Any AI Enthusiasts here? I just downloaded Caffe and H20 Learning these platforms, to design a AI for research purpose.
Artificial Intelligence in India : News & Disscussion
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India, Japan To Use Artificial Intelligence In Defence Sector
Indian and Japan are bringing in artificial intelligence into their arsenal as a measure of its counter-intelligent defense system. Kentauro Sonoura, minister of foreign affairs for Japan, said in a press release that Japan aims to collaborate with India to develop unmanned ground vehicles (UGV) and robotics. The move is also aimed at strengthening the geo-political ties between the two countries.
Although, there was initial rebuke between India and Japan, it seems to have been eased over the years, as to mainly counter China‘s strategic influence over India.
Sonoura emphasised on the fact that Japan planned to achieve cordial relations with all the South-Asian countries including Pakistan, Myanmar and Bangladesh in 2018. He also said that Japan wanted to promote a “free and open Indo-Pacific” policy, highlighting the steps taken by them to curb terrorism through initiating a dialogue with Pakistan.
Speaking to a national newspaper, Sonoura said, “”We need to share the importance of rule of law and freedom of navigation among related countries. The next step is infrastructure development based on global standards, so that connectivity among countries is increased. The third step would be maritime law enforcement and disaster management that would ensure the stability and prosperity in the Indo-Pacific region. Therefore, we would like to connect and combine our Indo-Pacific strategy and India’s Act East policy as a one big picture. That’s the synergy we seek.”
This makes India enter into a new foray of technological innovations with Japan with its friendly relations going strong with the recent developments. In fact, Japan Prime Minister Shinzo Abe, had gone as far as to say that India was a part of its support towards infrastructural development and growth in the IT sector.
India, on the other hand, has been on the rise with developments in its Make In India policy. This agreement will certainly strengthen its outlook towards creating more jobs in the country. Furthermore, the economic gain achieved by India will reinforce its status as an aggressive developing country. The move to enter AI and robotics sector might seem like a good idea for establishing a political and technological stability for the country.
Contrastingly, there has been criticism from the opposition parties in India for choosing foreign companies over homegrown organisations for high value projects.
Indian and Japan are bringing in artificial intelligence into their arsenal as a measure of its counter-intelligent defense system. Kentauro Sonoura, minister of foreign affairs for Japan, said in a press release that Japan aims to collaborate with India to develop unmanned ground vehicles (UGV) and robotics. The move is also aimed at strengthening the geo-political ties between the two countries.
Although, there was initial rebuke between India and Japan, it seems to have been eased over the years, as to mainly counter China‘s strategic influence over India.
Sonoura emphasised on the fact that Japan planned to achieve cordial relations with all the South-Asian countries including Pakistan, Myanmar and Bangladesh in 2018. He also said that Japan wanted to promote a “free and open Indo-Pacific” policy, highlighting the steps taken by them to curb terrorism through initiating a dialogue with Pakistan.
Speaking to a national newspaper, Sonoura said, “”We need to share the importance of rule of law and freedom of navigation among related countries. The next step is infrastructure development based on global standards, so that connectivity among countries is increased. The third step would be maritime law enforcement and disaster management that would ensure the stability and prosperity in the Indo-Pacific region. Therefore, we would like to connect and combine our Indo-Pacific strategy and India’s Act East policy as a one big picture. That’s the synergy we seek.”
This makes India enter into a new foray of technological innovations with Japan with its friendly relations going strong with the recent developments. In fact, Japan Prime Minister Shinzo Abe, had gone as far as to say that India was a part of its support towards infrastructural development and growth in the IT sector.
India, on the other hand, has been on the rise with developments in its Make In India policy. This agreement will certainly strengthen its outlook towards creating more jobs in the country. Furthermore, the economic gain achieved by India will reinforce its status as an aggressive developing country. The move to enter AI and robotics sector might seem like a good idea for establishing a political and technological stability for the country.
Contrastingly, there has been criticism from the opposition parties in India for choosing foreign companies over homegrown organisations for high value projects.
Report of Task Force on Artificial Intelligence
Report of Task Force on Artificial Intelligence | Department of Industrial Policy & Promotion | MoCI | GoI
Report of Task Force on Artificial Intelligence | Department of Industrial Policy & Promotion | MoCI | GoI
How India is carving out a niche for itself in the field of Artificial Intelligence
When 62-year-old computer scientist P Anandan started last September as CEO at the Wadhwani Institute of Artificial Intelligence (WIAI), he might have been apprehensive. He was signing up to work on AI in India after three decades at major global corporations and academia in the US and at home, including top teaching and research roles at Yale University, Adobe and Microsoft.
India isn’t exactly a hub for cutting-edge research in Artificial Intelligence (AI). Misconceptions abound about big data, machine learning, automation and other AI-related technologies in the context of job losses for humans. And unlike other major economies, India hadn’t yet spelled out its vision for a future with AI.
But when Anandan set out to work, he found support all around. In February, the Prime Minister inaugurated the institute. Maharashtra chief minister Devendra Fadnavis and NITI Aayog CEO Amitabh Kant were in attendance. Modi also invited Anandan to Delhi and met with him there.
“Right from the top, the government support has been fabulous. They have almost been like our working partner,” Anandan told ET Magazine. Anandan’s institute, funded by the entrepreneurs Romesh and Sunil Wadhwani, is among a string of emerging private, non-profit and government efforts to harness the power of AI to solve societal problems in India.
The focus is on areas such as agriculture, healthcare, education and infrastructure. There are also moves to channel global AI talent and resources to develop solutions that can benefit millions at the grassroot. And this month, India made its first steps in articulating what it wants to be in an AI-centric future.
A National Strategy
“Globally, no one is doing AI innovation for the social sector. India can lead here,” Anandan says. That’s indeed the overarching vision in the first major blueprint on AI that was released this month—a discussion paper from government think-tank NITI Aayog, titled National Strategy for Artificial Intelligence.
It pitches India as the AI “garage for the emerging and developing economies”. The focus will be on five key sectors— healthcare, agriculture, education, smart cities & infrastructure and smart mobility & transportation. The priorities are hard to argue with. India’s agriculture is notoriously inefficient, employing just under 50% of the population but contributing under 18% of the country’s gross domestic product.
In the US, for instance, less than 2% of the workforce is dependent on agriculture. Access to healthcare is poor—India’s life expectancy (68 in 2015) is among the lowest for BRICS nations, and so is its hospital beds per thousand people (0.9), a KPMG report said last year.
