data sets, and the country's large number of graduates in STEM fields."China will be where you monetize and, by nature of the beast, eventually they will start to innovate far beyond the U.S. — but a couple years away," he added.Meanwhile, Friedman said the race in AI could potentially come down to politics. More specifically, U.S. President Donald Trump's stance on immigration."What really drove our economy forward, what drives any economy, is that we had a higher percentage than any other country of high-IQ risk takers ... people who start new companies, and new businesses, and create new medical and new engineering breakthroughs," he said. "Trump basically has put out a sign in our front yard that says, 'Get off my lawn.'
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Release time：2018-12-19 00:00 reading：2590 Continue reading>>
Imec and CEA-Leti join forces on Artificial Intelligence and Quantum Computing
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Imec and CEA-Leti join forces on Artificial Intelligence and Quantum Computing

The Belgian research centre imec and the French research institute CEA-Leti, two leading research and innovation hubs in nanotechnologies for industry, have signed a memorandum of understanding (MoU) that lays the foundation of a strategic partnership in the domains of Artificial Intelligence and quantum computing.The joint efforts of imec and CEA-LETI underline Europe’s ambition to take a leading role in the development of these technologies and this increased collaboration will focus on developing, testing and experimenting neuromorphic and quantum computing – and should result in the delivery of a digital hardware computing toolbox that can be used by European industry partners to innovate in a wide variety of application domains – from personalised healthcare and smart mobility to the new manufacturing industry and smart energy sectors.Edge Artificial Intelligence (eAI) commonly refers to computer systems that display intelligent behavior locally on the hardware devices (e.g chips). They analyse their environment and take the required actions to achieve specific goals.Edge AI is poised to become a key driver of economic development. And, even more importantly perhaps, it holds the promise of solving many societal challenges – from treating diseases that cannot yet be cured today, to minimising the environmental impact of farming.Decentralisation from the cloud to the edge is a key challenge of AI technologies applied to large heterogeneous systems. This requires innovation in the components industry with powerful, energy-guzzling processors.“The ability to develop technologies such as AI and quantum computing – and put them into industrial use across a wide spectrum of applications – is one of Europe’s major challenges. Both quantum and neuromorphic computing (to enable artificial intelligence) are very promising areas of innovation, as they hold a huge industrialisation potential,” said Luc Van den hove, president and CEO of imec.“A stronger collaboration in these domains between imec and CEA-Leti, two of Europe’s leading research centers, will undoubtedly help to speed up the technologies’ development time: it will provide us with the critical mass that is required to create more – and faster – impact, and will result in plenty of new business opportunities for our European industry partners.”“Two European microelectronics pioneers today are joining forces to raise the game in both high-performance computing and trusted AI at the edge, and ultimately to fuel European industry success through innovations in aeronautics, defence, automobiles, Industry 4.0 and health care,” said Emmanuel Sabonnadière, Leti CEO. “This collaboration with imec following earlier innovation-collaboration agreements with the Fraunhofer Group for Microelectronics of the Fraunhofer-Gesellschaft, the largest organization for applied research, will focus all three institutes to the task of keeping Europe at the forefront of new digital hardware for AI, HPC and Cyber-security applications.”Imec and CEA-Leti are inviting partners from industry as well as academia to join them and benefit from access to the research centers’ state-of-the-art technology with proven reproducibility – enabling a much higher degree of device complexity, reproducibility and material perfection while sharing the costs of precompetitive research.
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Release time：2018-11-21 00:00 reading：1067 Continue reading>>
APeJ Spending on Cognitive and Artificial Intelligence to Reach $5.0 Billion in 2021
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APeJ Spending on Cognitive and Artificial Intelligence to Reach $5.0 Billion in 2021

