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- Explained: Generative AI’s environmental impact - MIT News
MIT News explores the environmental and sustainability implications of generative AI technologies and applications
- Massachusetts Institute of Technology - MIT News
New AI agent learns to use CAD to create 3D objects from sketches The virtual VideoCAD tool could boost designers’ productivity and help train engineers learning computer-aided design
- What does the future hold for generative AI? - MIT News
Hundreds of scientists, business leaders, faculty, and students shared the latest research and discussed the potential future course of generative AI advancements during the inaugural symposium of the MIT Generative AI Impact Consortium (MGAIC) on Sept 17
- Responding to the climate impact of generative AI - MIT News
MIT experts discuss strategies and innovations aimed at mitigating the amount of greenhouse gas emissions generated by the training, deployment, and use of AI systems, in the second in a two-part series on the environmental impacts of generative artificial intelligence
- Explained: Generative AI | MIT News | Massachusetts Institute of Technology
What do people mean when they say “generative AI,” and why are these systems finding their way into practically every application imaginable? MIT AI experts help break down the ins and outs of this increasingly popular, and ubiquitous, technology
- How we really judge AI - MIT News
A new study finds people are more likely to approve of the use of AI in situations where its abilities are perceived as superior to humans’ and where personalization isn’t necessary
- Using generative AI, researchers design compounds that can kill drug . . .
Using generative AI algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties The top candidates they discovered are structurally distinct from any existing antibiotics, and they appear to work by novel mechanisms that disrupt bacterial cell membranes
- Can AI really code? Study maps the roadblocks to autonomous software . . .
An AI that can shoulder the grunt work — and do so without introducing hidden failures — would free developers to focus on creativity, strategy, and ethics” says Gu “But that future depends on acknowledging that code completion is the easy part; the hard part is everything else Our goal isn’t to replace programmers It’s to
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