“AI is like the new electricity. The new factor of production. Like the industrial revolution, it will transform every sector. We want to exploit it to solve big socio-economic challenges that India faces,” said Amitabh Kant, CEO, NITI Aayog. This view of AI as a transformative force underpins the report as well.
While AI is commonly understood as a piece of esoteric high technology that could get too powerful for our own good, it’s really a suite of technologies like machine learning, pattern recognition, big data, neural networks and self improving algorithms, many of which have been around for a while and are now maturing.
What has changed in recent years in the promise of AI is the coming together of very advanced computing power with highly sophisticated algorithms and networks that collaborate to recognize patterns, discern meaning from vast sets of data and train themselves to get better at these tasks.
For the enthusiasts, the big question in AI might be when we will achieve machine super-intelligence, or Singularity, the point at which machine intelligence explodes to vastly surpass human intelligence. It is chillingly described as the last invention humans will make (not necessarily because it will destroy mankind, but because all the inventions thereon will be made by machines).
But for a country at India’s level of socio-economic development, the suite of AI technologies can be applied effectively to relatively prosaic concerns. And it’s already happening.
In Andhra Pradesh for instance, Microsoft is working with the state government to predict dropout rates in government schools. With granular knowledge of past outcomes across factors like gender, socio-economic background, academic performance, school infrastructure and teacher skills, the machine is able to predict with some margin of error, who among the current cohort are likely to drop out and when. This enables early intervention.
Microsoft and the International Crops Research Institute for the Semi-Arid Tropics have together developed a sowing app that uses AI technologies. It sends advisories to participating farmers on the optimal date of sowing. IBM and NITI Aayog have developed an AI-based crop yield prediction model. It’s able to offer real-time advisories to farmers on crop yield, pest outbreak, and so on.
Efforts are underway to make cancer screening and diagnosis far more accessible than it is currently, using AI technologies. Traffic, crowd management, avoiding of accidents, improvement of public facilities like parks and open spaces—are all problems with smart AI-based solutions.
Collaborative Efforts
Anandan of the Wadhwani Institute says collaboration between companies, government, non-profits and universities is key to effectively harnessing AI for India’s problems.
“The government and the NGOs do not have the capacity to tackle problems through technical innovations. We will be the connector that can help build public data ecosystems, develop solutions and help deliver at scale,” he says.
He is now helping Mumbai University rollout a master’s program in data sciences. Being a not-for-profit with an open innovation platform, close to 200 top AI scientists from universities such as MIT and Stanford have volunteered to collaborate to solve big societal problems.
The NITI Aayog report proposes an umbrella organisation to shape and implement India’s AI policies—from stitching global partnerships to picking specialised teams to pursue audacious moonshot projects. It identifies five focus areas (see box) and a two-tiered institutional structure — government-led CORE or Centre of Research Excellence to focus on core research and private sector-led ICTAI or International Centers of Transformational AI to focus on application-based AI research.
For AI to work, having vast amount of structured clean data is critical. To build data ecosystems, the report proposes a National AI Marketplace (NAIM) that will collect and annotate data and evolve deployable models. To tackle AI talent shortage, it suggests a slew of initiatives like reskilling workforce, modular certification courses and thrust on research with PhD fellowships.
The thrust of the report has been lauded by AI experts who are also familiar with India’s problems. “The report looks pretty comprehensive. I am impressed with what they have managed to put together,” says US-based scientist Subbarao Kambhampati, president, Association for the Advancement of Artificial Intelligence.
Akilur Rahman, chief technology officer at Swedish-Swiss tech giant ABB, says it tackles the topic well and in a timely manner. NVIDIA South Asia MD Vishal Dhuppar, who is passionate about AI, says the report’s thrust on public-private collaboration is the way to go. Prof V Kamakoti of IIT-Chennai, who authored a report on AI for the ministry of commerce and industry, said he found the Niti Aayog report to be “well-articulated and action oriented”.
However, sceptics abound. Many doubt government’s execution capabilities. The poor state of university research is a big worry. India lags far behind China and the US in the number of AI experts, researchers, patents filed, research published, AI startups and funding. They point out India neither has the private sector tech giants like Google and Facebook to give heft to its AI moves nor China’s financial might and state determination to make things happen.
To the naysayers, here’s what Kant has to say: “We are committed to having this strategy executed. Every major change faces hurdles and resistance. Change is the way to progress. The execution will be implemented using a METRO approach (Measurable, Time-bound, Real Outcomes).”
Gathering Momentum
With deep economic and security implications, the race for supremacy in AI is the space war of the digital age. All advanced nations are vying for supremacy, while some are focusing on niches. The US, with top research universities and Silicon Valley, is an obvious leader. China, with steely state determination, global linkages and deep resources, is an emerging challenger. Japan, the land of robots, is a leader in automation and related technologies. Russia, which features in the cyber-security nightmares of rival nations, is believed to be investing deeply in AI.
“Whoever leads the AI will lead the world, Vladimir Putin has declared unambiguously. The UK wants to focus on the ethical aspects of AI. UK is home to the influential Oxford philosopher Nick Bostrom, whose work and warnings on super-intelligence has helped bring AI into greater public knowledge.
“AI is a crucial tool to optimize business operations while for countries, it provides both commercial and potentially national security gains like enhanced cyber-security,” said Paul S Triolo, practice director (GeoCyber) at the Eurasia Group.
A gathering momentum on AI in India can now be observed at various levels.
This week, the ministry of external affairs held a closeddoor meeting of global AI experts to discuss how to attract Indian diaspora. Big Indian companies such as Bharti Airtel and Reliance Jio are setting up AI labs. Global corporations NVIDIA, Microsoft and Google have all set up labs in India that are advanced AI-linked work. Indian IT services giants such as Infosys and Wipro are belatedly investing in the space. IT industry body Nasscom is setting up Centre of Excellence (COE) in AI in Karnataka and Telangana with companies like IBM, Microsoft, NVIDIA, Intel and AWS, on the lines of its successful 10,000 Startups program.
There are startups that are joining the AI gold rush, too. SatSure Ltd, launched last year by former Goldman Sachs executive Amardeep Sibia, is one such. It builds AI applications using satellite images to provide real-time data on crop health, yield forecast etc. By some estimates, there are 300-plus startups in India developing or deploying AIrelated technologies.
In academia, Bennett University (backed by The Times of India Group, which publishes The Economic Times) is pitching itself as India’s AI-focused university. It recently organised leadingindia.ai, a conclave for AI-related startups. It’s also an ongoing initiative that aims to skill a million people in AI-related technologies in two years.
“We should not unduly worry about talent shortage. For most problems, 90% of the solution does not require AI expertise, says Kamakoti. State governments like Andhra Pradesh too are joining in.
