AI News, China may be AI leader by next decade artificial intelligence

Capitalizing on the promise of artificial intelligence Perspectives on AI adoption from around the world

Artificial intelligence has evolved from an esoteric research topic—with its origins six decades ago in corporate and academic computer science labs—into a collection of powerful technologies with mainstream business promise and applicability.

Many foresee AI helping to spur enormous productivity gains over the next decade, making it essential to the competitiveness of national economies.4 Some researchers even believe that AI is poised to become a “general-purpose technology”—one of only a couple dozen inventions in human history (including steam engines and the internet) to have pervasive effects across industries, spark complementary innovations, affect economies, and actually change societies.5 Technology giants with global reach are declaring “AI-first” ambitions and using AI innovations to reduce costs, increase productivity, and fuel new products and services.

And augmenting and amplifying human intelligence is likely to be only the beginning: According to Deloitte Consulting’s AI-fueled organizations: Reaching AI’s full potential in the enterprise, AI is progressing toward autonomous intelligence, in which processes are digitized and automated to a level where machines and systems can act directly upon the intelligence derived from them, without human involvement.8 Remarkably, a majority of early adopters within each country believe that AI will substantially transform their business within the next three years.

At the national level, Canada is making efforts to boost the nation’s AI prowess: In 2017, the government initiated its C$125million Pan-Canadian Artificial Intelligence Strategy to help drive research, talent development, and innovation.11 Canada is home to world-class AI research institutes and thriving AI startups in cities such as Montreal and Toronto.12 More broadly, though, at the company level, early AI adopters display a lack of urgency: Deloitte’s global study found that only 5 percent of AI adopters in Canada rate AI as “critically important” to their business today, and 27 percent expect it will be in two years—the lowest level among countries studied.13 Concerns around AI risks may be putting a damper on leaders’ efforts;

Boldly declaring China’s ambition to become the world’s leading AI innovator by 2030, the Chinese government has published a national AI strategy and announced plans to invest tens of billions of dollars in AI research and development.15 In 2017, nearly half of global AI venture funding went to Chinese AI startups, outpacing US startups for the first time.16 China reportedly has the world’s second-highest number of AI companies, nipping at the heels of the United States.17 According to the Deloitte global AI study, 54 percent of AI early adopters in China consider AI to be “very” or “critically” important to their business success, and that is expected to rise to 85 percent in two years—the highest level across countries studied.

They are also more likely to believe AI is helping them open a sizable edge over their competition (55 percent, versus 37 percent globally).18 China faces speed bumps along its journey to AI leadership: As Deloitte’s 2019 TMT Prediction China inside: Chinese semiconductors will power artificial intelligence explains, China is the world’s leading consumer of semiconductors, but its domestic manufacturers can meet only a small portion of the nation’s demand.19 Amid uncertainty brought on by international tension and worry about supply chain interruptions—and the increasing demand for specialized chips to run AI algorithms—China is making development of its own chip industry a strategic priority.20 To help increase technological self-reliance and close the gap between Chinese manufacturers and global chip leaders, the Chinese government has established a state-backed semiconductor-focused fund, the “Big Fund,” which reportedly raised US$29 billion in its second financing round in 2018, following an initial US$21.8 billion round in 2014.21 Because chip industry development is a complex, deliberate process, some analysts caution that China’s returns on AI investment may be lower and slower in the future.22 Acting decisively on AI now, as some countries and early-adopter companies are, could be critical for future competitiveness.

A report from Deloitte Germany, Cognitive artificial intelligence: The invisible invasion of the media business, explains how AI technologies can themselves be used to combat textual “fake news” and violent or offensive images and videos faster and better than humans can.27 Unfortunately, as Deepfakes and AI: Questioning artificial intelligence ethics and the dangers of AI explains, the power of AI can also be misused to create highly realistic fake images, audio clips, and videos—for example, convincingly manipulating authentic video to “put new words in someone’s mouth.”28 Identifying deepfakes is currently difficult for both humans and AI, and although detection methods continue to improve, some AI researchers admit they’re currently “outgunned” in the battle.29 With the potential for deepfakes to affect elections, national security, financial markets, and even international relations, the stakes are enormous.

