GamingNews

Facebook Gaming launches tournaments for esports amateurs

Facebook Gaming is launching tournaments for esports amateurs today in early access across the globe. In the era of social distancing, Facebook believes that games can bring us together. While the tournament feature was in the works for a while, Facebook decided to release it early to help people cope better while in isolation because of the coronavirus, said Mina Abouseif, the head engineer…
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GamingNews

Valve: More games are finding success on Steam than ever before

Steam is still one of the better ways for developers to make money from their games. But with thousands of new releases hitting Valve Software’s PC gaming store each year, it can seem like that opportunity is dwindling. But that’s not the case for most games, according…
AI & RoboticsNews

Tenstorrent reveals Grayskull, an all-in-one system that accelerates AI model training

Tenstorrent, an AI and machine learning hardware startup based in Toronto, Canada, today emerged from stealth with over $34 million in funding and an all-in-one computer system dubbed Grayskull. Cofounder and CEO Ljubisa Bajic, a former Nvidia senior architect who previously served as director of integrated circuit design at AMD, claims that Grayskull’s architecture eliminates unnecessary…
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AI & RoboticsNews

Microsoft claims its AI framework spots fake news better than state-of-the-art baselines

In a study published this week on the preprint server Arxiv.org, Microsoft and Arizona State University researchers propose an AI framework — Multiple sources of Weak Social Supervision (MWSS) — that leverages engagement and social media signals to detect fake news. They say that after training and testing the model on a real-world data set, it outperforms a number of state-of-the-art…
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AI & RoboticsNews

Google’s AI learns how to navigate environments from limited data

Carnegie Mellon, Google, and Stanford researchers write in a paper that they’ve developed a framework for using weak supervision — a form of AI training where the model learns from large amounts of limited, imprecise, or noisy data — that enables robots to efficiently explore a challenging environment. By learning to reach only areas of its surroundings relevant to tasks as opposed to every…
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