Machine Learning

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Study: AI chatbots provide less-accurate information to vulnerable users

ai, AI (Artificial Intelligence), Artificial Intelligence, data, ethics, Machine Learning, Media Lab, MIT Sloan School of Management, Research, School of Architecture and Planning

Large language models (LLMs) have been championed as tools that could democratize access to information worldwide, offering knowledge in a user-friendly interface regardless of a person’s background or location. However, new research from MIT’s Center for Constructive Communication (CCC) suggests these artificial intelligence systems may actually perform worse for the very users who could most […]

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Google AI Releases Gemini 3.1 Pro with 1 Million Token Context and 77.1 Percent ARC-AGI-2 Reasoning for AI Agents

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, RAG, Tech News, Technology

Google has officially shifted the Gemini era into high gear with the release of Gemini 3.1 Pro, the first version update in the Gemini 3 series. This release is not just a minor patch; it is a targeted strike at the ‘agentic’ AI market, focusing on reasoning stability, software engineering, and tool-use reliability. For devs,

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Exposing biases, moods, personalities, and abstract concepts hidden in large language models

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, data, Machine Learning, Mathematics, Research, School of Science, Software

By now, ChatGPT, Claude, and other large language models have accumulated so much human knowledge that they’re far from simple answer-generators; they can also express abstract concepts, such as certain tones, personalities, biases, and moods. However, it’s not obvious exactly how these models represent abstract concepts to begin with from the knowledge they contain.Now a

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Zyphra Releases ZUNA: A 380M-Parameter BCI Foundation Model for EEG Data, Advancing Noninvasive Thought-to-Text Development

ai, AI (Artificial Intelligence), AI Paper Summary, AI Shorts, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, New Releases, Small Language Model, Staff, Tech News, Technology

Brain-computer interfaces (BCIs) are finally having their ‘foundation model’ moment. Zyphra, a research lab focused on large-scale models, recently released ZUNA, a 380M-parameter foundation model specifically for EEG signals. ZUNA is a masked diffusion auto-encoder designed to perform channel infilling and super-resolution for any electrode layout. This release includes weights under an Apache-2.0 license and

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Parking-aware navigation system could prevent frustration and emissions

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Cities, Civil and environmental engineering, Climate change, Computer modeling, Computer science and technology, Electrical engineering and computer science (EECS), Emissions, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Energy Initiative, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, Sustainability, Transportation

It happens every day — a motorist heading across town checks a navigation app to see how long the trip will take, but they find no parking spots available when they reach their destination. By the time they finally park and walk to their destination, they’re significantly later than they expected to be.Most popular navigation

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Tavus Launches Phoenix-4: A Gaussian-Diffusion Model Bringing Real-Time Emotional Intelligence And Sub-600ms Latency To Generative Video AI

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The ‘uncanny valley’ is the final frontier for generative video. We have seen AI avatars that can talk, but they often lack the soul of human interaction. They suffer from stiff movements and a lack of emotional context. Tavus aims to fix this with the launch of Phoenix-4, a new generative AI model designed for

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Personalization features can make LLMs more agreeable

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), ethics, Human-computer interaction, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

Many of the latest large language models (LLMs) are designed to remember details from past conversations or store user profiles, enabling these models to personalize responses.But researchers from MIT and Penn State University found that, over long conversations, such personalization features often increase the likelihood an LLM will become overly agreeable or begin mirroring the

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Anthropic Releases Claude 4.6 Sonnet with 1 Million Token Context to Solve Complex Coding and Search for Developers

agentic ai, ai, AI (Artificial Intelligence), AI Agents, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Generative AI, Language Model, Large Language Model, Machine Learning, New Releases, Staff, Tech News, Technology, Uncategorized

Anthropic is officially entering its ‘Thinking’ era. Today, the company announced Claude 4.6 Sonnet, a model designed to transform how devs and data scientists handle complex logic. Alongside this release comes Improved Web Search with Dynamic Filtering, a feature that uses internal code execution to verify facts in real-time. https://www.anthropic.com/news/claude-sonnet-4-6 Adaptive Thinking: A New Logic

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Alibaba Qwen Team Releases Qwen3.5-397B MoE Model with 17B Active Parameters and 1M Token Context for AI agents

Alibaba Cloud just updated the open-source landscape. Today, the Qwen team released Qwen3.5, the newest generation of their large language model (LLM) family. The most powerful version is Qwen3.5-397B-A17B. This model is a sparse Mixture-of-Experts (MoE) system. It combines massive reasoning power with high efficiency. Qwen3.5 is a native vision-language model. It is designed specifically

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Google DeepMind Proposes New Framework for Intelligent AI Delegation to Secure the Emerging Agentic Web for Future Economies

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The AI industry is currently obsessed with ‘agents’—autonomous programs that do more than just chat. However, most current multi-agent systems rely on brittle, hard-coded heuristics that fail when the environment changes. Google DeepMind researchers have proposed a new solution. The research team argued that for the ‘agentic web’ to scale, agents must move beyond simple

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