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To enhance the proficiency of an AI assistant, it is essential to commence by mapping out 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, UncategorizedJuly 29, 202433Views0Likes0Comments
Researchers at MIT and University of Washington have crafted a model for understanding the behavior of humans and machines in decision-making scenarios, even when this behavior is suboptimal due to computational constraints. The model is based on an agent's “inference budget”, predictive of future behavior derived from observations of previous actions. This model could potentially…

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This compact chip is capable of protecting user information, while also promoting effective computing 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, UncategorizedJuly 29, 202433Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that enhances the security of health-tracking apps. These apps can be slow and consume a lot of energy due to the data exchange requirements between the phone and a central server. “Machine-learning accelerators” are used to speed up such apps but…

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Julie Shah has been appointed as the leader of the Department of Aeronautics and Astronautics.

Administration, Aeronautical and astronautical engineering, Alumni/ae, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Electrical Engineering & Computer Science (eecs), Faculty, Leadership, MIT Schwarzman College of Computing, Robotics, School of Engineering, UncategorizedJuly 29, 202433Views0Likes0Comments
Julie Shah, the H.N. Slater Professor in Aeronautics and Astronautics, has been named the new head of the Department of Aeronautics and Astronautics at MIT starting May 1. With an impressive record of technical contributions in AI and robotics, Shah has established herself as a visionary leader. Her work elucidates the social, ethical, and economic…

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CompeteAI: An AI structure that comprehends the competitive behavior of extensive language model-based constituents.

AI Agents, AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 28, 202441Views0Likes0Comments
Competition is vital in shaping all aspects of human society, including economics, social structures, and technology. Traditionally, studying competition has been reliant on empirical research, which is limited due to issues with data accessibility and a lack of micro-level insights. An alternative approach, agent-based modeling (ABM), advanced from rule-based to machine learning-based agents to overcome…

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Could the Next Medical Innovation be Concealed in Simple Text? Introducing NATURAL: A Procedure for Inferring Cause and Effect from Non-Formatted Text Data in Hours, Instead of Years.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 28, 202434Views0Likes0Comments
Causal effect estimation is a vital field of study employed in critical sectors like healthcare, economics, and social sciences. It concerns the evaluation of how modifications to one variable cause changes in another. Traditional approaches for this assessment, such as randomized controlled trials (RCTs) and observational studies, often involve structured data collection and experiments, making…

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SGLang: An Organized Production Language for Enhancing the Performance of Intricate Language Model Programs

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Staff, Tech News, Technology, UncategorizedJuly 28, 202432Views0Likes0Comments
Recent advancements in large language models (LLMs) have expanded their utility by enabling them to complete a broader range of tasks. However, challenges such as the complexity and non-deterministic nature of these models, coupled with their propensity to waste computational resources due to redundant calculations, limit their effectiveness. In an attempt to tackle these issues, researchers…

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LoRA-Pro: An Innovative Machine Learning Method for Eliminating the Performance Discrepancy Between Low-Rank Adaptation and Comprehensive Fine-Tuning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 28, 202430Views0Likes0Comments
The methods of parameter-efficient fine-tuning (PEFT) are essential in machine learning as they allow large models to adapt to new tasks without requiring extensive computational resources. PEFT methods achieve this by only fine-tuning a small subset of parameters while leaving the majority of the model unchanged, aiming to make the adaptation process more efficient and…

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This article from Google DeepMind introduces Conditioned Language Policies (CLP): A system of artificial intelligence algorithms designed to optimize language models across various objectives.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 28, 202428Views0Likes0Comments
Reinforcement Learning (RL) finetuning is an integral part of programming language models (LMs) to behave in a particular manner. However, in the current digital landscape, RL finetuning has to cater to numerous aims due to diverse human preferences. Therefore, multi-objective finetuning (MOFT) has come to the forefront as a superior method to train an LM,…

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An Evaluation of Leading Libraries for Generative AI Embeddings

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 28, 202430Views0Likes0Comments
Generative AI has made significant strides in recent times, increasing the need for text embeddings which convert textual data into dense vector representations, facilitating the processing of text, images, audio, etc., by models. Different embedding libraries have come to the fore in this space, each with unique pros and cons. This article provides a comparison…

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OpenDevin: A sophisticated AI platform designed to cultivate robust AI agents that emulate the interaction methods of a human developer.

AI Agents, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Software Engineering, Staff, Tech News, Technology, UncategorizedJuly 28, 202436Views0Likes0Comments
A team of scholars from various universities and tech organizations have proposed OpenDevin, a revolutionary platform that aids in the development of AI agents capable of performing a broad range of tasks like a human software developer. Current AI algorithms often struggle with complex operations, lacking flexibility and generalization. Existing frameworks for AI development fall…

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In order to create an enhanced AI assistant, begin by mimicking the unpredictable actions of people.

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, UncategorizedJuly 28, 202431Views0Likes0Comments
Researchers at MIT and the University of Washington have developed a model that can predict an agent's potential computational limitations, and therefore their decision-making process, simply by observing past behaviour. Referred to as an "inference budget," this could enable AI systems to better predict human behaviour. The research paper demonstrates this modelling method within the…

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This small microchip can protect user information while promoting effective processing on a mobile device.

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, UncategorizedJuly 28, 202428Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a novel machine-learning accelerator that can protect sensitive data like health records from two common types of cybersecurity threats while efficiently running large AI models. This advancement could make an noticable impact on challenging AI applications, such as augmented and virtual reality, autonomous driving…

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