Because of AI’s potential to affect billions of people globally, the authors advocate for a global AI ethics framework: While acknowledging the complexity of developing a code of ethics that’s accepted globally, they believe responsible AI development and deployment will require an international regulatory model that smartly secures AI technologies’ benefits for societies and economies.32 Finally, AI ethics: A new imperative for businesses, boards and C-suites, a report from the Deloitte Risk &

However, the abundance of data in insurance holds great promise for insurers to use AI as a competitive differentiator, and the authors provide an extensive list of potential future use cases for AI technologies across the insurance value chain.34 The new physics of financial services: How artificial intelligence is transforming the financial ecosystem, based on more than 200 interviews with global experts, describes the great upheaval that AI is causing in that industry—affecting operating models, disrupting competitive dynamics and strategies, and raising public policy issues.

According to the authors’ analysis, the US federal government could free up hundreds of millions of working hours annually by automating public sector tasks.36 Finally, Intelligent IoT: Bringing the power of AI to the Internet of Things explores the growing importance of AI to the Internet of Things (IoT), which has applicability in a wide range of industries, including manufacturing, transportation, automotive, utilities, government (“smart cities” initiatives), and even health care.37 Machine learning, an AI technology, is being used to identify patterns and aberrations in the data generated by IoT sensors and devices, and can make predictions faster than was previously possible.

The US is in danger of losing its global leadership in AI

Congress asked us to serve on a bipartisan commission of tech leaders, scientists, and national security professionals to explore the relationship between artificial intelligence (AI) and national security.

Our work is not complete, but our initial assessment is worth sharing now: in the next decade, the United States is in danger of losing its global leadership in AI and its innovation edge.

Computing power, large data sets, and new methods have led us to an inflection point where AI and its sub-disciplines (including machine vision, machine learning, natural language understanding, and robotics) will transform the world.

The Chinese government is amassing the personal data of its people, using facial recognition software to stifle dissent and repress minorities, and exporting its surveillance technology abroad.

After more than 150 discussions with AI experts ranging from skeptics to evangelists, we have identified several propositions to help the United States and its allies fashion an AI future more consistent with our shared interests and ideals.

That requires serious long-term federal investments in basic research and niche security applications that the commercial sector may not pursue.

AI will sort and integrate videos and other information streams and will help discern patterns and pick out threats with greater accuracy than a human.

The tech industry generates many of the major breakthroughs, and companies are on the frontlines of defending against cyber threats and malicious uses of AI.

The government, for its part, should articulate clear standards and policies for responsible use, rebuild trust through greater transparency, and offer a vision of shared purpose.

Some argue that only a “Sputnik” moment will wake the American people and government to act with purpose, just as the 1957 Soviet launch of a satellite catalyzed new educational and technological investments.

We are in a rare moment when challenge, urgency, and consensus may just align to generate the energy we need to extend our AI leadership and build a better future.

Eric Schmidt is chairman of the National Security Commission on Artificial Intelligence (NSCAI), an independent federal commission created in 2018 to recommend steps to advance AI’s development and its national security and defense implications.

Artificial Intelligence panel convenes at UAlbany: U.S. lags behind China

Few terms these days hold connotations as paradoxical as “artificial intelligence” and “automation” do — except maybe “electricity” and “industrial revolution” before them.  Ask anyone to conjure up a distant future where artificial intelligence has developed past the point of standard human capacities and you’re bound to presented with either a twinkling utopia, where automation has released the shackles of the working class and accelerates pursuits of culture and science;

“Andrew Yang,” continued Fahy, “put out an op-ed about a week ago, where he cited the Council of Economic Advisors, that claimed 83-percent of jobs now earning less than $20-per-hour will have substantial parts of their jobs automated.” Her point was to illustrate that popular discussion around automation and AI often contains points of alarm that turn people away from what she considers an opportunity for progress.

“But government often struggles to keep pace with anything technological, so that’s why we have such an extraordinary panel here with us.” The panel consisted of seven experts across a range of disciplines, and Congressman Paul Tonko, who was co-hosting and moderating the forum alongside Fahy.  Despite the national framing, the relevance of the panel was focused on the Capital District, which is nestled within “Tech Valley” — a region of high technological investment that stretches from top to bottom along New York State’s eastern border.   The Capital District is home to the University of Albany, which offers undergraduate and graduate programs in computer science;

“AI is going to be very useful in tailoring forecasts,” Thorncroft said.  And aside from making impending disasters known, better forecasts allow for more efficient harvesting of wind and solar energies, which Thorncroft termed “intermittent energies” that need to be accurately predicted in order to replace fossil fuels.  In a vice versa, Shahedipour-Sandvik explained that fundamental to the “energy-hungry” AI field is the construction of energy-efficient hardware.

