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Large language models utilize a surprisingly straightforward method to access some stored information.

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, Research, School of Engineering, UncategorizedJune 20, 2024147Views0Likes0Comments
Large language models (LLMs), such as those which power AI chatbots like ChatGPT, are highly complex. While these powerful tools are used in diverse applications like customer support, code generation, and language translation, they remain somewhat of a mystery to the scientists who work with them. To develop a deeper understanding of their inner workings,…

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Large language models utilize an unexpectedly uncomplicated method to recall certain stored information.

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, Research, School of Engineering, UncategorizedJune 20, 2024178Views0Likes0Comments
Large language models (LLMs) that power artificial intelligence chatbots like ChatGPT are extremely complex and their functioning isn't fully understood. These LLMs are used in a variety of areas such as customer support, code generation and language translation. However, researchers from MIT and other institutions have made strides in understanding how these models retrieve stored…

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The MIT-Takeda Program concluded with 16 research papers, a patent, and almost 24 projects successfully completed.

Artificial Intelligence, Awards, Classes and programs, Collaboration, Data, Drug development, Electrical Engineering & Computer Science (eecs), Faculty, Graduate, Health care, Health sciences and technology, honors and fellowships, Jameel Clinic, Machine learning, Medicine, MIT Schwarzman College of Computing, Pharmaceuticals, postdoctoral, School of Engineering, Special events and guest speakers, Students, SuperUROP, UncategorizedJune 19, 2024162Views0Likes0Comments

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Comprehending the visual comprehension of language models.

Artificial Intelligence, 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, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedJune 18, 2024181Views0Likes0Comments
Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) has revealed that language models without image experience still understand the visual world. The team found that even without seeing images, language models could write image-rendering code that could generate detailed and complicated scenes. The knowledge that enabled this process came from the vast…

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Scientists improve the peripheral vision capabilities in AI 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 17, 2024209Views0Likes0Comments
Researchers at Massachusetts Institute of Technology (MIT) have developed an image dataset to simulate peripheral vision in artificial intelligence (AI) models. This step is aimed at helping such models detect approaching dangers more effectively, or predict whether a human driver would take note of an incoming object. Peripheral vision in humans allows us to see…

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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, 2024208Views0Likes0Comments
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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Improving software testing through the application 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 17, 2024182Views0Likes0Comments
Generative AI, renowned for its capability to autonomously produce text and images, plays a crucial role in creating realistic synthetic data from diverse scenarios, helping organizations optimize operations. A notable initiative in the field is the Synthetic Data Vault (SDV), developed by DataCebo, an MIT spinoff. This generative system aids organizations in creating synthetic data…

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