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Three inquiries: Understanding the essentials about 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, UncategorizedJune 17, 202439Views0Likes0Comments
The recent misuse of audio deepfakes, including a robocall purporting to be Joe Biden in New Hampshire and spear-phishing campaigns, has prompted questions about the ethical considerations and potential benefits of this emerging technology. Nauman Dawalatabad, a postdoctoral researcher, discussed these concerns in a Q&A prepared for MIT News. According to Dawalatabad, the attempt to obscure…

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Scientists improve side vision capabilities in AI modules.

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, UncategorizedJune 17, 202440Views0Likes0Comments
Researchers from MIT have developed an image dataset that simulates peripheral vision in machine learning models, improving their object detection capabilities. However, even with this modification, the AI models still fell short of human performance. The researchers discovered that size and visual clutter, factors that impact human performance, largely did not affect the AI's ability.…

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Three Inquiries: Essential Information on Audio Deepfakes You Should Understand

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, UncategorizedJune 17, 202436Views0Likes0Comments
Audio deepfakes have recently been in the news, particularly in regards to their negative impacts, such as fraudulent robocalls pretending to be Joe Biden, encouraging people not to vote. These malicious uses could negatively affect political campaigns, financial markets, and lead to identity theft. However, Nauman Dawalatabad, a postdoc student at MIT, argues that deepfakes…

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Scientists improve the side vision capabilities in artificial intelligence models.

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, UncategorizedJune 16, 202434Views0Likes0Comments
Peripheral vision, most humans' mechanism to see objects not directly in their line of sight, although with less detail, does not exist in AI. However, researchers at MIT have made significant progress towards this by developing an image dataset to simulate peripheral vision in machine learning models. The research indicated that models trained with this…

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Three Queries: Essential Information Regarding Deepfakes in the Audio Realm

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, UncategorizedJune 16, 202433Views0Likes0Comments
Nauman Dawalatabad, a postdoctoral researcher discusses the concerns and potential benefits of audio deepfake technology in a Q&A with MIT News. He addresses ethical considerations regarding the concealment of a source speaker’s identity in audio deepfakes, noting that speech contains a wealth of sensitive personal information beyond identity and content, such as age, gender and…

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Scientists improve sideline sight in AI prototypes.

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, UncategorizedJune 16, 202438Views0Likes0Comments
MIT researchers are replicating peripheral vision—a human's ability to detect objects outside their direct line of sight—in AI systems, which could enable these machines to more effectively identify imminent dangers or predict human behavior. By equipping machine learning models with an extensive image dataset to imitate peripheral vision, the team found these models were better…

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Three Inquiries: Essential Information on Audio Deepfakes You Should Know

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, UncategorizedJune 16, 202436Views0Likes0Comments
Recently, an AI-generated robocall mimicking Joe Biden urged New Hampshire residents not to vote. Meanwhile, "spear-phishers" – phishing campaigns targeting specific people or groups – are using audio deepfakes to extract money. However, less attention has been paid to how audio deepfakes could positively impact society. Postdoctoral fellow Nauman Dawalatabad does just that in a…

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Scientists improve sideline viewing capabilities 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, UncategorizedJune 15, 202434Views0Likes0Comments
Peripheral vision, the ability to see objects outside of our direct line of sight, has been simulated by researchers at MIT to be used with AI technology. Unlike human vision, AI lacks the capability to perceive peripherally. Enhancing AI with this ability could greatly enhance its proactivity in identifying threats, and could even predict if…

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Three Queries: Essential Information on Audio Deepfakes You Should Understand

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, UncategorizedJune 15, 202436Views0Likes0Comments
Audio deepfakes, or AI-generated audio, have lately been in the limelight due to harmful deception applied by ill-intentioned individuals. Cases such as robocalls impersonating political figures, spear-phishers tricking individuals into revealing personal information, and actors misusing technology to preserve their voices have surfaced in the media. While these negative instances have been widely publicized, MIT…

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Scientists improve side vision capabilities 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, UncategorizedJune 15, 202436Views0Likes0Comments
A team from MIT has created an image dataset aimed at simulating peripheral vision in machine learning models, a characteristic which AI typically lacks. This could improve the models' ability to recognise approaching threats and predict whether a human driver would spot an oncoming object. In experiments, these models improved in terms of hazard detection,…

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Three Inquiries: Essential Information you must Understand about 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, UncategorizedJune 15, 202435Views0Likes0Comments
In this Q&A article for MIT News, postdoc Nauman Dawalatabad discusses the ethical considerations, challenges, and positive impacts of audio deepfakes - the AI-generated audio that can mimic human voices. Recently, the technology has been misused causing public concern, for example, a robocall imitating Joe Biden’s voice instructed New Hampshire residents not to vote, while…

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This method enhances the problem-solving abilities of extensive language models.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, Programming, Research, School of Engineering, UncategorizedJune 14, 202433Views0Likes0Comments
A new technique has been proposed by researchers from the Massachusetts Institute of Technology (MIT) and other institutions that allows large language models (LLMs) to solve tasks involving natural language, math and data analysis, and symbolic reasoning by generating programs. Known as natural language embedded programs (NLEPs), the approach enables a language model to create…

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