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To enhance your AI assistant, begin by simulating the unpredictable conduct 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 new way to model human behaviour by accounting for unknown computational constraints that may impact problem-solving abilities. This new model enables an agent, human or machine, to infer another agent's computational constraints from their previous actions. The resulting 'inference budget' can be used to…

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This small microchip can protect user information while also facilitating effective 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, UncategorizedJuly 28, 202431Views0Likes0Comments
Researchers from the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator designed to be resistant to cyber-attacks, offering a secure platform for health-monitoring applications. The chip secures users' data whilst running large artificial intelligence (AI) models efficiently, protecting sensitive health and financial information. The technology is capable of…

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FLUTE: A CUDA Kernel Formulated for Compound Quantized Matrix Multiplications to Speed Up LLM Inference

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 27, 202428Views0Likes0Comments
Large Language Models (LLMs) face several deployment challenges including latency issues triggered by memory bandwidth constraints. To mitigate such problems, researchers have resorted to applying weight-only quantization, a technique that compresses the parameters of LLMs to lower precision. Nevertheless, to effectively implement weight-only quantization, it is necessary to employ mixed-type matrix-multiply kernels that can manage,…

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PRISE: An Exclusive Machine Learning Approach for Multitask Time-Bound Action Comprehension Utilizing Natural Language Processing (NLP)

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 27, 202428Views0Likes0Comments
In the dynamic and complex field of robotics, decision-making often involves managing continuous action spaces and processing high volumes of data. This scenario demands sophisticated methodologies to handle the information efficiently and translate it into meaningful action. To address this challenge, researchers from the University of Maryland, College Park, and Microsoft Research have proposed a…

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The Intersection of Theory of Mind and Language Models: Conceptualizing Minds for Sophisticated Multi-Agent Activities

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 27, 202427Views0Likes0Comments
Artificial intelligence (AI) is continually evolving, with a significant challenge being the creation of systems that can effectively collaborate in dynamic environments. One area of focus in this regard is multi-agent reinforcement learning (MARL), which aims to teach agents to interact and adapt in these settings. However, these methods struggle with complexity and adaptability, especially…

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The Eindhoven University of Technology has published a revolutionary Deep Learning Paper, introducing Nerva: A New Sparse Neural Network Library that significantly improves efficiency and performance.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 27, 202429Views0Likes0Comments
Deep learning's exceptional performance across a wide range of scientific fields and its utilization in various applications have been proven. However, these models often come with many parameters that require a substantial amount of computational power for training and testing. The improvement of these models has been a primary focus of advancement in the field,…

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AlphaProof and AlphaGeometry-2 by Google’s DeepMind Successfully Tackle Complex Mathematical Reasoning Challenges

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 27, 202437Views0Likes0Comments
Google DeepMind's AI systems AlphaProof and AlphaGeometry 2 have achieved a silver medal-level score at the 2024 International Mathematical Olympiad (IMO), a highly prestigious competition for budding mathematicians worldwide. Despite competing against 609 contestants, the AI models secured rankings among the top 58, by resolving four of the six difficult math problems, earning 28…

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To construct an improved AI assistant, initiate by emulating the unpredictable actions of humans.

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 27, 202432Views0Likes0Comments
Researchers at MIT and the University of Washington have developed a computational model that can predict an intelligent agent's behaviors based on its "inference budget" (i.e. the limits on its computational resources). This was accomplished by using an algorithm that recorded all the decisions made by the agent within a given period of time. They…

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This small microchip can protect user information while facilitating effective 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, UncategorizedJuly 27, 202431Views0Likes0Comments
Health-monitoring applications have become pivotal in managing chronic diseases and tracking fitness goals, largely due to the advent of machine-learning powered tools. However, these applications are often slow and energy-inefficient, largely due to the massive machine-learning models that require transfer between a smartphone and a central memory server. Despite the development of machine-learning accelerators that…

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To improve the creation of AI assistants, begin by imitating the unpredictable actions of humans.

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 27, 202430Views0Likes0Comments
Researchers at MIT and the University of Washington have devised a model to predict the behaviour of AI systems and humans. The model factors in the indefinite computational constraints which may hinder an agent's problem-solving skills. By analysing only a few instances of previous actions, the model can predict an agent's future behaviour. The findings…

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To enhance the development of more effective AI assistants, consider simulating the unpredictable actions of humans as a starting point.

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 27, 202432Views0Likes0Comments
To build an Artificial Intelligence (AI) system that can work effectively with humans, it's critical to have an accurate model of human behavior. However, humans often act less optimally when making decisions, and these irrational behaviors are challenging to imitate. This is due to computational constraints - a person cannot dedicate decades to finding an…

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