Wednesday July 17, 2019
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Swiggy Acqui-hires AI Start-up For Deep Learning

Kint.io is the first technology-led acqui-hire for Swiggy as it makes investments in its long-term strategy of building AI-first platforms

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Swiggy
Founded in 2014, Swiggy claims to have 50,000 restaurant partners

Online food ordering and delivery app Swiggy on Monday announced it has acqui-hired Kint.io, an Artificial Intelligence (AI) start-up that applies deep learning and computer vision for object recognition in video, for an undisclosed sum.

Founded in 2014, the Bengaluru-based start-up would assist Swiggy in boosting its computer-vision technology and consumer experience.

The founding members of Kint.io, Pavithra Solai Jawahar and Jagannathan Veeraraghavan, will join the Swiggy team, the company said in a statement.

Swiggy
Swiggy will use the funds to bring more quality food brands closer to consumers.

“This acqui-hire is part of our strategy to scale our tech prowess by bringing in entrepreneurial teams that can solve unique customer problems, while leveraging the network and resources at Swiggy,” said Dale Vaz, Head of Engineering and Data Sciences, Swiggy.

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Kint.io is the first technology-led acqui-hire for Swiggy as it makes investments in its long-term strategy of building AI-first platforms.

“AI research has leap-frogged this past year but lack of data, cultural biases and inability to adapt to our diversity has somehow always pulled us back when it comes to applying AI to India-based problems. This is where Swiggy left us stumped,” said Jawahar and Veeraraghavan. (IANS)

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Researchers Develop AI Algorithm That can Solve Rubik’s Cube in Less Than a Second

According to the researchers, the ultimate goal of projects such as this one is to build the next generation of AI systems

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Researchers have developed an AI algorithm that can solve a Rubiks Cube in a fraction of a second, faster than most humans. The work is a step toward making AI systems that can think, reason, plan and make decisions.

The study, published in the journal Nature Machine Intelligence, shows DeepCubeA — a deep reinforcement learning algorithm programmed by University of California computer scientists and mathematicians — can solve the Rubik’s Cube in a fraction of a second, without any specific domain knowledge or in-game coaching from humans.

This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state – each of six sides displaying a solid colour – which apparently can not be found through random moves.

“Artificial Intelligence can defeat the world’s best human chess and Go players, but some of the more difficult puzzles, such as the Rubik’s Cube, had not been solved by computers, so we thought they were open for AI approaches,” said study author Pierre Baldi, Professor at the University of California.

“The solution to the Rubik’s Cube involves more symbolic, mathematical and abstract thinking, so a deep learning machine that can crack such a puzzle is getting closer to becoming a system that can think, reason, plan and make decisions,” Baldi said.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

For the study, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the shortest path to the goal state about 60 per cent of the time.

The algorithm also works on other combinatorial games such as the sliding tile puzzle, Lights Out and Sokoban.

The researchers were interested in understanding how and why the Artificial Intelligence (AI) made its moves and how long it took to perfect its method.

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“It learned on its own, our AI takes about 20 moves, most of the time solving it in the minimum number of steps,” Baldi said.

“Right there, you can see the strategy is different, so my best guess is that the AI’s form of reasoning is completely different from a human’s,” he added.

According to the researchers, the ultimate goal of projects such as this one is to build the next generation of AI systems. (IANS)