“Data is exploding,” said McGuinness, referring to the fodder of AI systems, “but there aren’t enough data scientists.”  “I think the biggest thing we have to do is look at education in the future,” said Malatras, who suggested that exposing kids to coding programs and teaching educational resilience would be imperative in keeping the U.S. ahead of countries like China, which already incorporate AI-based learning in their schools.

“We keep falling for phishing,” he said, referencing a rudimentary and easy-to-avoid hacking technique that attempts to gain access to users’ private information by posing as a trustworthy source or company.  “We need to invest — now — in very focused areas of [AI],” Goel said.  After the opening statements, Tonko posed his first question to the panelists: “Is there a way to take inventory of tasks that will be displaced by automation?” McGuinness said it’s less about identifying specific jobs and tasks and more about figuring out the properties of those jobs and tasks.

Artificial Intelligence in India – Opportunities, Risks, and Future Potential

Given the Indian government’s recent focus on developing a plan for artificial intelligence, we decided to apply our strengths (deep analysis of AI applications and implications) to determine (a) the state of AI innovation in India, and (b) strategic insights to help India survive and thrive in a global market with the help of AI initiatives.

According to Komal Sharma Talwar, Co-founder XLPAT Labs and member of India’s AI Task Force: “I think the government has realized that we need to have a formal policy in place so that there’s a mission statement from them as to how AI should evolve in the country so it’s beneficial at large for the country.” Indeed it’s comments like Komal’s that made us realize that we should aid in determining a strategic direction for artificial intelligence development in India –

In our research and interviews, we saw consensus (from executives, non-profits, and researchers alike) that healthcare and agriculture would be among the most important sectors of focus in order to improve living conditions for India’s citizens.

is currently engaged in the following public sector initiatives: “The current areas of focus for AI applications in India are majorly focused in 3 areas: With the government’s growing interest around AI applications in India, Deepak Garg the Director at NVIDIA-Bennett Center of Research in Artificial Intelligence (and Director believes that there has been a significant growth in interest levels around AI across all industry sectors in India.

He explains that although AI attention is considerably smaller in India than in China or the USA, the increased AI interest has manifested itself in the following three ways: “1) Industries have started working to skill their manpower to enable themselves to compete with other global players 2) Educational institutions have started working on their curricula to include courses on machine learning and other relevant areas 3) Individuals and professionals have started acquiring these skills and are comfortable investing in upgrading their own skills.” Despite the initial enthusiasm for AI, there were also a few opinions from experts about a sense of unfulfilled potential and that the country could be doing far more to adopt and integrate AI technologies.

number of our interviewees mentioned the prevalence of copy-catting business models in India (taking a famous or successful business model in the USA or Europe and reconstructing it in India), as opposed to the invention of entirely new business models.

roughly 18% of the Indian GDP) have a significant potential opportunity to cater to the coming demand for data cleaning and human-augmented AI training (data labeling, search engine training, content moderation, etc).

Historically, the slower adoption of IT services by domestic Indian companies (in some cases by even by a period of around 10 years) as compared to global competitors was an indicator of the unfulfilled potential according to some experts we spoke to.

“The Indian foundation of IT services and business process outsourcing makes me believe that such AI training jobs will be even more lucrative for India than elsewhere in the future.” During the interview with him, Aakrit explained his stance with an example about the possibility that Indian BPO services providers could potentially be attractive in terms of skills and cost for tasks (which he believes will for a long time remain a manual effort) like cleaning and tagging of data in the near future.

We believe India has a major advantage over other countries in terms of talent, a vibrant startup ecosystem, strong IT services and an offshoring industry to harness the power of AI.” Kiran Rama, the Director of Data Sciences at the VMware Center of Excellence (CoE) in Bangalore also seems to agree that the cost-competitive talent in India will be an opportunity for companies looking to open offices in India: “There seems to be a lot of opportunity for companies that are setting u shop in India.