“We want to build our own Centre for Excellence and groom AI specialists,” says Subbarao Ghanta, IT advisor to Andhra Pradesh chief minister Chandrababu Naidu.
It is in talks with Stanford University and the machine-learning expert Andrew NG to get its strategy in place. In three years, it plans to train 250,000 AI specialists. Extensive efforts are underway to collect data. For example, the state government plans to train 25,000 drone pilots in the next 18 months to collect village- and farm-level data for water level and crop cultivation.
“In AI, there is no insurmountable first mover advantage,” says Prof Kambhampati. In other words, it’s not too late yet for India on the AI playground.
How India is carving out a niche for itself in the field of Artificial Intelligence
When 62-year-old computer scientist P Anandan started last September as CEO at the Wadhwani Institute of Artificial Intelligence (WIAI), he might have been apprehensive. He was signing up to work on AI in India after three decades at major global corporations and academia in the US and at home, including top teaching and research roles at Yale University, Adobe and Microsoft.
India isn’t exactly a hub for cutting-edge research in Artificial Intelligence (AI). Misconceptions abound about big data, machine learning, automation and other AI-related technologies in the context of job losses for humans. And unlike other major economies, India hadn’t yet spelled out its vision for a future with AI.
But when Anandan set out to work, he found support all around. In February, the Prime Minister inaugurated the institute. Maharashtra chief minister Devendra Fadnavis and NITI Aayog CEO Amitabh Kant were in attendance. Modi also invited Anandan to Delhi and met with him there.
“Right from the top, the government support has been fabulous. They have almost been like our working partner,” Anandan told ET Magazine. Anandan’s institute, funded by the entrepreneurs Romesh and Sunil Wadhwani, is among a string of emerging private, non-profit and government efforts to harness the power of AI to solve societal problems in India.
The focus is on areas such as agriculture, healthcare, education and infrastructure. There are also moves to channel global AI talent and resources to develop solutions that can benefit millions at the grassroot. And this month, India made its first steps in articulating what it wants to be in an AI-centric future.
A National Strategy
“Globally, no one is doing AI innovation for the social sector. India can lead here,” Anandan says. That’s indeed the overarching vision in the first major blueprint on AI that was released this month—a discussion paper from government think-tank NITI Aayog, titled National Strategy for Artificial Intelligence.
It pitches India as the AI “garage for the emerging and developing economies”. The focus will be on five key sectors— healthcare, agriculture, education, smart cities & infrastructure and smart mobility & transportation. The priorities are hard to argue with. India’s agriculture is notoriously inefficient, employing just under 50% of the population but contributing under 18% of the country’s gross domestic product.
In the US, for instance, less than 2% of the workforce is dependent on agriculture. Access to healthcare is poor—India’s life expectancy (68 in 2015) is among the lowest for BRICS nations, and so is its hospital beds per thousand people (0.9), a KPMG report said last year.
“AI is like the new electricity. The new factor of production. Like the industrial revolution, it will transform every sector. We want to exploit it to solve big socio-economic challenges that India faces,” said Amitabh Kant, CEO, NITI Aayog. This view of AI as a transformative force underpins the report as well.
While AI is commonly understood as a piece of esoteric high technology that could get too powerful for our own good, it’s really a suite of technologies like machine learning, pattern recognition, big data, neural networks and self improving algorithms, many of which have been around for a while and are now maturing.
What has changed in recent years in the promise of AI is the coming together of very advanced computing power with highly sophisticated algorithms and networks that collaborate to recognize patterns, discern meaning from vast sets of data and train themselves to get better at these tasks.
For the enthusiasts, the big question in AI might be when we will achieve machine super-intelligence, or Singularity, the point at which machine intelligence explodes to vastly surpass human intelligence. It is chillingly described as the last invention humans will make (not necessarily because it will destroy mankind, but because all the inventions thereon will be made by machines).
But for a country at India’s level of socio-economic development, the suite of AI technologies can be applied effectively to relatively prosaic concerns. And it’s already happening.
In Andhra Pradesh for instance, Microsoft is working with the state government to predict dropout rates in government schools. With granular knowledge of past outcomes across factors like gender, socio-economic background, academic performance, school infrastructure and teacher skills, the machine is able to predict with some margin of error, who among the current cohort are likely to drop out and when. This enables early intervention.
Microsoft and the International Crops Research Institute for the Semi-Arid Tropics have together developed a sowing app that uses AI technologies. It sends advisories to participating farmers on the optimal date of sowing. IBM and NITI Aayog have developed an AI-based crop yield prediction model. It’s able to offer real-time advisories to farmers on crop yield, pest outbreak, and so on.
Efforts are underway to make cancer screening and diagnosis far more accessible than it is currently, using AI technologies. Traffic, crowd management, avoiding of accidents, improvement of public facilities like parks and open spaces—are all problems with smart AI-based solutions.
Collaborative Efforts
Anandan of the Wadhwani Institute says collaboration between companies, government, non-profits and universities is key to effectively harnessing AI for India’s problems.
“The government and the NGOs do not have the capacity to tackle problems through technical innovations. We will be the connector that can help build public data ecosystems, develop solutions and help deliver at scale,” he says.
He is now helping Mumbai University rollout a master’s program in data sciences. Being a not-for-profit with an open innovation platform, close to 200 top AI scientists from universities such as MIT and Stanford have volunteered to collaborate to solve big societal problems.
The NITI Aayog report proposes an umbrella organisation to shape and implement India’s AI policies—from stitching global partnerships to picking specialised teams to pursue audacious moonshot projects. It identifies five focus areas (see box) and a two-tiered institutional structure — government-led CORE or Centre of Research Excellence to focus on core research and private sector-led ICTAI or International Centers of Transformational AI to focus on application-based AI research.
For AI to work, having vast amount of structured clean data is critical. To build data ecosystems, the report proposes a National AI Marketplace (NAIM) that will collect and annotate data and evolve deployable models. To tackle AI talent shortage, it suggests a slew of initiatives like reskilling workforce, modular certification courses and thrust on research with PhD fellowships.
The thrust of the report has been lauded by AI experts who are also familiar with India’s problems. “The report looks pretty comprehensive. I am impressed with what they have managed to put together,” says US-based scientist Subbarao Kambhampati, president, Association for the Advancement of Artificial Intelligence.
Akilur Rahman, chief technology officer at Swedish-Swiss tech giant ABB, says it tackles the topic well and in a timely manner. NVIDIA South Asia MD Vishal Dhuppar, who is passionate about AI, says the report’s thrust on public-private collaboration is the way to go. Prof V Kamakoti of IIT-Chennai, who authored a report on AI for the ministry of commerce and industry, said he found the Niti Aayog report to be “well-articulated and action oriented”.
