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Scientists improve the peripheral vision capabilities in AI models.

Artificial Intelligence, Autonomous vehicles, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, UncategorizedJune 17, 202447Views0Likes0Comments
Researchers at Massachusetts Institute of Technology (MIT) have developed an image dataset to simulate peripheral vision in artificial intelligence (AI) models. This step is aimed at helping such models detect approaching dangers more effectively, or predict whether a human driver would take note of an incoming object. Peripheral vision in humans allows us to see…

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Three inquiries: Understanding the essentials about 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, UncategorizedJune 17, 202443Views0Likes0Comments
The recent misuse of audio deepfakes, including a robocall purporting to be Joe Biden in New Hampshire and spear-phishing campaigns, has prompted questions about the ethical considerations and potential benefits of this emerging technology. Nauman Dawalatabad, a postdoctoral researcher, discussed these concerns in a Q&A prepared for MIT News. According to Dawalatabad, the attempt to obscure…

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AI Implementation in Healthcare: An Exploration, Understanding and Application Journey

Adoption, C-Suite, Education, Health System Optimization, UncategorizedJune 17, 202435Views0Likes0Comments
The use of Artificial Intelligence (AI) in healthcare started as early as the 1970s, but its significant transformative power was only widely recognized in the last decade. The scope and capabilities of AI is being pushed and innovated by numerous players in the healthcare sector. Despite the promising advances, spectators are questioning the true impact…

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Researchers at Google DeepMind have suggested a new and unique approach to Monte Carlo Tree Search (MCTS) Algorithm called ‘OmegaPRM’. This innovative method, which utilizes a divide-and-conquer style, aims at effectively gathering superior quality data for process monitoring.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 17, 202456Views0Likes0Comments
Artificial intelligence (AI) with large language models (LLMs) have made major strides in several sophisticated applications, yet struggle with tasks that require complex, multi-step reasoning such as solving mathematical problems. Improving their reasoning abilities is vital for improving their efficiency on such tasks. LLMs often fail when dealing with tasks requiring logical steps and intermediate-step…

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OpenVLA: An Open-Source VLA with 7 Billion Parameters, Redefining the Benchmark for Robotic Handling Strategies

AI Shorts, Artificial Intelligence, Editors Pick, Robotics, Staff, Tech News, Technology, UncategorizedJune 17, 202440Views0Likes0Comments
Robotic manipulation policies are currently limited by their inability to extrapolate beyond their training data. While these policies can adapt to new situations, such as different object positions or lighting, they struggle with unfamiliar objects or tasks, and require assistance to process unseen instructions. Promisingly, vision and language foundation models, like CLIP, SigLIP, and Llama…

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BiGGen Bench: A Gauge Developed to Assess Nine Fundamental Abilities of Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 17, 202435Views0Likes0Comments
The evaluation of Large Language Models (LLMs) requires a systematic and multi-layered approach to accurately identify areas of improvement and limitations. As these models advance and become more intricate, their assessment presents greater challenges due to the diversity of tasks they are required to execute. Current benchmarks often employ non-precise, simplistic criteria such as "helpfulness"…

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Pioneering Methods in Machine Unlearning: Understanding and Discoveries from the inaugural NeurIPS Unlearning Contest on Effective Data Deletion

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 17, 202433Views0Likes0Comments
Machine unlearning refers to the efficient elimination of specific training data's influence on a trained AI model. It addresses legal, privacy, and safety issues arising from large, data-dependent AI models. The primary challenge is to eliminate specific data without the expensive and time-consuming approach of retraining the model from scratch, especially for complex deep neural…

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The Allen Institute for AI Unveils Tulu 2.5 Suite on Hugging Face: Sophisticated AI Models Educated using DPO and PPO, Incorporating Reward and Value Models.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 17, 202435Views0Likes0Comments
The Allen Institute for AI has recently launched the Tulu 2.5 suite, a revolutionary progression in model training employing Direct Preference Optimization (DPO) and Proximal Policy Optimization (PPO). The suite encompasses an array of models that have been trained on several datasets to augment their reward and value models, with the goal of significantly enhancing…

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Algorithmic Neural Reasoning Framework for Transformers: The TransNAR Model

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 17, 202427Views0Likes0Comments
DeepMind researchers have presented TransNAR, a new hybrid architecture which pairs the language comprehension capabilities of Transformers with the robust algorithmic abilities of pre-trained graph neural networks (GNNs), known as neural algorithmic reasoners (NARs. This combination is designed to enhance the reasoning capabilities of language models, while maintaining generalization capacities. The routine issue faced by…

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Overcoming the Obstacles of Selective Categorization under Differential Privacy: A Practical Research Investigation.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 17, 202437Views0Likes0Comments
Machine learning is a crucial domain where differential privacy (DP) and selective classification (SC) play pivotal roles in safeguarding sensitive data. DP adds random noise to protect individual privacy while retaining the overall utility of the data, while SC chooses to refrain from making predictions in cases of uncertainty to enhance model reliability. These components…

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Improving software testing through the application of generative artificial intelligence.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 17, 202439Views0Likes0Comments
Generative AI, renowned for its capability to autonomously produce text and images, plays a crucial role in creating realistic synthetic data from diverse scenarios, helping organizations optimize operations. A notable initiative in the field is the Synthetic Data Vault (SDV), developed by DataCebo, an MIT spinoff. This generative system aids organizations in creating synthetic data…

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