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Improving the dependability of language models by leveraging concepts from game theory.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Game theory, Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, Research, Robotics, School of Engineering, UncategorizedMay 15, 202432Views0Likes0Comments
Researchers from MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a new type of game to enhance how artificial intelligence (AI) comprehends and produces text. This "consensus game" includes two parts of an AI system - the part that generates sentences and a part that evaluates those sentences. This model significantly improved the…

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Improved coding, planning, and robotics performance can be attributed to the enhancement brought about by natural language.

Artificial Intelligence, Brain and cognitive sciences, Center for Brains Minds and Machines, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Defense Advanced Research Projects Agency (DARPA), Department of Defense (DoD), Electrical Engineering & Computer Science (eecs), Human-computer interaction, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Natural language processing, Programming, Programming languages, Quest for Intelligence, Research, Robotics, School of Engineering, School of Science, UncategorizedMay 2, 202440Views0Likes0Comments
Researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) presented three papers at the International Conference on Learning Representations, indicating breakthroughs in Large Language Models' (LLMs) abilities to form useful abstractions. The team used everyday words for context in code synthesis, AI planning, and robotic navigation and manipulation. The three frameworks, LILO, Ada,…

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Three Inquiries: Understanding the essentials of 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, UncategorizedMarch 16, 202442Views0Likes0Comments
Audio deepfakes, although often associated with unethical practices, have potential uses that can benefit society, suggests postdoc Nauman Dawalatabad in a Q&A with MIT News. He highlights the need for technology that protects sensitive information held within speech patterns, such as age, gender, and health conditions, stating that obscuring the speaker's identity in audio deepfakes…

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Utilizing language to comprehend machines.

Artificial Intelligence, Classes and programs, Collaboration, Data, Electrical Engineering & Computer Science (eecs), Graduate, Human-computer interaction, Industry, Linguistics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, postdoctoral, Research, School of Engineering, School of Humanities Arts and Social Sciences, Students, UncategorizedMarch 7, 202442Views0Likes0Comments
MIT engineering students Irene Terpstra ’23 and Rujul Gandhi ’22 are collaborating with the MIT-IBM Watson AI Lab to advance Artificial Intelligence (AI) systems using Natural Language Processing (NLP), taking advantage of the vast amount of natural language data available. Terpstra is focusing on the application of AI algorithms for computer chip design, leveraging the…

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Logical thinking and dependability in Artificial Intelligence

Artificial Intelligence, Communications, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Graduate, Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural language processing, postdoctoral, Research, Robotics, School of Engineering, Students, UncategorizedMarch 7, 202444Views0Likes0Comments
MIT PhD students interning at the MIT-IBM Watson AI Lab are researching ways to improve the efficiency and accuracy of AI systems in understanding and communicating through natural language. The team, including Athul Paul Jacob, Maohao Shen, Victor Butoi, and Andi Peng, aims to enhance each stage of the process involving natural language models, from…

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