However, sceptics abound. Many doubt government’s execution capabilities. The poor state of university research is a big worry. India lags far behind China and the US in the number of AI experts, researchers, patents filed, research published, AI startups and funding. They point out India neither has the private sector tech giants like Google and Facebook to give heft to its AI moves nor China’s financial might and state determination to make things happen.
To the naysayers, here’s what Kant has to say: “We are committed to having this strategy executed. Every major change faces hurdles and resistance. Change is the way to progress. The execution will be implemented using a METRO approach (Measurable, Time-bound, Real Outcomes).”
Gathering Momentum
With deep economic and security implications, the race for supremacy in AI is the space war of the digital age. All advanced nations are vying for supremacy, while some are focusing on niches. The US, with top research universities and Silicon Valley, is an obvious leader. China, with steely state determination, global linkages and deep resources, is an emerging challenger. Japan, the land of robots, is a leader in automation and related technologies. Russia, which features in the cyber-security nightmares of rival nations, is believed to be investing deeply in AI.
“Whoever leads the AI will lead the world, Vladimir Putin has declared unambiguously. The UK wants to focus on the ethical aspects of AI. UK is home to the influential Oxford philosopher Nick Bostrom, whose work and warnings on super-intelligence has helped bring AI into greater public knowledge.
“AI is a crucial tool to optimize business operations while for countries, it provides both commercial and potentially national security gains like enhanced cyber-security,” said Paul S Triolo, practice director (GeoCyber) at the Eurasia Group.
A gathering momentum on AI in India can now be observed at various levels.
This week, the ministry of external affairs held a closeddoor meeting of global AI experts to discuss how to attract Indian diaspora. Big Indian companies such as Bharti Airtel and Reliance Jio are setting up AI labs. Global corporations NVIDIA, Microsoft and Google have all set up labs in India that are advanced AI-linked work. Indian IT services giants such as Infosys and Wipro are belatedly investing in the space. IT industry body Nasscom is setting up Centre of Excellence (COE) in AI in Karnataka and Telangana with companies like IBM, Microsoft, NVIDIA, Intel and AWS, on the lines of its successful 10,000 Startups program.
There are startups that are joining the AI gold rush, too. SatSure Ltd, launched last year by former Goldman Sachs executive Amardeep Sibia, is one such. It builds AI applications using satellite images to provide real-time data on crop health, yield forecast etc. By some estimates, there are 300-plus startups in India developing or deploying AIrelated technologies.
In academia, Bennett University (backed by The Times of India Group, which publishes The Economic Times) is pitching itself as India’s AI-focused university. It recently organised leadingindia.ai, a conclave for AI-related startups. It’s also an ongoing initiative that aims to skill a million people in AI-related technologies in two years.
“We should not unduly worry about talent shortage. For most problems, 90% of the solution does not require AI expertise, says Kamakoti. State governments like Andhra Pradesh too are joining in.
“We want to build our own Centre for Excellence and groom AI specialists,” says Subbarao Ghanta, IT advisor to Andhra Pradesh chief minister Chandrababu Naidu.
It is in talks with Stanford University and the machine-learning expert Andrew NG to get its strategy in place. In three years, it plans to train 250,000 AI specialists. Extensive efforts are underway to collect data. For example, the state government plans to train 25,000 drone pilots in the next 18 months to collect village- and farm-level data for water level and crop cultivation.
“In AI, there is no insurmountable first mover advantage,” says Prof Kambhampati. In other words, it’s not too late yet for India on the AI playground.
How India is carving out a niche for itself in the field of Artificial Intelligence
Indian AI Startup Funding 2018: Total Global Investment In India Touched USD$ 529.52 Million
Analytics India Magazine Startup Funding Report 2018 highlights the latest trends in funding in 2018. AIM conducted an independent study and tracked the funding of AI & Analytics startups over the last one year and looked at which domains attracted big ticket investments, deals by geography and which startups won the biggest war chest. This list does not include AR/VR or hardware focused startups in India. The data is only reflective of reports published in the last one year and doesn’t include any non-public information.
The startup landscape in India is being transformed by accelerating investment and deal activity around intelligent automation and artificial intelligence, machine learning and big data. In 2018, startups raised an all-time high capital, registering a 368% growth from 2017. In 2018, startups with operations in India and globally raised approximately USD$ 529.52 million in funding rounds and this data includes startups with investment at varying stages of development, from pre-seed to well-funded companies. California and India based Automation Anywhere bagged the biggest cheque of $300 million from SoftBank Vision Fund. As compared to 2017, where the startups received an aggregate investment of US$113 million, funding rose to a record 368% in 2018.
The data clearly indicates that startups that had AI as a core product or are developing narrow AI tech bagged the heaviest funding from leading VC firms and investors who are investing heavily in deep tech startups in automation, enterprise AI and big data. It also underscores much of the financing is happening in domain-specific breakthrough technologies, and not general-purpose AI tech.
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2018 also saw one of the biggest mega-rounds led by top-tier investor SoftBank Vision Fund for San Jose headquartered Automation Anywhere which secured a sizable $300 million investment from the Vision Fund in November 2018.
Key Highlights
Big ticket funding was led by US-Bangalore startups that included RPA player Automation Anywhere ($raised 300 million from Soft Bank Vision Fund), enterprise AI specialist Noodle.ai (raised $35 million from Dell Technologies Capital and TPG Growth), AI-based grid analytics provider AutoGrid which works on energy solutions (raised $32 million Series D from CLP, Innogy, Orsted and Tenaska. Meanwhile, energy analytics firm Bidgely secured $27 million in Series C (raised funding from $27 million from Georgian Partners). Healthtech startup SigTuple that has developed an AI-powered platform Manthana SigTuple (raised $19 million in series B funding round from Accel and IDG Ventures). Note: All the top 4 most-funded startups, excluding SigTuple are headquartered in California with engineering units in Bangalore.
2018 – AI showed promise with November recording highest deal volume
The year started on a mild note with $28 million deal volume in January. SoftBank Vision Fund’s deal in November was the highest ever funding seen in the year, taking the deal volume to $337 million in November. Earlier in 2018, June registered a high deal volume of $60.95 million followed by September, $46.55.
Technology Growth Across Sectors – Automation, AI, ML big winners
The biggest deals of 2018 show there is a lot of optimism around AI, automation, machine learning, big data and analytics. The trend is clearly towards AI-driven investing and this can also be seen from a domain point of view where narrow domains, such as energy and automation specific applications being the most funded. The new capital is not only driving the valuation of these companies but also proves that all the rumblings about AI are true.
