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‘Artificial Intelligence yet to make its mark in India’

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By Nishant Arora

From taking care of businesses to fulfilling personal needs, Artificial Intelligence (AI) is very much a part of the daily lives of people across the globe with global technological giants judiciously utilizing its benefits. However, it has yet to make a mark in India.

When Amit Singhal, an India-born techie who joined Google nearly 15 years ago practically reigning at Google Search since then, decided to quit this month and hand the baton over to the head of the technology giant’s artificial intelligence (AI) chief, the message was clear: AI was the future that had arrived.

Amid all the brouhaha over machines acquiring near-human intelligence, is India ready to embrace the change?

“For the Indian market, we might see some serious AI in action around 2020, and by 2025, there should be considerable advancements,” Faisal Kawoosa, lead analyst, Telecoms Practice, at market research and consulting firm CyberMedia Research (CMR), told reporters.

According to Thomas George, SBU Head of CMR, there were several studies projecting AI becoming mainstream within five years. “However, this appears possible only in the high-end segments in the advanced and developed markets and not in India,” he added.

According to a latest forecast by the research firm MarketsandMarkets, the AI market is estimated to reach $5 billion by 2020 globally. “The increasing use of machine learning technology in the advertising and media and finance sectors, and the growing demand for AI across diversified application areas are driving the growth of the AI market,” the findings showed.

In India, the top-notch technology companies are yet to make a substantial progress in the business of AI.

While Tata Consultancy Services (TCS) has Ignio — a neural science-based automation platform that optimises IT operations, Infosys has recently launched AiKiDo project that will focus on AI, knowledge-based IT and design thinking to help enterprise clients.

Wipro, on the other hand, has an AI platform “Holmes”- a rich set of cognitive computing services for the development of digital virtual agents, cognitive process automation, visual computing applications, robotics and drones. To fulfill its AI dreams, Wipro recently acquired a strategic stake in Vicarious, an AI company based in San Francisco, California.

But this does not seem enough when it comes to the practical application of AI in the country on a large scale. “Although industry circles have been talking about AI for more than a decade, it is yet to make its mark in India,” George said.

Globally, Microsoft, Google and Facebook are leading the way when it comes to incorporating AI into the workplace — transforming the experience of “machine learning” via “deep neural networks” of hardware and software that nearly approximate neurons in the human brain.

“Machine intelligence is crucial to our search vision of building a truly intelligent assistant that connects our users to information and actions in the real world,” Google said in a statement recently.

John Giannandrea, who led Google’s machine learning efforts and is going to replace Singhal, is applying the technology to products such as image recognition for Google Photos search and the smart reply for Google Inbox.

In a cheer for the AI community, Google’s AlphaGo, a program of its artificial intelligence arm DeepMind, recently defeated the reigning human champion of Go – a complex Chinese board game that is considered the “quintessential unsolved problem” for machine intelligence.

At Facebook, its CEO Mark Zuckerberg wants to focus on AI and is even thinking of a simple AI to run his home and workplace like the famous Jarvis character in the Hollywood movie “Iron Man”.

According to Chris Bishop, managing director at Microsoft Research, 2016 will be the year of AI. “During 2016, we will see the emergence of new silicon architectures that are tuned to the intensive workloads of machine learning, offering a major performance boost over GPUs (Graphics Processing Units),” he posted.

In his first “Ask Me Anything” session on the social networking website Reddit last year, famed theoretical physicist Stephen Hawking said that we evolved to be smarter than our ape-like ancestors and scientist Albert Einstein was smarter than his parents.

“If they become that clever, then we may face an ‘intelligence explosion’, as machines develop the ability to engineer themselves to be far more intelligent,” he said in reply to a question on the discussion board.

That might eventually result in “machines whose intelligence exceeds ours by more than ours exceeds that of snails”, Hawking answered.

That may be a daunting task for people to absorb. But perhaps human intelligence will evolve to do just that. (IANS) (Image source: digitaltrends.com)

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Microsoft Lays Off News Production Workers; Replace Them With AI

A report suggests that Microsoft has cut off its editorial staff and replaced them with AI

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Microsoft
Microsoft cuts off staff and replaces them with artificial intelligence. Pxabay

Microsoft is reportedly laying off at least 50 news production workers and replacing them with artificial intelligence (AI)-based algorithms to perform their editorial duties.

According to a report in the Seattle Times on Saturday, the roughly 50 employees contracted through staffing agencies Aquent, IFG and MAQ Consulting have been notified “that their services would no longer be needed beyond June 30”.

These news production contractors work with Microsoft News, the company’s news content arm that operates MSN.com and other properties.

