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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, 202438Views0Likes0Comments
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, 202438Views0Likes0Comments
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, 202437Views0Likes0Comments
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, 202436Views0Likes0Comments
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, 202434Views0Likes0Comments
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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Startup advances the journey towards computing at the speed of light.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 13, 202439Views0Likes0Comments
In today's digital era, the demand for ever-increasing computing power has been overwhelmingly huge, driven primarily by advancements in artificial intelligence. However, the constant innovation in computing technology is facing obstacles, primarily due to the limitations in the shrinking size of transistors used in chips. This imposes a strict limit on Moore's Law and Dennard's…

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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, 202439Views0Likes0Comments
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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Researchers utilize extensive language models to assist robots with navigation.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robotics, Robots, School of Engineering, UncategorizedJune 12, 202433Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a language-based navigational strategy for AI robots. The method uses textual descriptions instead of visual information, effectively simplifying the process of robotic navigation. Visual data traditionally requires significant computational capacity and detailed hand-crafted machine-learning models to function effectively. The researchers' approach involves converting a…

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A novel approach to computer vision accelerates the screening process of electronic components.

3-D printing, Algorithms, Artificial Intelligence, Automation, Computer vision, Imaging, Machine learning, Materials science and engineering, Mechanical engineering, Renewable energy, Research, School of Engineering, Solar, Sustainability, UncategorizedJune 12, 202436Views0Likes0Comments
Solar cells, transistors, LEDs, and batteries with boosted performance require better electronic materials which are often discovered from novel compositions. Scientists have turned to AI tools to identify potential materials from millions of chemical formulations, with engineers developing machines that can print hundreds of samples at a time, based on compositions identified by AI algorithms.…

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