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Microsoft has released a public preview of a free app lets helps people train machine learning models without writing any code.

The Lobe desktop app for Windows and Mac currently only supports image classification, but Microsoft plans to expand it to other models and data types in the future.

“Just show it examples of what you want it to learn, and it automatically trains a custom machine learning model that can be shipped in your app,” the Lobe website explains.

Deci, a Tel Aviv-based startup that is building a new platform that uses AI to optimized AI models and get them ready for production, today announced that it has raised a $9.1 million seed round led by Emerge and Square Peg.

The general idea here is to make it easier and faster for businesses to take AI workloads into production — and to optimize those production models for improved accuracy and performance. To enable this, the company built an end-to-end solution that allows engineers to bring in their pre-trained models and then have Deci manage, benchmark and optimize them before they package them up for deployment. Using its runtime container or Edge SDK, Deci users can also then serve those models on virtually any modern platform and cloud.

Tuomas Sandholm, a computer scientist at Carnegie Mellon University, is not a poker player—or much of a poker fan, in fact—but he is fascinated by the game for much the same reason as the great game theorist John von Neumann before him. Von Neumann, who died in 1957, viewed poker as the perfect model for human decision making, for finding the balance between skill and chance that accompanies our every choice. He saw poker as the ultimate strategic challenge, combining as it does not just the mathematical elements of a game like chess but the uniquely human, psychological angles that are more difficult to model precisely—a view shared years later by Sandholm in his research with artificial intelligence.

“Poker is the main benchmark and challenge program for games of imperfect information,” Sandholm told me on a warm spring afternoon in 2018, when we met in his offices in Pittsburgh. The game, it turns out, has become the gold standard for developing artificial intelligence.

Tall and thin, with wire-frame glasses and neat brow hair framing a friendly face, Sandholm is behind the creation of three computer programs designed to test their mettle against human poker players: Claudico, Libratus, and most recently, Pluribus. (When we met, Libratus was still a toddler and Pluribus didn’t yet exist.) The goal isn’t to solve poker, as such, but to create algorithms whose decision making prowess in poker’s world of imperfect information and stochastic situations—situations that are randomly determined and unable to be predicted—can then be applied to other stochastic realms, like the military, business, government, cybersecurity, even health care.

The future Russian soldier is going to be able to control drone swarms, have landmine proof boots and an exoskeleton/suit to enhance their physical abilities and situational awareness.


Russia will integrate the ability to control small size attack drone swarms, robots, and exoskeletons into its next-generation soldier gear, in a development that feels more like a videogame update than reality.

Online health care and medtech AI have risen in prominence in the country as the government seeks more equal access to medicines and treatment for its citizens, spread across a vast land mass. The urgency has been heightened by the impact from Covid-19 – with Indonesia recently overtaking the Philippines as the hardest-hit country in Southeast Asia.


Indonesia’s fast-growing manufacturing sector also presents opportunities for medtech innovation as well as research and development.

“What will the next generation of artificial intelligence look like? Which novel AI approaches will unlock currently unimaginable possibilities in technology and business? This article highlights three emerging areas within AI that are poised to redefine the field—and society—in the years ahead. Study up now.”

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If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today. Methods that are currently considered cutting-edge will have become outdated; methods that today are nascent or on the fringes will be mainstream.

What will the next generation of artificial intelligence look like? Which novel AI approaches will unlock currently unimaginable possibilities in technology and business? This article highlights three emerging areas within AI that are poised to redefine the field—and society—in the years ahead. Study up now.