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Zhipu AI has open sourced the GLM-4.6V series as a pair of vision language models that treat images, video and tools as first class inputs for agents, not as afterthoughts bolted on top of text. Model lineup and context length The series has 2 models. GLM-4.6V is a 106B parameter foundation model for cloud and […]
Jina AI has released Jina-VLM, a 2.4B parameter vision language model that targets multilingual visual question answering and document understanding on constrained hardware. The model couples a SigLIP2 vision encoder with a Qwen3 language backbone and uses an attention pooling connector to reduce visual tokens while preserving spatial structure. Among open 2B scale VLMs, it
Cisco and Splunk have introduced the Cisco Time Series Model, a univariate zero shot time series foundation model designed for observability and security metrics. It is released as an open weight checkpoint on Hugging Face under an Apache 2.0 license, and it targets forecasting workloads without task specific fine tuning. The model extends TimesFM 2.0
Google is closing an old gap between Kaggle and Colab. Colab now has a built in Data Explorer that lets you search Kaggle datasets, models and competitions directly inside a notebook, then pull them in through KaggleHub without leaving the editor. What Colab Data Explorer actually ships? Kaggle announced the feature recently where they describe
Microsoft has released VibeVoice-Realtime-0.5B, a real time text to speech model that works with streaming text input and long form speech output, aimed at agent style applications and live data narration. The model can start producing audible speech in about 300 ms, which is critical when a language model is still generating the rest of
How do you turn slow, manual click work across browsers and desktops into a reliable, automated system that can actually use a computer for you at scale? Lux is the latest example of computer use agents moving from research demo to infrastructure. OpenAGI Foundation team has released Lux, a foundation model that operates real desktops
How do you keep RAG systems accurate and efficient when every query tries to stuff thousands of tokens into the context window and the retriever and generator are still optimized as 2 separate, disconnected systems? A team of researchers from Apple and University of Edinburgh released CLaRa, Continuous Latent Reasoning, (CLaRa-7B-Base, CLaRa-7B-Instruct and CLaRa-7B-E2E) a
NVIDIA announced today a significant expansion of its strategic collaboration with Mistral AI. This partnership coincides with the release of the new Mistral 3 frontier open model family, marking a pivotal moment where hardware acceleration and open-source model architecture have converged to redefine performance benchmarks. This collaboration is a massive leap in inference speed: the
Large language model agents are starting to store everything they see, but can they actually improve their policies at test time from those experiences rather than just replaying context windows? Researchers from University of Illinois Urbana Champaign and Google DeepMind propose Evo-Memory, a streaming benchmark and agent framework that targets this exact gap. Evo-Memory evaluates
How do you get GPT-5-level reasoning on real long-context, tool-using workloads without paying the quadratic attention and GPU cost that usually makes those systems impractical? DeepSeek research introduces DeepSeek-V3.2 and DeepSeek-V3.2-Speciale. They are reasoning-first models built for agents and targets high quality reasoning, long context and agent workflows, with open weights and production APIs. The