Investment by Cities – Bangalore continues to be the hub
Bangalore has the biggest war chest with an aggregate of $113 million capital. This number doesn’t include the biggest funding round of all – San Jose headquartered Automation Anywhere’s $300 million funding. There is a wide gap between Bangalore and Chennai which received $35 million, followed by Gurgaon that grossed $29.5 million and Mumbai at $6 million while Delhi recorded a deal volume of $1.7 million. However, outside the major hubs, other cities that saw VC momentum was Coimbatore’s social media analytics platform Synctag which raised $307,600 and Chandigarh-based AgNext which received an undisclosed amount of funding.
Early Stage vs Late Stage funding
Even though the biggest deals were closed in late stage, early stage and seed stage funding surpassed late stage thanks to more deals, not higher amount. The boost in early stage is from higher number of deals, with Series A leading by 36.4% followed by 27.3% in seed stage investments. Series B saw 18.2% investment while late stage (Series C, D) recorded 4.5% each respectively.
Top Dealmakers 2018 – SoftBank’s Masa Leads The Way
SoftBank with its ambitious $100 billion Vision Fund led by Masayoshi Son and Rajeev Misra has disrupted the venture capital market with its staggering investments, allowing companies to stay private longer. In India, SoftBank has an impressive investment portfolio, backing the biggest consumer internet companies and this time too, it gave a major fillip to RPA giant Automation Anywhere by writing a $300 million cheque. Given Masa’s funding pattern, he always puts a safe distance between his competitors.
The second major investment, $35 million was by Dell Technologies venture investment arm and TPG Growth in Noodle.ai. Bain Capital Venture and early stage VC firm Hyde Park Venture Partners also invested $35 million in Four Kites. This was followed by consortium of Denmark’s Orsted, Hong Kong-based CLP, US energy company Tenaska and German energy company Innogy which made an investment of $32 million in AutoGrid. Meanwhile, Jungle Ventures and European Venture Capital firm Lakestar invested $29.5 million in AI low-code platform Engineer.ai.
Year-on-year comparison – 2018 grossed an all-time high funding
The last five years has seen the industry build on its analytics innovations and lay the foundation for AI. There has been a steady rise in investment from 2014 which clocked $75 million in investment, while 2015 saw a 70% growth in funding. 2016 saw $213 million being poured into startups while 2017 saw funding almost halved by $100 million. A key reason is that in 2016 companies were tinkering at the edges of AI, and 2017 it moved from PoC stage to production and now we are seeing full-fledged commercial applications. Also, one of the key takeaways of 2018 is that high-growth startups and companies that are fostering AI innovation are also proving it with their robust financial performance, a major reason why investors and VC firms are betting big on the high-growth companies.
Bottom funded startups of 2018
At the bottom of the stack are Bangalore-headquartered HR tech startup Skillate that raised $200k, AI-driven conversational platform Trilyo targeted at the hospitality sector, which raised $250k in 2018. These startups are followed by Tamil Nadu based social media analytics startup Synctag ($308k) while restaurant analytics company Spoonshot (DishQ) raised $400k in pre-seed funding followed by Bangalore-based Mate Labs that raised $550k in seed funding.
Indian AI Startup Funding 2018: Global Investment In India Touched USD$ 529.52 Million
Analytics India Magazine Startup Funding Report 2018 highlights the latest trends in funding in 2018. AIM conducted an independent study and tracked the funding of AI & Analytics startups over the last one year and looked at which domains attracted big ticket investments, deals by geography and which startups won the biggest war chest. This list does not include AR/VR or hardware focused startups in India. The data is only reflective of reports published in the last one year and doesn’t include any non-public information.
The startup landscape in India is being transformed by accelerating investment and deal activity around intelligent automation and artificial intelligence, machine learning and big data. In 2018, startups raised an all-time high capital, registering a 368% growth from 2017. In 2018, startups with operations in India and globally raised approximately USD$ 529.52 million in funding rounds and this data includes startups with investment at varying stages of development, from pre-seed to well-funded companies. California and India based Automation Anywhere bagged the biggest cheque of $300 million from SoftBank Vision Fund. As compared to 2017, where the startups received an aggregate investment of US$113 million, funding rose to a record 368% in 2018.
The data clearly indicates that startups that had AI as a core product or are developing narrow AI tech bagged the heaviest funding from leading VC firms and investors who are investing heavily in deep tech startups in automation, enterprise AI and big data. It also underscores much of the financing is happening in domain-specific breakthrough technologies, and not general-purpose AI tech.
Advertisement2018 also saw one of the biggest mega-rounds led by top-tier investor SoftBank Vision Fund for San Jose headquartered Automation Anywhere which secured a sizable $300 million investment from the Vision Fund in November 2018.
Key Highlights
- 2018 saw the biggest funding rounds of all, grossing USD$ 529.52 million, 20% less than the combined share of deal volume over the last four years — 2014-2017, where the total investment was USD $661 million.
- Compared to the drop in 2017, where funding was almost halved vis-a-vis 2016, 2018 saw a 368% increase with investment of USD$ 529.52 million in applied technology sector with AI, ML and Data Science being the major domain and sub-domains. This is a 4x increase as compared to last year’s numbers
- All the high-growth companies that attracted big ticket funding had AI as a core product or are applying AI, ML technologies to verticals like healthcare, finance, supply chain and energy
- Domain centricity was the key trend in 2018 with domain-specific applications such as data centre automation, energy efficiency and supply chain management receiving the highest capital infusion. This shows these are the domains that show maximum promise for VCs who see the potential in these commercial applications and believe it will turn into a viable business model
- Bangalore, the startup capital of India eclipsed other Indian cities by a staggering margin, grossing $133 in aggregate funding. India’s Silicon Valley was followed by Chennai at $35 million and Gurugram at $29.5 million. It is yet to be seen whether Bangalore, the hub of groundbreaking startups will be able to translate the capital into growth and customer acquisition
- Outside the traditional hubs, Chandigarh-based and IIT Kharagpur-incubated AgNext Technologies, agritech startup received an undisclosed amount of funding from Omnivore Partners
- Biggest dealmakers of 2018 are SoftBank Vision Fund (the biggest purse of all – $100 billion Vision Fund), Dell Technologies Capital, TPG Growth, Bain Capital Venture, Hyde Park Venture Partners and CLP Holdings Group, Innogy, Orsted, Tenaska followed by Jungle Ventures and Lakestar
- Venture investment at the early stage (Series A, Series B and seed funding) showed a sharp rise as compared to late stage financings (Series C and Series D)
Big ticket funding was led by US-Bangalore startups that included RPA player Automation Anywhere ($raised 300 million from Soft Bank Vision Fund), enterprise AI specialist Noodle.ai (raised $35 million from Dell Technologies Capital and TPG Growth), AI-based grid analytics provider AutoGrid which works on energy solutions (raised $32 million Series D from CLP, Innogy, Orsted and Tenaska. Meanwhile, energy analytics firm Bidgely secured $27 million in Series C (raised funding from $27 million from Georgian Partners). Healthtech startup SigTuple that has developed an AI-powered platform Manthana SigTuple (raised $19 million in series B funding round from Accel and IDG Ventures). Note: All the top 4 most-funded startups, excluding SigTuple are headquartered in California with engineering units in Bangalore.
