Mistral AI has introduced Devstral 2, a next generation coding model family for software engineering agents, together with Mistral Vibe CLI, an open source command line coding assistant that runs inside the terminal or IDEs that support the Agent Communication Protocol. Devstral 2 and Devstral Small 2, model sizes, context and benchmarks Devstral 2 is The post Mistral AI Ships Devstral 2 Coding Models And Mistral Vibe CLI For Agentic, Terminal Native Development appeared first on MarkTechPost.

In this tutorial, we explore how an intelligent agent can gradually form procedural memory by learning reusable skills directly from its interactions with an environment. We design a minimal yet powerful framework in which skills behave like neural modules: they store action sequences, carry contextual embeddings, and are retrieved by similarity when a new situation The post A Coding Guide to Build a Procedural Memory Agent That Learns, Stores, Retrieves, and Reuses Skills as Neural Modules Over Time appeared first on MarkTechPost.

The new LiteRT NeuroPilot Accelerator from Google and MediaTek is a concrete step toward running real generative models on phones, laptops, and IoT hardware without shipping every request to a data center. It takes the existing LiteRT runtime and wires it directly into MediaTek’s NeuroPilot NPU stack, so developers can deploy LLMs and embedding models The post Google LiteRT NeuroPilot Stack Turns MediaTek Dimensity NPUs into First Class Targets for on Device LLMs appeared first on MarkTechPost.

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 The post Zhipu AI Releases GLM-4.6V: A 128K Context Vision Language Model with Native Tool Calling appeared first on MarkTechPost.

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 The post Jina AI Releases Jina-VLM: A 2.4B Multilingual Vision Language Model Focused on Token Efficient Visual QA appeared first on MarkTechPost.

As AI models grow in complexity and hardware evolves to meet the demand, the software layer connecting the two must also adapt. We recently sat down with Stephen Jones, a Distinguished Engineer at NVIDIA and one of the original architects of CUDA. Jones, whose background spans from fluid mechanics to aerospace engineering, offered deep insights The post Interview: From CUDA to Tile-Based Programming: NVIDIA’s Stephen Jones on Building the Future of AI appeared first on MarkTechPost.

What comes after Transformers? Google Research is proposing a new way to give sequence models usable long term memory with Titans and MIRAS, while keeping training parallel and inference close to linear. Titans is a concrete architecture that adds a deep neural memory to a Transformer style backbone. MIRAS is a general framework that views The post From Transformers to Associative Memory, How Titans and MIRAS Rethink Long Context Modeling appeared first on MarkTechPost.

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 The post Cisco Released Cisco Time Series Model: Their First Open-Weights Foundation Model based on Decoder-only Transformer Architecture appeared first on MarkTechPost.

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 The post Google Colab Integrates KaggleHub for One Click Access to Kaggle Datasets, Models and Competitions appeared first on MarkTechPost.

In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a probabilistic model that captures both global patterns and group-level variations. Through each snippet, we set up inference using NUTS, analyze posterior distributions, and perform posterior The post A Coding Implementation of a Complete Hierarchical Bayesian Regression Workflow in NumPyro Using JAX-Powered Inference and Posterior Predictive Analysis appeared first on MarkTechPost.