　　The latest update of the IDC Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide for Asia Pacific (excluding Japan ) expects cognitive and artificial intelligence spending to reach $1.0 billion in 2018, registering an annual increase of 94% over 2016, mainly led by software and services related technologies. IDC provides a detailed outlook at the Cognitive Artificial Intelligence spending based on technologies and use cases. IDC further predicts, Cognitive and AI spending will grow extensively and reach $5.0 billion in 2021, achieving a five-year compound annual growth rate (CAGR) of 69.8% over the forecast period (2016-21).　　“Enterprises across are showing high Interest towards AI/ Cognitive system in APeJ with a decent adoption rate,” said Ashutosh Bisht, Research Manager at IDC Asia Pacific. “Automated Customer Service Agents and Intelligent Processing Automation are implemented by all the industries with a varied degree of penetration. AI/Cognitive system is one of the foundations of a digital transformation initiative and around 70% of enterprises will use AI Services by 2021,” Bisht added.　　Banking industry is a major feeder market in terms of cognitive/AI spending. This industry will add around $140.7 million in 2018 backed by different use cases including fraud analysis and investigation, IT automation, automated customer service agents and program advisors and recommendation systems. Retail is the second leading industry and will invest around $112.7 million this year on a range of AI use cases which includes expert shopping advisors & product recommendations, automated customer service agents, merchandising for omni channel operations and supply and logistics. Healthcare provider industry placing at third position allocates most of its $87.6 million investments to its diagnosis and treatment systems.　　Automated customer service agents, sales process recommendation and automation, and digital assistants for enterprise knowledge workers are the three major use cases with 11.5%, 9.1% and 9.0% respectively share to the overall cognitive/AI use cases spending in 2018. Whilst, over the forecast period (2017-21), expert shopping advisors & product recommendations, automated claims processing and intelligent processing automation use cases will register exceptional increase with five-year compound annual growth rate of 91.2%, 88.4% and 85% respectively.　　Majority spending on cognitive and AI technology will go to software with 50.7% share of the overall spending in 2018, and the trend is likely to observe a linear growth with a five-year CAGR (2016-21) of 72.3% and reach $2.3 billion by 2021. The category is dominated by Cognitive Applications, which will deliver more than 82.6% of all cognitive and AI spending. While, services are the second leading technology group with $421.0 million, preceded by hardware technology group (servers and storage) with $108.4 million spending in 2018. Throughout the forecast period (2016-21), spending on services-based technology group will grow at faster pace at a five-year CAGR 75.3%, while hardware will record a sluggish growth at 38.5% CAGR respectively.　　Jessie Cai, Senior Research Manager at IDC Asia Pacific said, “The cognitive/AI solution market is fast growing in APeJ and the demand within enterprises will mostly rise due to increased pressure to reduce operational cost. Organizations need to take note that the availability, quality and continuity of scenario-specific training data should be reviewed to best utilize cognitive/AI technologies.”　　China is a top market in Asia Pacific (excluding Japan) with greater share of 65.5% to the overall spending. Automated customer service agents and sales process recommendation and automation are the leading use cases in China, which represents 25.6% share with the ongoing popularity of AI, chatbots and automated, self-service technologies. In the near term, advancement in technology will lead to maximum usage of robots as well as enhanced automated customer service agents which will deliver cognitively-enabled process and industry applications.
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Release time：2018-03-28 00:00 reading：1149 Continue reading>>
Worldwide Spending on Cognitive and Artificial Intelligence Systems Will Grow to $19.1 Billion in 2018
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Worldwide Spending on Cognitive and Artificial Intelligence Systems Will Grow to $19.1 Billion in 2018

　　Worldwide spending on cognitive and artificial intelligence (AI) systems will reach $19.1 billion in 2018, an increase of 54.2% over the amount spent in 2017. With industries investing aggressively in projects that utilize cognitive/AI software capabilities, the International Data Corporation (IDC) Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide forecasts cognitive and AI spending will grow to $52.2 billion in 2021 and achieve a compound annual growth rate (CAGR) of 46.2% over the 2016-2021 forecast period.　　"Interest and awareness of AI is at a fever pitch. Every industry and every organization should be evaluating AI to see how it will affect their business processes and go-to-market efficiencies," said David Schubmehl, research director, Cognitive/Artificial Intelligence Systems at IDC. "IDC has estimated that by 2019, 40% of digital transformation initiatives will use AI services and by 2021, 75% of enterprise applications will use AI. From predictions, recommendations, and advice to automated customer service agents and intelligent process automation, AI is changing the face of how we interact with computer systems."　　Retail will overtake banking in 2018 to become the industry leader in terms of cognitive/AI spending. Retail firms will invest $3.4 billion this year on a range of AI use cases, including automated customer service agents, expert shopping advisors and product recommendations, and merchandising for omni channel operations. Much of the $3.3 billion spent by the banking industry will go toward automated threat intelligence and prevention systems, fraud analysis and investigation, and program advisors and recommendation systems. Discrete manufacturing will be the third largest industry for AI spending with $2.0 billion going toward a range of use cases including automated preventative maintenance and quality management investigation and recommendation systems. The fourth largest industry, healthcare providers, will allocate most of its $1.7 billion investment to diagnosis and treatment systems.　　"Enterprise digital transformation strategies are increasingly including multiple cognitive/artificial intelligence use cases," saidMarianne Daquila, research manager, Customer Insights & Analysis at IDC. "Business transformation is occurring across all industries as successful companies embrace the array and potential impact of these solutions. Automated customer service agents, increased public safety, preventative maintenance, reduction of fraud, and improved healthcare diagnosis are just the tip of the iceberg driving spend today. With double-digit year-over-year spending growth forecast, IDC expects to see an increase in general use cases, as well as a refinement of industry-specific use cases."　　The cognitive/AI use cases that will see the largest spending totals in 2018 are: automated customer service agents ($2.4 billion) with significant investments from the retail and telecommunications industries; automated threat intelligence and prevention systems ($1.5 billion) with the banking, utilities, and telecommunications industries as the leading industries; and sales process recommendation and automation ($1.45 billion) spending led by the retail and media industries. Three other use cases will be close behind in terms of global spending in 2018: automated preventive maintenance; diagnosis and treatment systems; and fraud analysis and investigation. The use cases that will see the fastest spending growth over the 2016-2021 forecast period are: public safety and emergency response (75.4% CAGR), pharmaceutical research and discovery (70.5% CAGR), and expert shopping advisors and product recommendations (67.3% CAGR).　　A little more than half of all cognitive/AI spending throughout the forecast will go toward cognitive software. The largest software category is cognitive applications, which includes cognitively-enabled process and industry applications that automatically learn, discover, and make recommendations or predictions. The other software category is cognitive platforms, which facilitate the development of intelligent, advisory, and cognitively enabled applications. Industries will also invest in IT services to help with the development and implementation of their cognitive/AI systems and business services such as consulting and horizontal business process outsourcing related to these systems. The smallest category of technology spending will be the hardware (servers and storage) needed to support the systems.　　On a geographic basis, the United States will deliver more than three quarters of all spending on cognitive/AI systems in 2018, led by the retail and banking industries. Western Europe will be the second largest region in 2018, led by retail, discrete manufacturing and banking. The strongest spending growth over the five-year forecast will be in Japan (73.5% CAGR) and Asia/Pacific (excluding Japan and China) (72.9% CAGR). China will also experience strong spending growth throughout the forecast (68.2% CAGR).　　"The latest iteration of the Cognitive/AI Spending Guide is a roadmap for the journey of organizational digital transformation through the use of AI, deep learning, and machine learning," added Schubmehl. "Organizations should be evaluating and starting to use AI throughout their systems and the Cognitive/AI Spending Guide is an indispensable resource in that effort."　　The Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide sizes spending for technologies that analyze, organize, access, and provide advisory services based on a range of unstructured information. The spending guide quantifies the cognitive computing opportunity by providing data for more than 20 use cases across 16 industries in eight regions. Data is also available for the related hardware, software, and services categories. Unlike any other research in the industry, the detailed segmentation and timely, global data is designed to help suppliers targeting the market to identify market opportunities and execute an effective strategy.
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Release time：2018-03-23 00:00 reading：1155 Continue reading>>
Intel Banks on Artificial Intelligence
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Intel Banks on Artificial Intelligence