2018 – AI showed promise with November recording highest deal volume
The year started on a mild note with $28 million deal volume in January. SoftBank Vision Fund’s deal in November was the highest ever funding seen in the year, taking the deal volume to $337 million in November. Earlier in 2018, June registered a high deal volume of $60.95 million followed by September, $46.55.
Technology Growth Across Sectors – Automation, AI, ML big winners
The biggest deals of 2018 show there is a lot of optimism around AI, automation, machine learning, big data and analytics. The trend is clearly towards AI-driven investing and this can also be seen from a domain point of view where narrow domains, such as energy and automation specific applications being the most funded. The new capital is not only driving the valuation of these companies but also proves that all the rumblings about AI are true.
Investment by Cities – Bangalore continues to be the hub
Bangalore has the biggest war chest with an aggregate of $113 million capital. This number doesn’t include the biggest funding round of all – San Jose headquartered Automation Anywhere’s $300 million funding. There is a wide gap between Bangalore and Chennai which received $35 million, followed by Gurgaon that grossed $29.5 million and Mumbai at $6 million while Delhi recorded a deal volume of $1.7 million. However, outside the major hubs, other cities that saw VC momentum was Coimbatore’s social media analytics platform Synctag which raised $307,600 and Chandigarh-based AgNext which received an undisclosed amount of funding.
Early Stage vs Late Stage funding
Even though the biggest deals were closed in late stage, early stage and seed stage funding surpassed late stage thanks to more deals, not higher amount. The boost in early stage is from higher number of deals, with Series A leading by 36.4% followed by 27.3% in seed stage investments. Series B saw 18.2% investment while late stage (Series C, D) recorded 4.5% each respectively.
Top Dealmakers 2018 – SoftBank’s Masa Leads The Way
SoftBank with its ambitious $100 billion Vision Fund led by Masayoshi Son and Rajeev Misra has disrupted the venture capital market with its staggering investments, allowing companies to stay private longer. In India, SoftBank has an impressive investment portfolio, backing the biggest consumer internet companies and this time too, it gave a major fillip to RPA giant Automation Anywhere by writing a $300 million cheque. Given Masa’s funding pattern, he always puts a safe distance between his competitors.
The second major investment, $35 million was by Dell Technologies venture investment arm and TPG Growth in Noodle.ai. Bain Capital Venture and early stage VC firm Hyde Park Venture Partners also invested $35 million in Four Kites. This was followed by consortium of Denmark’s Orsted, Hong Kong-based CLP, US energy company Tenaska and German energy company Innogy which made an investment of $32 million in AutoGrid. Meanwhile, Jungle Ventures and European Venture Capital firm Lakestar invested $29.5 million in AI low-code platform Engineer.ai.
Year-on-year comparison – 2018 grossed an all-time high funding
The last five years has seen the industry build on its analytics innovations and lay the foundation for AI. There has been a steady rise in investment from 2014 which clocked $75 million in investment, while 2015 saw a 70% growth in funding. 2016 saw $213 million being poured into startups while 2017 saw funding almost halved by $100 million. A key reason is that in 2016 companies were tinkering at the edges of AI, and 2017 it moved from PoC stage to production and now we are seeing full-fledged commercial applications. Also, one of the key takeaways of 2018 is that high-growth startups and companies that are fostering AI innovation are also proving it with their robust financial performance, a major reason why investors and VC firms are betting big on the high-growth companies.
Bottom funded startups of 2018
At the bottom of the stack are Bangalore-headquartered HR tech startup Skillate that raised $200k, AI-driven conversational platform Trilyo targeted at the hospitality sector, which raised $250k in 2018. These startups are followed by Tamil Nadu based social media analytics startup Synctag ($308k) while restaurant analytics company Spoonshot (DishQ) raised $400k in pre-seed funding followed by Bangalore-based Mate Labs that raised $550k in seed funding.
Indian AI Startup Funding 2018: Global Investment In India Touched USD$ 529.52 Million
As someone who is currently working on "cutting edge" "AI" --or rather computer vision-- and having developed a major commercial "AI" solution; I have very simple BUT concrete suggestions to the government on policy lines:
1. Establish a standard for datasets to be used in India.
2. Establish massive public datasets and a collection of models trained with them; with a license that forces entities to contribute in terms of labelled datasets. Ie, if you use our pre-trained network to translate or 'recognize' Marathi and transfer learn it to specific context, for example say security products, you will have to contribute atleast part of your data-set back into public dataset with same license.
3. Working with Indian software industry, establish a massive labelling platform on the lines of MTurk AND/OR force MTurk or any company employing Indian via MTurk to release and license datasets collected from India which is about Indian content like road-signs, spoken or written languages etc to Indian government and companies. Basically you don't want foreign companies to collect massive datasets on India and put Indian companies at disadvantage.
4. Synchronize and coordinate the work by all Indian government funded institute towards data collection. Often data collected by one government department or university is simply not visible to any one else. You want a data-sets collected by various bodies to have a synergy.
5. Have large scale GPU "clouds" or data centres to enable Indian universities or start-ups to train their models.
"AI" is just all about data collection and labelling. "Data" is your secret sauce and differentiator. Developing modern AI is essentially a large scale optimization problem --usually stochastic-- and you need data for it.
1. Establish a standard for datasets to be used in India.
2. Establish massive public datasets and a collection of models trained with them; with a license that forces entities to contribute in terms of labelled datasets. Ie, if you use our pre-trained network to translate or 'recognize' Marathi and transfer learn it to specific context, for example say security products, you will have to contribute atleast part of your data-set back into public dataset with same license.
