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Algorithms

A single step allows AI to produce high-grade images at a speed 30 times quicker.

In the age of artificial intelligence, computers can generate "art" using diffusion models. However, this often involves a complex, time-consuming process requiring multiple iterations for the algorithm to perfect the image. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have now launched a new technique that simplifies this process into a single step using…

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A fresh approach relies on collective input from the public to assist in the education of robots.

A team of researchers from MIT, Harvard University, and the University of Washington have developed a novel reinforcement learning technique using crowdsourced feedback. The technique allows AI to learn complex tasks more quickly and without relying on an expertly designed reward function. The conventional reward function designed by dedicated human experts has been replaced by…

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What lies ahead for generative artificial intelligence?

MIT's Generative AI Week began with a symposium on November 28, titled “Generative AI: Shaping the Future”. The keynote speaker was Rodney Brooks, co-founder of iRobot and former director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT. During his address, Brooks cautioned against overestimating the capabilities of generative AI, which forms the basis…

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A novel approach employs collective public input to assist in educating robots.

Reinforcement learning, which involves teaching an AI agent a new task using a trial and error methodology, often requires the assistance of a human expert to create and modify the reward function. However, this can be time-consuming, inefficient and difficult to upscale, particularly when the task is highly complex and involves several stages. In response…

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What does the future entail for generative artificial intelligence?

In a keynote address at MIT's Generative AI Week on November 28, iRobot co-founder Rodney Brooks highlighted the potential dangers of overestimating the capabilities of generative AI, an emerging technology that supports powerful tools like OpenAI’s ChatGPT and Google’s Bard. He urged that while the technology has significant capabilities, the illusion that it can solve…

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A novel approach incorporates feedback from the public to assist in teaching robots.

Researchers from MIT, Harvard, and the University of Washington have developed a new method for training AI agents using reinforcement learning. Their approach replaces a process often involving a time-consuming design of a reward function by a human expert with feedback crowdsourced from non-expert users. Traditionally, AI reinforcement learning has used a reward function, designed by…

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What does the prospect look like for generative AI in the future?

At the Generative AI: Shaping the Future symposium, Rodney Brooks, keynote speaker and co-founder of iRobot, cautioned against overestimating the capabilities of Generative AI. The technology supports powerful tools like OpenAI’s ChatGPT and Google’s Bard, but Brooks argued that no single technology ever exceeds all others. He stressed the importance of responsible development and use…

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This fresh approach leverages input from the masses to assist in educating robots.

Teaching AI agents new tasks can be a challenging and time-consuming process, often involving iteratively updating a reward function designed by a human expert to motivate the AI’s exploration of possible actions. However, researchers from the Massachusetts Institute of Technology, Harvard University, and the University of Washington have developed a new reinforcement learning approach that…

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What does the future look like for generative AI?

In a recent symposium titled "Generative AI: Shaping the Future", iRobot co-founder Rodney Brooks urged caution regarding the unbridled optimism around generative artificial intelligence (AI). Generative AI uses machine-learning models to generate new material similar to the data it has been trained on, and has proven capable of creative writing, translation, generating code, and creating…

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A novel approach uses collective user feedback to assist in the training of robots.

Researchers at MIT, Harvard, and the University of Washington have shunned traditional reinforcement learning approaches, using crowdsourced feedback to teach artificial intelligence (AI) new skills instead. Traditional methods to teach AI tasks often required a reward function, which was updated and managed by a human expert. This limited scalability and was often time-consuming, particularly if…

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What does the future entail for generative AI?

During the kickoff event of MIT’s Generative AI Week, the “Generative AI: Shaping the Future” symposium, Rodney Brooks, co-founder of iRobot, cautioned attendees about the dangers of overestimating the capabilities of generative AI technology. Brooks, also a professor emeritus at MIT and former director of the Computer Science and Artificial Intelligence Laboratory (CSAIL), warned that…

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New algorithm delivers detailed understanding for computer vision.

MIT researchers have developed an algorithm called FeatUp that enables computer vision algorithms to capture both high-level details and fine-grained minutiae of a scene simultaneously. Modern computer vision algorithms, like human beings, can only recall the broad details of a scene while the more nuanced specifics are often lost. To understand an image, they break…

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