　　Last year, Intel Corp. acquired neural-network hardware maker Nervana and built Nervana’s chip, integrating it with Intel’s own on-processor deep-learning and artificial-intelligence (AI) capabilities. This month, Intel Capital invested in AI startups CognitiveScale, Aeye Inc., and Element AI. At the ISC High Performance conferencethis week. Intel fellow Pradeep Dubey outlined the big picture for Intel’s growing AI portfolio.　　Intel is investing in AI startups, acquiring others, and blending the mix with its own AI expertise to ensure a leadership position in machine learning, deep learning, and brainlike neural networks based on its AI hardware and software. The company is aiming at all applicable industries, from drug screening with the Xeon Phi to software-defined visualization with its graphics hardware, Dubey said. Intel is also re-architecting its Xeon family for AI by including Altera’s field-programmable gate arrays on chip, he said.　　CognitiveScale’s augmented intelligence　　The bottom line on Intel’s investment in CognitiveScale is to tap the latter’s expertise, backed by more than 100 patents, on what the startup calls the first industrial-grade “augmented intelligence” software. CognitiveScale defines augmented intelligence as a model of cognition that allows computers to replicate human mental abilities. The goal of its software is to augment human memory, perception, anticipation, problem-solving, and decision-making.　　The cognitive software’s deep-learning capabilities are “always on,” allowing it to improve continually by learning from its past experiences of what worked and what did not in six iterative steps: understanding, using a semantic engine that can derive meaning from data and user interactions; interpretation, by representing semantic meaning through both deterministic and probabilistic knowledge graphs; reasoning, using domain-optimized contexts that personalize advice; learning continuously in real-time by comparing historical data with current user interactions; assurance, by maintaining compliance with humanlike principles of responsible risk management; and repeating the process.　　Element AI’s new world　　Perhaps the most enigmatic of the AI startups in which Intel Capital has invested is Element AI, which claims to be conjuring an “AI-First World” that “elevates collective wisdom.” The year-old startup hasn’t detailed its techniques but says it is amalgamating knowledge from entrepreneurs, technology leaders, and academia. The aim, according to Element AI, is to translate the world’s most important AI research into “transformative business applications” that will be personalized for the needs of particular companies. Element AI has coined the term called AI-as-a-Service (AIaaS) to describe its technology, which it plans to keep in-house.　　AEye’s vision　　AEye, on the other hand, develops vision algorithms for vehicles, plus the hardware and software to execute them optimally. Its patented approach emulates human eyes and the brain’s visual cortex to make autonomous vehicles visually “smart.” Using solid-state LiDAR scanners, AEye claims to have achieved a variety of breakthroughs in intelligent sensing and perception technology.
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Release time：2017-06-26 00:00 reading：1240 Continue reading>>

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