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Liquid AI Releases LFM2.5: A Compact AI Model Family For Real On Device Agents

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Liquid AI has introduced LFM2.5, a new generation of small foundation models built on the LFM2 architecture and focused at on device and edge deployments. The model family includes LFM2.5-1.2B-Base and LFM2.5-1.2B-Instruct and extends to Japanese, vision language, and audio language variants. It is released as open weights on Hugging Face and exposed through the […]

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Recursive Language Models (RLMs): From MIT’s Blueprint to Prime Intellect’s RLMEnv for Long Horizon LLM Agents

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Recursive Language Models aim to break the usual trade off between context length, accuracy and cost in large language models. Instead of forcing a model to read a giant prompt in one pass, RLMs treat the prompt as an external environment and let the model decide how to inspect it with code, then recursively call

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Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorld

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Alibaba Tongyi Lab have released MAI-UI—a family of foundation GUI agents. It natively integrates MCP tool use, agent user interaction, device–cloud collaboration, and online RL, establishing state-of-the-art results in general GUI grounding and mobile GUI navigation, surpassing Gemini-2.5-Pro, Seed1.8, and UI-Tars-2 on AndroidWorld. The system targets three specific gaps that early GUI agents often ignore,

Alibaba Tongyi Lab Releases MAI-UI: A Foundation GUI Agent Family that Surpasses Gemini 2.5 Pro, Seed1.8 and UI-Tars-2 on AndroidWorld Read More »

From Gemma 3 270M to FunctionGemma, How Google AI Built a Compact Function Calling Specialist for Edge Workloads

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Google has released FunctionGemma, a specialized version of the Gemma 3 270M model that is trained specifically for function calling and designed to run as an edge agent that maps natural language to executable API actions. But, What is FunctionGemma? FunctionGemma is a 270M parameter text only transformer based on Gemma 3 270M. It keeps

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This AI Paper from Stanford and Harvard Explains Why Most ‘Agentic AI’ Systems Feel Impressive in Demos and then Completely Fall Apart in Real Use

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Agentic AI systems sit on top of large language models and connect to tools, memory, and external environments. They already support scientific discovery, software development, and clinical research, yet they still struggle with unreliable tool use, weak long horizon planning, and poor generalization. The latest research paper ‘Adaptation of Agentic AI‘ from Stanford, Harvard, UC

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Google Health AI Releases MedASR: a Conformer Based Medical Speech to Text Model for Clinical Dictation

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Google Health AI team has released MedASR, an open weights medical speech to text model that targets clinical dictation and physician patient conversations and is designed to plug directly into modern AI workflows. What MedASR is and where it fits? MedASR is a speech to text model based on the Conformer architecture and is pre

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Google DeepMind Researchers Release Gemma Scope 2 as a Full Stack Interpretability Suite for Gemma 3 Models

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Google DeepMind Researchers introduce Gemma Scope 2, an open suite of interpretability tools that exposes how Gemma 3 language models process and represent information across all layers, from 270M to 27B parameters. Its core goal is simple, give AI safety and alignment teams a practical way to trace model behavior back to internal features instead

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Introducing Translator Copilot: Bridging Customers and Translators with AI  

2023, AI, Automation & Tech, Artificial Intelligence, Blog, Language, Large Language Model, LLM, Quality, Research, Translation Quality

Translator Copilot is Unbabel’s new AI assistant built directly into our CAT tool. It leverages large language models (LLMs) and Unbabel’s proprietary Quality Estimation (QE) technology to act as a smart second pair of eyes for every translation. From checking whether customer instructions are followed to flagging potential errors in real time, Translator Copilot strengthens

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TowerLLM, Unbabel’s GenAI for translation, ushers in the next era of machine translation  

2023, AI, Automation & Tech, Artificial Intelligence, Blog, Language, Large Language Model, LLM, Translation Quality

Machine translation (MT) has come a long way. From the early rule-based systems to the advent of neural networks, the field has seen remarkable advancements. For more than a decade, Unbabel has been at the forefront of this evolution, leveraging state-of-the-art technologies like quality estimation (QE) to enhance translation accuracy and fluency.  However, despite all

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Announcing Tower: An Open Multilingual LLM for Translation-Related Tasks

2023, AI, Automation & Tech, Artificial Intelligence, Blog, Language, Large Language Model, Localization & Translation, NLP and MT, Quality, Research, Translation, Translation Quality

Updated February 9, 2024 to include the newest iteration of Tower models. We are thrilled to announce the release of Tower, a suite of multilingual large language models (LLM) optimized for translation-related tasks. Tower is built on top of LLaMA2 [1], comes in two sizes — 7B and 13B parameters —, and currently supports 10

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