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

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robots, UncategorizedMarch 20, 202432Views0Likes0Comments
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?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 20, 202435Views0Likes0Comments
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.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robots, UncategorizedMarch 20, 202433Views0Likes0Comments
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?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 20, 202437Views0Likes0Comments
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.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robots, UncategorizedMarch 19, 202436Views0Likes0Comments
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?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 19, 202436Views0Likes0Comments
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.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Imaging, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedMarch 19, 202437Views0Likes0Comments
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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Three Inquiries: Understanding the essentials of audio deepfakes.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Ethics, Interview, Machine learning, MIT Schwarzman College of Computing, Natural language processing, School of Engineering, Technology and society, UncategorizedMarch 16, 202441Views0Likes0Comments
Audio deepfakes, although often associated with unethical practices, have potential uses that can benefit society, suggests postdoc Nauman Dawalatabad in a Q&A with MIT News. He highlights the need for technology that protects sensitive information held within speech patterns, such as age, gender, and health conditions, stating that obscuring the speaker's identity in audio deepfakes…

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Scientists improve the side vision abilities in AI systems.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedMarch 9, 202443Views0Likes0Comments
Researchers at MIT have developed an image dataset that simulates peripheral vision for use in training machine learning (ML) models, an area where artificial intelligence (AI) notably diverges from human ability. Humans leverage less-detailed peripheral vision to detect shapes and items outside their direct line of sight, an ability AI lacks. Incorporating aspects of peripheral…

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What does the future have in store for generative AI?

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, McGovern Institute, MIT Schwarzman College of Computing, School of Engineering, Special events and guest speakers, Staff, Students, UncategorizedMarch 7, 202440Views0Likes0Comments
The "Generative AI: Shaping the Future" symposium, the kickoff event of MIT’s Generative AI Week, drew hundreds of attendees both from academia and industry. Rodney Brooks, iRobot co-founder and keynote speaker, warned attendees against uncritically overestimating the capabilities of generative AI, a technology increasingly powering tools such as OpenAI’s ChatGPT and Google’s Bard. Generative AI…

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The automated system instructs users on appropriate timings for collaboration with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedMarch 7, 202435Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an onboarding process that efficiently combines human and AI efforts. The system educates a user when to collaborate with an AI assistant and when not. This method can find situations when a user trusts the AI model's advice, but the model is incorrect. The…

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