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Assessing AI Model Safety via Red Teaming Method: An In-depth Analysis of LLM and MLLM’s Resilience to Jailbreak Assaults and Prospective Enhancements

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 7, 202437Views0Likes0Comments
Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) are key advancements in artificial intelligence (AI) capable of generating text, interpreting images, and understanding complex multimodal inputs, mimicking human intelligence. However, concerns arise due to their potential misuse and vulnerabilities to jailbreak attacks, where malicious inputs trick the models into generating harmful or objectionable…

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The automated platform instructs users on the appropriate instances to engage with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 7, 202435Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a method of teaching users when to collaborate with an artificial intelligence (AI) assistant. The model creates a customised onboarding process, educating users on when to trust or ignore an AI model’s advice. The training process can detect situations where the AI model is…

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The team from MIT has published reports on the management of AI.

Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Government, Machine learning, MIT Schwarzman College of Computing, Policy, School of Engineering, Technology and society, UncategorizedApril 7, 202443Views0Likes0Comments
A committee consisting of leaders and scholars from the Massachusetts Institute of Technology (MIT) have released policy briefs that provide a blueprint for governing artificial intelligence (AI) in the U.S. The committee believes that existing regulatory and liability processes can be extended to regulate AI in the U.S. The goal is to strengthen U.S. leadership…

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A software engineer advances the limits of geometric study.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedApril 7, 202436Views0Likes0Comments
Justin Solomon is an associate professor in the MIT Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory who is using geometric techniques to solve complex problems in data science and artificial intelligence, among other areas. These techniques draw upon the geometric structures within datasets to…

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Bridging the gap between design and production for optical instruments.

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 7, 202434Views0Likes0Comments
Photolithography, the technique of etching features onto a surface using light manipulation, is commonly used in the manufacturing of computer chips and optical devices. However, small deviations during the manufacturing process often impact the performance of the finished product. To address this, researchers from MIT and the Chinese University of Hong Kong have leveraged machine…

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Deep neural networks exhibit potential as representations of human auditory perception.

Artificial Intelligence, Brain and cognitive sciences, Hearing, Machine learning, McGovern Institute, National Institutes of Health (NIH), Research, School of Science, UncategorizedApril 7, 202434Views0Likes0Comments
MIT researchers have found that computational models based on machine learning that simulate the human auditory system are drawing closer to potentially helping in the creation of improved hearing aids, cochlear implants and brain-machine interfaces. The study is the most comprehensive comparison so far made between these computer models and the human auditory system. Notably,…

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The Function of Transformers in Natural Language Processing – Training Large Language Models (LLMs) with Transformers, How Does it Work?

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, Tutorials, UncategorizedApril 7, 202434Views0Likes0Comments
Transformers have revolutionized Natural Language Processing (NLP) with Large Language Models (LLMs), such as OpenAI's GPT series, BERT, and Claude series, etc. The advancement of Transformer Architecture brought about a new way of building models designed to understand and accurately generate human language. The Transformer Model was introduced in 2017 through a research paper titled "Attention…

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Google DeepMind Introduces Mixture-of-Depths: Fine-Tuning Transformer Models for Adaptable Resource Management and Improved Computation Efficiency

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedApril 7, 202438Views0Likes0Comments
The transformer model has become a crucial technical component in AI, transforming areas such as language processing and machine translation. Despite its success, a common criticism is its standard method of uniformly assigning computational resources across an input sequence, failing to acknowledge the varying computational demands of different parts of a data sequence. This simplified…

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The automated system guides users on when to partner with an artificial intelligence assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 7, 202437Views0Likes0Comments
Researchers at the Massachusetts Institute of Technology and the MIT-IBM Watson AI Lab have developed an onboarding system that trains humans when and how to collaborate with Artificial Intelligence (AI). The fully automated system learns to customize the onboarding process according to the tasks performed, making it usable across a variety of scenarios where AI…

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The team from MIT publishes research articles discussing AI’s governance.

Artificial Intelligence, Computer science and technology, Electrical Engineering & Computer Science (eecs), Government, Machine learning, MIT Schwarzman College of Computing, Policy, School of Engineering, Technology and society, UncategorizedApril 7, 202437Views0Likes0Comments
A group of scholars and leaders from MIT has developed policy briefs to establish a governance framework for artificial intelligence (AI). The briefs are intended to assist U.S. policymakers, sustain the country's leadership position in AI, limit potential risks from new technologies, and explore how AI can benefit society. The primary policy paper, "A Framework for…

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A computing expert is expanding the frontiers of geometric studies.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Faculty, Machine learning, MIT Schwarzman College of Computing, Profile, School of Engineering, UncategorizedApril 7, 202433Views0Likes0Comments
Over 2,000 years after Euclid's groundbreaking work in geometry, MIT associate professor Justin Solomon is using the ancient principles in fresh, modern ways. Solomon's work in the Geometric Data Processing Group applies geometry to solve a variety of problems, from comparing datasets in machine learning to enhancing generative AI models. His work assumes a variety…

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Bridging the gap between design and production for optical instruments

Artificial Intelligence, Biological engineering, Computer science and technology, Electronics, Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT.nano, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedApril 7, 202433Views0Likes0Comments
Researchers at MIT and the Chinese University of Hong Kong have developed a machine learning tool to emulate photolithography manufacturing processes. Photolithography is commonly used in the production of computer chips and optical devices, manipulating light to etch features onto surfaces. Variations in the manufacturing process can cause the end products to deviate from their…

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