3. Working with Indian software industry, establish a massive labelling platform on the lines of MTurk AND/OR force MTurk or any company employing Indian via MTurk to release and license datasets collected from India which is about Indian content like road-signs, spoken or written languages etc to Indian government and companies. Basically you don't want foreign companies to collect massive datasets on India and put Indian companies at disadvantage.
4. Synchronize and coordinate the work by all Indian government funded institute towards data collection. Often data collected by one government department or university is simply not visible to any one else. You want a data-sets collected by various bodies to have a synergy.
5. Have large scale GPU "clouds" or data centres to enable Indian universities or start-ups to train their models.
"AI" is just all about data collection and labelling. "Data" is your secret sauce and differentiator. Developing modern AI is essentially a large scale optimization problem --usually stochastic-- and you need data for it.
How India can prepare its workforce for the artificial intelligence era
As artificial intelligence technologies take over a larger number of tasks, India will face unique impacts of automation relative to other countries. With its large and young population, advances in AI will affect India in aspects from jobs to quality of life. Incidentally, the Indian economy is currently ill-equipped to face the advent of automation and AI. Though India is one of the fastest growing large economies, higher growth is not converting into more jobs. There are measures that the country must take to meet the challenges that arise as different working environments steadily automate. These include boosting employment in sectors that are least vulnerable to automation and encouraging entrepreneurship among the youth. Political will and awareness of the challenges associated with automation are key prerequisites to prepare India for automation.
Employment in India
Imagining the future of work and workforce cannot be complete without considering its future in India—soon-to-be the world’s fifth largest economy. The country with a population of 1.3 billion is already facing a problem of employing its vast and growing workforce. In February 2018, its railroads had 63,000 job openings, for which 19 million people applied. An Ernst & Young study states that there are 17 million new entrants into the Indian workforce year after year, but only 5.5 million jobs created.
According to the State of Working in India 2018 report, a 10% increase in GDP now results in less than a 1% increase in employment—leading to counterintuitive higher unemployment in a fast-growing economy. The report also highlights the issue of income disparity: As labor productivity in organized manufacturing increased sixfold over the past three decades, wages increased just 50% over that period. Services may not be able to compensate for the job losses that automation causes in manufacturing, because major service industries like information technology and banking—the leading employers—face the threat of job losses thanks to changing industry dynamics and automation.
Our recommendations to realize the promise for AI and the potential of India start with better management of employment data. The Indian government should more proactively collect data on the state of employment to be able to plan for AI. The biometric information embedded in the unique identification numbers from Aadhaar data can be used to gauge the proportion of employed and unemployed in the economy.
With half of the country’s population below the age of 25, a pertinent step would be to prepare the young workforce by exposing them to the tech-enabled future of work with AI interfaces, machine learning, and increased automation. Online training programs, inclusion of AI and automation in the existing education curriculum, and corporate training programs for new hires can achieve this without much structural change and investment. For this, the political leadership also needs a better understanding of automation technologies and their implications for the Indian economy.
Transitioning to less vulnerable sectors
Instead of framing policies and incentives to create employment opportunities in areas that are going to be the first to lose jobs with the advent of automation and AI, it will be better to boost employment in the areas that are least vulnerable to automation. Sectors like healthcare and education have a high element of human engagement that cannot be easily automated. Jobs in the arts, entertainment, and sports are highly interpersonal and creative in nature, and likewise may not immediately be vulnerable to automation. These sectors should be boosted to revive the industry’s capacity to create jobs.
As a natural corollary, India needs to attract more talent towards the humanities, arts, crafts, and sports than STEM. With the Indian Institute of Technologies, India has built islands of excellence in STEM education, but has failed to repeat this success in other fields of education. There is an argument that holds that more STEM education won’t protect our jobs from robots. Too much focus on STEM has the inherent risk of over-saturation of few sectors over the others, hampering overall economic development.
Labor-intensive industries like tourism and arts should be aggressively pushed. India currently has a 1.2% share of international tourism, leaving much room to grow. While a grand scheme at the federal level will be instrumental in laying down the vision—implementation will have to be granular and decentralized. India is already the eighth largest exporters of creative goods, according to a UNCTAD report. The country’s creative goods exports nearly tripled from USD $7.4 billion in 2005 to USD $20.2 billion in 2014. With a proactive government-backed initiative to promote arts, India has significant potential to partake in the rising global market for creative goods that encompasses food, fashion, jewelry, handicrafts, movies, interior design, gaming, animation, and entertainment.
Boosting startups and entrepreneurship among youth can help. The rise of entrepreneurship courses in universities is instrumental in creating a startup culture in the country. Higher government procurement of goods and services from domestic startups can also boost entrepreneurship. Many small enterprises, instead of massive factories, are the more likely future of work in India.
The overall success of AI will rest on how a large and complicated country like India meanders towards becoming future-ready. If India fails to smoothly ride the AI wave that is taking shape in the developed world, it will be a setback for the AI revolution. For India to succeed, it needs concrete measures that go beyond the ongoing policy discussions.
How India can prepare its workforce for the artificial intelligence era
As artificial intelligence technologies take over a larger number of tasks, India will face unique impacts of automation relative to other countries. With its large and young population, advances in AI will affect India in aspects from jobs to quality of life. Incidentally, the Indian economy is currently ill-equipped to face the advent of automation and AI. Though India is one of the fastest growing large economies, higher growth is not converting into more jobs. There are measures that the country must take to meet the challenges that arise as different working environments steadily automate. These include boosting employment in sectors that are least vulnerable to automation and encouraging entrepreneurship among the youth. Political will and awareness of the challenges associated with automation are key prerequisites to prepare India for automation.
Employment in India
Imagining the future of work and workforce cannot be complete without considering its future in India—soon-to-be the world’s fifth largest economy. The country with a population of 1.3 billion is already facing a problem of employing its vast and growing workforce. In February 2018, its railroads had 63,000 job openings, for which 19 million people applied. An Ernst & Young study states that there are 17 million new entrants into the Indian workforce year after year, but only 5.5 million jobs created.
According to the State of Working in India 2018 report, a 10% increase in GDP now results in less than a 1% increase in employment—leading to counterintuitive higher unemployment in a fast-growing economy. The report also highlights the issue of income disparity: As labor productivity in organized manufacturing increased sixfold over the past three decades, wages increased just 50% over that period. Services may not be able to compensate for the job losses that automation causes in manufacturing, because major service industries like information technology and banking—the leading employers—face the threat of job losses thanks to changing industry dynamics and automation.
Our recommendations to realize the promise for AI and the potential of India start with better management of employment data. The Indian government should more proactively collect data on the state of employment to be able to plan for AI. The biometric information embedded in the unique identification numbers from Aadhaar data can be used to gauge the proportion of employed and unemployed in the economy.
