Language Model

Auto Added by WPeMatico

Cohere Releases Tiny Aya: A 3B-Parameter Small Language Model that Supports 70 Languages and Runs Locally Even on a Phone

Cohere AI Labs has released Tiny Aya, a family of small language models (SLMs) that redefines multilingual performance. While many models scale by increasing parameters, Tiny Aya uses a 3.35B-parameter architecture to deliver state-of-the-art translation and generation across 70 languages. The release includes 5 models: Tiny Aya Base (pretrained), Tiny Aya Global (balanced instruction-tuned), and […]

Cohere Releases Tiny Aya: A 3B-Parameter Small Language Model that Supports 70 Languages and Runs Locally Even on a Phone Read More »

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

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

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

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

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

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

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

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

Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support

The landscape of generative audio is shifting toward efficiency. A new open-source contender, Kani-TTS-2, has been released by the team at nineninesix.ai. This model marks a departure from heavy, compute-expensive TTS systems. Instead, it treats audio as a language, delivering high-fidelity speech synthesis with a remarkably small footprint. Kani-TTS-2 offers a lean, high-performance alternative to

Meet ‘Kani-TTS-2’: A 400M Param Open Source Text-to-Speech Model that Runs in 3GB VRAM with Voice Cloning Support Read More »

Kyutai Releases Hibiki-Zero: A3B Parameter Simultaneous Speech-to-Speech Translation Model Using GRPO Reinforcement Learning Without Any Word-Level Aligned Data

Kyutai has released Hibiki-Zero, a new model for simultaneous speech-to-speech translation (S2ST) and speech-to-text translation (S2TT). The system translates source speech into a target language in real-time. It handles non-monotonic word dependencies during the process. Unlike previous models, Hibiki-Zero does not require word-level aligned data for training. This eliminates a major bottleneck in scaling AI

Kyutai Releases Hibiki-Zero: A3B Parameter Simultaneous Speech-to-Speech Translation Model Using GRPO Reinforcement Learning Without Any Word-Level Aligned Data Read More »

OpenAI Releases a Research Preview of GPT‑5.3-Codex-Spark: A 15x Faster AI Coding Model Delivering Over 1000 Tokens Per Second on Cerebras Hardware

OpenAI just launched a new research preview called GPT-5.3 Codex-Spark. This model is built for 1 thing: extreme speed. While the standard GPT-5.3 Codex focuses on deep reasoning, Spark is designed for near-instant response times. It is the result of a deep hardware-software integration between OpenAI and Cerebras. The results are game-changing. Spark is 15x

OpenAI Releases a Research Preview of GPT‑5.3-Codex-Spark: A 15x Faster AI Coding Model Delivering Over 1000 Tokens Per Second on Cerebras Hardware Read More »

Is This AGI? Google’s Gemini 3 Deep Think Shatters Humanity’s Last Exam And Hits 84.6% On ARC-AGI-2 Performance Today

Google announced a major update to Gemini 3 Deep Think today. This update is specifically built to accelerate modern science, research, and engineering. This seems to be more than just another model release. It represents a pivot toward a ‘reasoning mode’ that uses internal verification to solve problems that previously required human expert intervention. The

Is This AGI? Google’s Gemini 3 Deep Think Shatters Humanity’s Last Exam And Hits 84.6% On ARC-AGI-2 Performance Today Read More »

ByteDance Releases Protenix-v1: A New Open-Source Model Achieving AF3-Level Performance in Biomolecular Structure Prediction

How close can an open model get to AlphaFold3-level accuracy when it matches training data, model scale and inference budget? ByteDance has introduced Protenix-v1, a comprehensive AlphaFold3 (AF3) reproduction for biomolecular structure prediction, released with code and model parameters under Apache 2.0. The model targets AF3-level performance across protein, DNA, RNA and ligand structures while

ByteDance Releases Protenix-v1: A New Open-Source Model Achieving AF3-Level Performance in Biomolecular Structure Prediction Read More »

Google AI Introduces PaperBanana: An Agentic Framework that Automates Publication Ready Methodology Diagrams and Statistical Plots

Generating publication-ready illustrations is a labor-intensive bottleneck in the research workflow. While AI scientists can now handle literature reviews and code, they struggle to visually communicate complex discoveries. A research team from Google and Peking University introduce new framework called ‘PaperBanana‘ which is changing that by using a multi-agent system to automate high-quality academic diagrams

Google AI Introduces PaperBanana: An Agentic Framework that Automates Publication Ready Methodology Diagrams and Statistical Plots Read More »