N V Vijayakumar, DH News Service, Bengaluru, Aug 13 2017, 23:55 IST
The company says it is focused on building deep learning and ML systems to address 'old problems'.
Google’s recent acquisition of Halli Labs, an artificial intelligence (AI) and machine learning (ML) startup started by an IIT-Delhi alumni Pankaj Gupta, has fuelled Bengaluru’s ambition of becoming the hub of AI and ML product startups.
Halli, which means a village in Kannada, was born five months ago in Bengaluru for developing solutions to traditional problems using AI, ML, deep learning and natural language processing technologies.
Commenting on the development, Google’s vice-president for product management Ceasar Sengupta tweeted, “Welcome Pankaj and the team at Halli Labs to Google. Looking forward to building some cool stuff together.”
The company says it is focused on building deep learning and ML systems to address ‘old problems’. Gupta said the company will be joining Google’s Next Billion Users team. “Halli Labs will help get more technology and information into more people’s hands around the world,” he said.
Gupta is interested in the areas of personalisation, applied machine learning, AI, user growth and engagement, search, recommendation and discovery products, distributed systems, graph infrastructure and algorithms. He has published over 30 papers and filed more than 20 patent applications. Google and its parent company Alphabet are vigorously persuing acqui-hiring in AI startups along with other technology giants Baidu, Samsung, Microsoft, Apple, Facebook and Snap.
According to a startup founder working in the similar space, AI and ML are still in their initial stages, just like how smartphone and mobile apps were a decade ago. “All startup founders are very much aware of its importance. But they are groping in the dark to identify problems so that they can resolve it via business solution based on AI and ML tools.
He also said human beings are better than machines anyway in doing activities. “But there are many tasks which can be done at par and at a lower cost by AI, ML supported machines,” he said.
Bengaluru is emerging as hub of AI and ML startup as various accelerators and incubators are giving primacy to them. According to analysts, Kalaari Capital’s KStart and TLabs are incubating lots of startups in this area.
Tech experts said, AI helps machines to carry out tasks in a smart and intelligent way. ML is applications of AI to give machines access to data and let them learn for themselves. Machines and devices with AI are classified into one of the two fundamental groups – applied or general.
“Applied AI is where common problems, majority single solutions, for example, intelligently trade stocks and shares, or manoeuvre an autonomous vehicle. Generalised AIs are systems or devices which can handle any task and here some of the most exciting advancements are happening today,” said an analyst.
Artifacia, a Bengaluru-based startup that provides an AI-based visual discovery platform to fashion and lifestyle retailers, and brands, is really a classic example of this. It helps them improve product discovery, and hence conversions on their apps and websites.
Artifacia’s major differentiator is its visual-first approach to solving product discovery problems for end-users. “Basically, what it means is that in the case of categories like fashion what matters is the visual quality or the attributes of the image, like what makes the dress unique, whether it is the colour, style and shape, and so on. We combine the understanding of these product images with the users’ interests, demography and available product data with our AI technologies to be able to recommend the right kind of products to end-users,” Navneet Sharma, Co-founder and CEO, Artifacia said.
Besides IBM’s Watson, which the company describes as a “cognitive” system that uses artificial intelligence (AI) technologies mostly in healthcare and education and IPsoft’s Amelia, Microsoft Corporation’s AI and Research Group, Amazon AI Services, Facebook AI Research (FAIR) and OpenAI, a non-profit lab partly funded by Elon Musk of Tesla are doing enormous work around in this area. Not to be left behind, Indian IT services companies like Infosys Nia, TCS Ignio and Wipro Holmes artificial intelligence platforms also are driving these initiatives.
In a recent letter to employees, Infosys Chief Executive Officer Vishal Sikka said there is a need to massively embrace automation in the commoditising parts of our core business, and bring grassroots innovation into everything employees are working on. “Doing so requires us to reach back within ourselves and to learn, to exercise our learnability. Learn about AI and automation, learn about new technologies, but most importantly learn to learn, to innovate, to build with creative confidence,” Sikka said.
Demis Hassabis, the founder of London-based AI startup DeepMind which was purchased by Google for $650 million back in 2014, is heading the AI initiatives of the global tech giant. As part of its initiatives, the company is bringing humans at the complex game of AlphaGo to play instinctively and begun making steps towards crafting more general AI programme.
Hassabis has now stated that the only way AI can realise its true potential is by imbibing and taking inspiration from human intellect than banking on layers of mathematics. But different types of machine learning, such as speech recognition or identifying objects in an image, require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks.
Building AI that can perform general tasks, rather than niche ones, is a long-held desire in the world of machine learning. But the truth is that expanding those specialised algorithms to something more versatile remains an incredibly difficult problem, in part because human traits like inquisitiveness, imagination, and memory don’t exist or are only in their infancy in the world of AI.
Backed by emerging technologies, we can expect that AI will go beyond mere automation of routine tasks and help us to address complex business challenges not previously tackled by ‘traditional’ IT and engineering.