With half of the country’s population below the age of 25, a pertinent step would be to prepare the young workforce by exposing them to the tech-enabled future of work with AI interfaces, machine learning, and increased automation. Online training programs, inclusion of AI and automation in the existing education curriculum, and corporate training programs for new hires can achieve this without much structural change and investment. For this, the political leadership also needs a better understanding of automation technologies and their implications for the Indian economy.
Transitioning to less vulnerable sectors
Instead of framing policies and incentives to create employment opportunities in areas that are going to be the first to lose jobs with the advent of automation and AI, it will be better to boost employment in the areas that are least vulnerable to automation. Sectors like healthcare and education have a high element of human engagement that cannot be easily automated. Jobs in the arts, entertainment, and sports are highly interpersonal and creative in nature, and likewise may not immediately be vulnerable to automation. These sectors should be boosted to revive the industry’s capacity to create jobs.
As a natural corollary, India needs to attract more talent towards the humanities, arts, crafts, and sports than STEM. With the Indian Institute of Technologies, India has built islands of excellence in STEM education, but has failed to repeat this success in other fields of education. There is an argument that holds that more STEM education won’t protect our jobs from robots. Too much focus on STEM has the inherent risk of over-saturation of few sectors over the others, hampering overall economic development.
Labor-intensive industries like tourism and arts should be aggressively pushed. India currently has a 1.2% share of international tourism, leaving much room to grow. While a grand scheme at the federal level will be instrumental in laying down the vision—implementation will have to be granular and decentralized. India is already the eighth largest exporters of creative goods, according to a UNCTAD report. The country’s creative goods exports nearly tripled from USD $7.4 billion in 2005 to USD $20.2 billion in 2014. With a proactive government-backed initiative to promote arts, India has significant potential to partake in the rising global market for creative goods that encompasses food, fashion, jewelry, handicrafts, movies, interior design, gaming, animation, and entertainment.
Boosting startups and entrepreneurship among youth can help. The rise of entrepreneurship courses in universities is instrumental in creating a startup culture in the country. Higher government procurement of goods and services from domestic startups can also boost entrepreneurship. Many small enterprises, instead of massive factories, are the more likely future of work in India.
The overall success of AI will rest on how a large and complicated country like India meanders towards becoming future-ready. If India fails to smoothly ride the AI wave that is taking shape in the developed world, it will be a setback for the AI revolution. For India to succeed, it needs concrete measures that go beyond the ongoing policy discussions.
How India can prepare its workforce for the artificial intelligence era
India ranks third in research on artificial intelligence
Jacob Koshy
NEW DELHI , JANUARY 18, 2019 22:19 IST
UPDATED: JANUARY 18, 2019 22:19 IST
New analysis tracked papers in peer-reviewed journals
India ranks third in the world in terms of high quality research publications in artificial intelligence (AI) but is at a significant distance from world leader China, according to an analysis by research agency Itihaasa, which was founded by Kris Gopalakrishnan, former CEO and co-founder of Infosys.
The agency computed the number of ‘citable documents’— the number of research publications in peer-reviewed journals — in the field of AI between 2013-2017 as listed out by Scimago, a compendium that tracks trends in scientific research publications.
China stands first
India, while third in the world with 12,135 documents, trailed behind China with 37, 918 documents and the United States with 32,421 documents.
However, when parsed by another metric ‘citations’— or the number of times an article is referenced — India ranked only fifth and trailed the United Kingdom, Canada, the U.S. and China. “This suggests that India must work at improving the quality of its research output in AI,” said Dayasindhu N., one of the authors of the report ‘Landscape of AI/ML (Machine Learning) Research In India’.
Given India’s traditional strength in information technology and AI said to pose a transformation in industry and academic circles, the report was an attempt at mapping the state of AI-based research in India.
There were only about 50 to 75 principal researchers in the AI-space in India and they were tended to collaborate with each other. The Indian Institutes of Technology and the Indian Institutes of Information Technology were among the key centres for AI research.
The report authors interviewed 25 AI researchers across the country, who said that as of now “…there was adequate support and funding from the government and industry for AI research.”
Healthcare, financial services, monsoon forecasting, retail and education were the key fields likely to benefit from AI and the field was “unlikely to lead” to a destruction of jobs — a key global concern regarding the field.
India’s national think-tank, the NITI Ayog, last June released a discussion paper on the transformative potential of AI in India that said the country could add $1 trillion to its economy through integrating AI into its economy.
India ranks third in research on artificial intelligence
NEW DELHI , JANUARY 18, 2019 22:19 IST
UPDATED: JANUARY 18, 2019 22:19 IST
New analysis tracked papers in peer-reviewed journals
India ranks third in the world in terms of high quality research publications in artificial intelligence (AI) but is at a significant distance from world leader China, according to an analysis by research agency Itihaasa, which was founded by Kris Gopalakrishnan, former CEO and co-founder of Infosys.
The agency computed the number of ‘citable documents’— the number of research publications in peer-reviewed journals — in the field of AI between 2013-2017 as listed out by Scimago, a compendium that tracks trends in scientific research publications.
China stands first
India, while third in the world with 12,135 documents, trailed behind China with 37, 918 documents and the United States with 32,421 documents.
However, when parsed by another metric ‘citations’— or the number of times an article is referenced — India ranked only fifth and trailed the United Kingdom, Canada, the U.S. and China. “This suggests that India must work at improving the quality of its research output in AI,” said Dayasindhu N., one of the authors of the report ‘Landscape of AI/ML (Machine Learning) Research In India’.
Given India’s traditional strength in information technology and AI said to pose a transformation in industry and academic circles, the report was an attempt at mapping the state of AI-based research in India.
There were only about 50 to 75 principal researchers in the AI-space in India and they were tended to collaborate with each other. The Indian Institutes of Technology and the Indian Institutes of Information Technology were among the key centres for AI research.
The report authors interviewed 25 AI researchers across the country, who said that as of now “…there was adequate support and funding from the government and industry for AI research.”
Healthcare, financial services, monsoon forecasting, retail and education were the key fields likely to benefit from AI and the field was “unlikely to lead” to a destruction of jobs — a key global concern regarding the field.
India’s national think-tank, the NITI Ayog, last June released a discussion paper on the transformative potential of AI in India that said the country could add $1 trillion to its economy through integrating AI into its economy.
India ranks third in research on artificial intelligence
I wonder how's this news. Anyone who's seen @Guynextdoor & his antics over a period of time will put down his existence to AI. On his own, he wouldn't even qualify to climb trees for a living.