A Microsoft spokesperson said in a statement that like all companies, they evaluate business on a regular basis.

“This can result in increased investment in some places and, from time to time, redeployment in others. These decisions are not the result of the current pandemic,” said the Microsoft spokesperson.

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All the work, duty and tasks of the workers will be performed by AI. Pixabay

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Some employees told Seattle Times that “MSN will use AI to replace the production work they’d been doing”.

The work includes using algorithms to identify trending news stories from dozens of publishing partners, rewrite headlines or adding better photographs or slide shows.

Besides the production work, the contract employees also planned content, maintained the editorial calendars of partner news websites and assigned content to them. (IANS)

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Facebook AI Research Team Develops ‘RegNet’

Facebook AI model beats Google, runs 5 times faster on GPUs

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Facebook
Facebook AI Research (FAIR) has developed a novel low-dimensional design space called 'RegNet' that outperforms traditional available models. Pixabay

A team from Facebook AI Research (FAIR) has developed a novel low-dimensional design space called ‘RegNet’ that outperforms traditional available models like from Google and runs five times faster on GPUs.

RegNet produces simple, fast and versatile networks and in experiments, it outperformed Google’s SOTA EfficientNet models, said the researchers in a paper titled ‘Designing Network Design Spaces; published on pre-print repository ArXiv. The researchers aimed for “interpretability and to discover general design principles that describe networks that are simple, work well, and generalize across settings”.

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The Facebook AI team conducted controlled comparisons with EfficientNet with no training-time enhancements and under the same training setup.

Introduced in 2019, Google’s EfficientNet uses a combination of NAS and model scaling rules and represents the current SOTA.
With comparable training settings and Flops, RegNet models outperformed EfficientNet models while being up to 5× faster on GPUs.

Facebook
Facebook AI research team recently developed a tool that tricks the facial recognition system to wrongly identify a person in a video. Pixabay

Rather than designing and developing individual networks, the team focused on designing actual network design spaces comprising huge and possibly infinite populations of model architectures. Design space quality is analyzed using error empirical distribution function (EDF).

Analyzing the RegNet design space also provided researchers other unexpected insights into network design. They noticed, for example, that the depth of the best models is stable across compute regimes with an optimal depth of 20 blocks (60 layers).

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“While it is common to see modern mobile networks employ inverted bottlenecks, researchers noticed that using inverted bottlenecks degrades performance. The best models do not use either a bottleneck or an inverted bottleneck, said the paper. Facebook AI research team recently developed a tool that tricks the facial recognition system to wrongly identify a person in a video.

The “de-identification” system, which also works in live videos, uses machine learning to change key facial features of a subject in a video. FAIR is advancing the state-of-the-art in artificial intelligence through fundamental and applied research in open collaboration with the community.

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The social networking giant created the Facebook AI Research (FAIR) group in 2014 to advance the state of the art of AI through open research for the benefit of all.

Since then, FAIR has grown into an international research organization with labs in Menlo Park, New York, Paris, Montreal, Tel Aviv, Seattle, Pittsburgh, and London. (IANS)

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Researchers Design AI-Based System That Can Predict Battery Health

The researchers designed a new way to monitor batteries by sending electrical pulses into them and measuring the response

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The researchers also showed that the machine learning model can be interpreted to give hints about the physical mechanism of degradation. Pixabay

Researchers have designed an Artificial Intelligence (AI)-based system that can predict battery health with 10 times higher accuracy than current industry standard.

The findings, detailed in the journal Nature Communications, could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics as predicting the state of health and the remaining useful lifespan of lithium-ion batteries is one of the big problems limiting widespread adoption of electric vehicles.

It is also a familiar annoyance to mobile phone users. “Safety and reliability are the most important design criteria as we develop batteries that can pack a lot of energy in a small space,” said Alpha Lee from University of Cambridge who co-led the research.

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The researchers designed a new way to monitor batteries by sending electrical pulses into them and measuring the response. The measurements were then processed by a machine learning algorithm to predict the battery’s health and useful lifespan.

The researchers performed over 20,000 experimental measurements to train the model.
Their method is non-invasive and is a simple add-on to any existing battery system.

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Researchers have designed an Artificial Intelligence (AI)-based system that can predict battery health with 10 times higher accuracy than current industry standard. Pixabay

The researchers also showed that the machine learning model can be interpreted to give hints about the physical mechanism of degradation.

The model can inform which electrical signals are most correlated with ageing, which in turn allows them to design specific experiments to probe why and how batteries degrade.

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“By improving the software that monitors charging and discharging, and using data-driven software to control the charging process, I believe we can power a big improvement in battery performance,” Lee said. (IANS)