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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, 202437Views0Likes0Comments
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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Improving software testing by utilizing generative AI

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 15, 202436Views0Likes0Comments
Generative AI, which can create text and images, also has extensive potential in creating realistic synthetic data for various applications. Being able to produce synthetic data can assist organizations, particularly in situations where real-world data is lacking or sensitive. For instance, it can help in patient care, rerouting of flights due to adverse weather, or…

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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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Improving software testing with the use of generative artificial intelligence.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 15, 202434Views0Likes0Comments
Generative AI has the capability to produce realistic synthetic data that could help organizations in various sectors such as healthcare, aviation, and software development efficiently carry out operations. For the last three years, MIT spinout DataCebo has been offering the Synthetic Data Vault (SDV), a generative software system that can design synthetic data, useful in…

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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, 202436Views0Likes0Comments
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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Improving software testing through the use of generative artificial intelligence.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 14, 202435Views0Likes0Comments
Generative AI, recognized mainly for its ability in creating text and images, is now used by companies to create synthetic data for various scenarios aiding in patient treatment, plane rerouting, and software improvements especially in situations that lack real-world data or require sensitive data. DataCebo, an MIT spinoff, has invented a generative software system called…

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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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Enhancing software testing through the application of generative AI.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 14, 202432Views0Likes0Comments
Generative AI, in the past few years, has gained significant popularity because of its capacity to develop realistic text and images. However, the created text and images form only a portion of the data generated today. Every interaction we have with a medical system, software application, or the effect of any environment, such as a…

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Improving software testing through the application of generative AI.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 13, 202437Views0Likes0Comments
Generative AI is increasingly being utilized to generate synthetic data, enhancing organizations' abilities to deal with situations where actual data may be limited or sensitive. Over the past three years, DataCebo, an MIT spinoff initiative, has been offering a generative software system known as the Synthetic Data Vault (SDV) to enable organizations to create synthetic…

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