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Nvidia GPUs are being used in deep learning because of their high performance capabilities. Making them the best choice for training complex AI models.

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AMD is well know for its hardware Radeon GPUs now leads the charge on AI chips being optimized for the next generation of AI apps.

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Yoshua Bengio "The Godfather" of AI voices his concern for its possible impact on human life.

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The catastrophic risks of AI — and a safer path

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Yoshua Bengio — the world’s most-cited computer scientist and a “godfather” of artificial intelligence — is deadly concerned about the current trajectory of the technology. As AI models race toward full-blown agency, Bengio warns that they’ve already learned to deceive, cheat, self-preserve and slip out of our control. Drawing on his groundbreaking research, he reveals a bold plan to keep AI safe and ensure that human flourishing, not machines with unchecked power and autonomy, defines our future.

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John McCarthy gives a unique perspective by presenting AI as science and engineering of making intelligent machines.

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His company's innovates by creating tools to help reachers train models faster without needing deep hardware knowledge.

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This podcast covers AI across real world applications and features subject matter experts.

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will.i.am on AI – and the future of creativity (from ReThinking with Adam Grant)

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Podcast · [object Object] · Sure, some predictions about AI are just hype – but others suggest that everything we know is about to fundamentally change. Creative technologist Bilawal Sidhu talks with the world’s leading experts, artists, journalists, and more to explore the thrilling, sometimes terrifying, future ahead.

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In this article Roger C. Shank challenges traditional definitions of artificial intelligence. His argument is that true AI should focus on mimicking human behavior and not just problem solving.

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DOI:
https://doi.org/10.1609/aimag.v8i4.623

Abstract In this article, the scientific and technological goals of artificial intelligence, and a proposal of ten fundamental problems in AI research are discussed. This article is an introduction to Scientific Datalink's microfiche publication of the Yale AI technical reports. In this context, examples of research conducted at the Yale Artificial Intelligence Project relating to each of the research problems presented.

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https://doi.org/10.1609/aimag.v8i4.623 Abstract In this article, the scientific and technological goals of artificial intelligence, and a proposal of ten fundamental problems in AI research are discussed. This article is an introduction to Scientific Datalink's microfiche publication of the Yale AI technical reports.

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Shaolei Ren explains how and why AI uses water.

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Shaolei Ren: AI consumes a lot of water - but why?

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AI could soon consume billions of liters of water each year - much of it drinking water, says electrical and computer engineer Shaolei Ren. He dives into how energy-intensive training of large AI models, data center cooling and chip manufacturing all contribute to AI's massive "water footprint," advocating for greater transparency, smarter resource management and more sustainable practices to reduce AI's environmental impact, before it's too late.

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This image show how vast an AI data center is to paint the picture of how must heat a center produces.

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Is AI just a trend, or is it something that is here to stay long term?

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Some parts are hype, but the core technology will last.