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This small microchip can protect user information and simultaneously promote efficient processing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedAugust 6, 202473Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that can resist the two most common types of cyberattacks while maintaining the functionality of large Artificial Intelligence (AI) models, according to senior author Anantha Chandrakasan, MIT’s chief innovation and strategy officer, dean of the School of Engineering, and the Vannevar…

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A dataset based on AI paves the way for innovative tornado detection methods.

Algorithms, Artificial Intelligence, Climate change, Data, Disaster response, Lincoln Laboratory, Machine learning, Natural disasters, Radar, Research, Technology and society, Uncategorized, Weather, Weather modelingAugust 6, 202437Views0Likes0Comments
Researchers at MIT Lincoln Laboratory have introduced an open-source dataset called TorNet in an attempt to enable enhanced detection and prediction of tornadoes. The dataset comprises radar returns from thousands of tornadoes that struck the US over the past decade and includes copies of storms that generated tornadoes as well as other extreme weather events…

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Speedier LLMs through theoretical deciphering and AWS Inferentia2.

AI/ML, Amazon Machine Learning, Artificial Intelligence, AWS Inferentia, Generative AI, Machine learning, Technical How-to, UncategorizedAugust 6, 202436Views0Likes0Comments
Large language models (LLMs), used to solve natural language processing (NLP) tasks, have seen a significant increase in their size. This increase dramatically improves the model's performance, with larger models scoring better on tasks such as reading comprehension. However, these larger models require more computation and are more costly to deploy. The role of larger models…

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LlamaIndex Processes: A Stimulus-Based Strategy for Managing Intricate AI Applications

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202439Views0Likes0Comments
Artificial intelligence (AI) applications are becoming increasingly complicated, involving multiple interactive tasks and components that must be coordinated for effective and efficient performance. Traditional methods of managing this complex orchestration, such as Directed Acyclic Graphs (DAGs) and query pipelines, often fall short in dynamic and iterative processes. To overcome these limitations, LlamaIndex has introduced…

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Safety Standards for AI May Not Guarantee Real Safety: This AI Study Uncovers the Concealed Dangers of Overstating Safety Measures

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202436Views0Likes0Comments
Artificial Intelligence (AI) safety continues to become an increasing concern as AI systems become more powerful. This has led to AI safety research aiming to address the imminent and future risks through the development of benchmarks to measure safety properties such as fairness, reliability, and robustness. However, these benchmarks are not always clear in defining…

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ARCLE: An Abstract Reasoning Challenge Platform Utilizing Reinforcement Learning Environment

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202435Views0Likes0Comments
As an area of Artificial Intelligence (AI), Reinforcement Learning (RL) enables agents to learn by interacting with their environment and making decisions that maximize their cumulative rewards over time. This learning approach is especially useful in robotics and autonomous systems due to its focus on trial and error learning. However, RL faces challenges in situations…

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To enhance an AI assistant, begin by mirroring the unpredictable actions of individuals.

Algorithms, Artificial Intelligence, Computer modeling, 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, National Science Foundation (NSF), Research, School of Engineering, UncategorizedAugust 5, 202437Views0Likes0Comments
Researchers from MIT and the University of Washington have developed a model to predict the behavior of human and artificial intelligence (AI) agents, taking into account computational constraints. The model automatically deduces these constraints by processing previous actions of the agent. This "inference budget" can help predict future behavior of the agent; for instance, it…

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Begin developing an improved AI assistant by emulating the unpredictable actions of human beings.

Algorithms, Artificial Intelligence, Computer modeling, 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, National Science Foundation (NSF), Research, School of Engineering, UncategorizedAugust 5, 202434Views0Likes0Comments
Researchers at the Massachusetts Institute of Technology (MIT) and the University of Washington have developed a model that accounts for the computational constraints often experienced by decision-making agents, both human and machine. This model auto-infers an agent's computational restrictions by analysing traces of past actions, which, in turn, can be used to predict future behaviour. In…

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This small microchip can protect user information yet still allow for proficient processing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedAugust 5, 202474Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that provides security against the two most common types of attacks. This chip can keep sensitive data, such as health records or financial information, private while allowing AI models to run efficiently on devices. The increased security doesn't affect the accuracy…

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A dataset for artificial intelligence paves novel ways for identifying tornadoes.

Algorithms, Artificial Intelligence, Climate change, Data, Disaster response, Lincoln Laboratory, Machine learning, Natural disasters, Radar, Research, Technology and society, Uncategorized, Weather, Weather modelingAugust 5, 202438Views0Likes0Comments
Springtime in the Northern Hemisphere marks the onset of tornado season, and while the dust and debris-filled spiral of a tornado may seem an unmistakable sight, these violent weather phenomena often evade detection until it's too late. Recognizing the need for better ways of predicting these occurrences, researchers at MIT Lincoln Laboratory have compiled a…

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ReSi Benchmark: An All-inclusive Assessment Structure for Neural Network Representation Parallels Across Various Spheres and Frameworks

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedAugust 5, 202435Views0Likes0Comments
Representational similarity measures are essential instruments in machine learning as they facilitate the comparison of internal representations of neural networks, aiding researchers in understanding how various neural network layers and architectures process information. These measures are vital for understanding the performance, behavior, and learning dynamics of a model. However, the development and application of these…

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