I also think there Indians are starting to contribute to the advancement of machine learning libraries and algorithms.” Subramanian Mani, who heads the analytics wing at, an online Indian grocery e-commerce firm, reiterates the idea that the IT services background in India is an advantage.

He believes that the major difference between the software and AI waves is that although India was slow to adopt software service as compared to America, this time around with the AI wave, adoption will be much faster and only slightly behind the leading countries.

Folks in India realized that they’ve been able to scale software and I think AI / ML is an extension of software development.” While software was often taught through books and in classrooms exclusively, many of the latest artificial intelligence approaches are available to learn online –

Going in, we knew that one of the key advantages for India would, in fact, be the very IT and ITeS sectors which will make it easy for Indian tech providers to transition into AI services, given that well-developed ecosystems have evolved over the past 25 years in cities like Bangalore and Hyderabad.

The state government is interested in planning and grooming for startups in this space as witnessed by the launch of the Center for Excellence (CoE) in AI setup by the GOI and NASSCOM in Bangalore.” While the advantage from the existing Indian IT sector may have been more intuitive, Madhusudan Shekar, Principal Technology Evangelist at Amazon AWS explains through an example how India’s diversity and scale (generally considered a challenge) can be an opportunity to make the best out of a tough situation: “In India, people speak over 40+ formal languages in about 800+ dialects.

To further explain,  According to a report by the Telecom Regulatory Authority of India (TRAI) the total number of internet subscribers in the country as a percentage of the overall population increased by 12.01% from December 2013 to reach 267.39 million in December 2014.

Along these lines, Mayank Kapur Co-founder of Gramener cites the increased level of data collection and the scale to which it could potentially grow as an opportunity for India in public sector AI applications: “In the public sector, we have an advantage of scale the amount of data that can potentially be gathered is huge.

Juergen Hase the CEO of Unlimit- A Reliance Group Company, one of India’s largest private sector companies, expressed his thoughts during our research: “The direct switch to mobile platforms in India means that there are no legacy systems to deal with and new technologies can be developed from scratch.” As shown in the figure to the right, an overwhelming majority of India’s Internet subscribers gain access through mobile wireless networks.

He thinks that the two underlying factors here are larger salaries lie in the corporate sector, which is potentially creating a dearth of mentors for the next generation of software developers looking to transition into AI and the availability of data.

Industry-university partnerships where students can work with real world data science applications and reskilling of existing workforces (example: getting software engineers to look at statistics or vice versa) are just beginning to take shape in India (starting with the unicorns).” The cultural factors in India play a role in talent development here as explained by Nimilita Chatterjee SVP, Data and Analytics at Equifax: “I see issues in AI talent in India are at 3 levels: The issues that Nimilita addresses above aren’t all that different from what we see in the United States (indeed in Silicon Valley) on a daily basis.

Just being cheaper than a Western idea is not true innovation… that’s not ALL that we should be thinking about.” The following points became evident through our interviews about India’s AI risks and weaknesses: In light of NITI Aayog’s recent report, and in light of our research on AI in India (and our understanding of AI’s economic possibilities in various tech ecosystems), we were determined to contribute to the national conversation about AI in India.

With the AI wave, there is the potential to catch up immediately thanks to substantial and continuing growth in internet connectivity, and India’s swollen population of young engineers could hypothetically leap directly to the cutting edge of programming, development, and data science.

If India can marshall this next generation of the tech-savvy workforce people into the right skills, they can form a huge base of just the kind of engineers and data scientists experts that the world will need most in the years ahead.

They could stay at the bottom of the value chain, basically being relegated to tagging images, combing through data for edge cases, training algorithms, etc (we might name this scenario “The nation of mechanical turks”).

being a cheaper version of some Western business model), and become the kind of firms that the rest of the world references as “leading” and “premier,” not merely “less expensive.” The services sector is where much of India’s current and future growth is likely to come from (, with IT services and business process outsourcing (BPO) services employing millions of Indians.

India’s real opportunity is doing AI for social good as we have historically always been a technology test bed for social efforts and we possess the technological know-how to get it done reasonably well here.” We certainly hope that India can make the most of artificial intelligence –

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