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Scientists at the University College London decoded the common operations of representation learning in deep neural networks.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202428Views0Likes0Comments
Deep neural networks (DNNs) are diverse in size and structure, and their performance heavily depends on their architecture, the dataset and learning algorithm used. However, even the simplest adjustment to the network's structure necessitates substantial modifications to the analysis. Modern models are so intricate that they tend to surpass practical analytical solutions, making their theoretical…

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Researchers from MIT present a generative artificial intelligence for databases.

Algorithms, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, School of Science, UncategorizedJuly 8, 202434Views0Likes0Comments
GenSQL, a new AI tool developed by scientists at MIT, is designed to simplify the complex statistical analysis of tabular data, enabling users to readily understand and interpret their databases. To this end, users don't need to grasp what is happening behind the scenes to develop accurate insights. The system's capabilities include making predictions, identifying anomalies,…

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Salesforce is pushing the boundaries in AI trends through the compact but powerful xLAM-1B and 7B models.

Industry, Machine learning, UncategorizedJuly 8, 202436Views0Likes0Comments
Enterprise software giant Salesforce has introduced two compact AI models, the 1-billion and 7-billion parameter xLAM models, which have notably challenged the prevalent “bigger is better” approach in artificial intelligence. Despite their smaller size, these models surpass many more extensive models on function-calling tasks, a process where AI interprets and translates natural language requests into…

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Improving Efficiency and Performance in Multi-Task Reinforcement Learning through Policy Learning with Extensive World Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202431Views0Likes0Comments
Researchers from the Georgia Institute of Technology and the University of California, San Diego, have introduced an innovative model-based reinforcement learning algorithm called Policy learning with Large World Models (PWM). Traditional reinforcement learning methods have faced difficulties with multitasking, especially across different robotic forms. PWM tackles these issues by pretraining world models on offline data,…

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MIT scholars researching generative AI’s implications and uses received the second round of seed fund allocations.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 8, 202440Views0Likes0Comments
MIT President Sally Kornbluth and Provost Cynthia Barnhart last year issued a call for papers with the aim of developing effective strategies, policy recommendations, and calls to action in the field of generative artificial intelligence (AI). The response was overwhelming, with a total of 75 proposals submitted. Out of these, 27 were selected for seed…

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MIT researchers studying the implications and uses of generative AI receive a second phase of seed funds.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 7, 202432Views0Likes0Comments
Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart issued a call for papers on generative artificial intelligence (AI). They sought effective roadmaps, policy recommendations, and calls for action in the AI field, and received 75 proposals. Out of these, 27 were selected for seed funding. Due to the robust response to this initial funding…

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Researchers at DeepSeek AI have suggested implementing Expert-Specialized Fine-Tuning (ESFT) as a way to cut down memory usage by as much as 90% and reduce processing time by up to 30%.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 7, 202433Views0Likes0Comments
Natural language processing has been making significant headway recently, with a special focus on fine-tuning large language models (LLMs) for specified tasks. These models typically comprise billions of parameters, hence customization can be a challenge. The goal is to devise more efficient methods that customize these models to particular downstream tasks without overwhelming computational costs.…

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Researchers from DeepSeek AI have introduced ESFT, also known as Expert-Specialized Fine-Tuning, which is projected to decrease memory usage by up to 90% and save time by up to 30%.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 7, 202429Views0Likes0Comments
The rapid evolution of natural language processing (NLP) is currently focused on refining large language models (LLMs) for specific tasks, which often contain billions of parameters posing a significant challenge for customization. The primary goal is to devise better methods to fine-tune these models to particular downstream tasks with minimal computational costs, posing a need…

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MIT researchers studying the effects and uses of generative AI have received a second round of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 7, 202437Views0Likes0Comments
MIT President, Sally Kornbluth, and Provost, Cynthia Barnhart, recently solicited research proposals on the topic of generative artificial intelligence (AI). The response was overwhelming, with 75 proposals submitted from across MIT. Consequently, due to the level of interest and quality of the proposals, a second call for papers was announced, which led to an additional…

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Examining the Extensive Abilities and Ethical Framework of Anthropic’s Premier Language Model, Claude AI: A Detailed Review

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202443Views0Likes0Comments
Introduced by an AI-focused startup Anthropic, Claude AI is a high-performing large language model (LLM) boasting advanced capabilities and a unique approach to training known as "Constitutional AI." Co-founded by former OpenAI employees, Anthropic adheres to a rigorous ethical AI framework and is supported by industry heavyweights such as Google and Amazon. Claude AI, launched in…

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Examining and Improving Model Efficiency for Tabular Data with XGBoost and Ensembles: A Step Further than Deep Learning

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202435Views0Likes0Comments
Model selection is a critical part of addressing real-world data science problems. Traditionally, tree ensemble models such as XGBoost have been favored for tabular data analysis. However, deep learning models have been gaining traction, purporting to offer superior performance on certain tabular datasets. Recognising the potential inconsistency in benchmarking and evaluation methods, a team of…

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Princeton University scientists uncover concealed expenses linked with advanced AI Agents.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 6, 202438Views0Likes0Comments
Research out of Princeton University makes a critical commentary on the current practice of evaluating artificial intelligence (AI) agents predominantly based on accuracy. The researchers argue that this unidimensional evaluation method leads to unnecessarily complex and costly AI agent architectures, which can hinder practical implementations. The evaluation paradigms for AI agents have traditionally focused on…

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