In this tutorial, we explore the full capabilities of Z.AI’s GLM-5 model and build a complete understanding of how to use it for real-world, agentic applications. We start from the fundamentals by setting up the environment using the Z.AI SDK and its OpenAI-compatible interface, and then progressively move on to advanced features such as streaming […]

The post How to Build Production-Ready Agentic Systems with Z.AI GLM-5 Using Thinking Mode, Tool Calling, Streaming, and Multi-Turn Workflows appeared first on MarkTechPost.

Designing algorithms for Multi-Agent Reinforcement Learning (MARL) in imperfect-information games — scenarios where players act sequentially and cannot see each other’s private information, like poker — has historically relied on manual iteration. Researchers identify weighting schemes, discounting rules, and equilibrium solvers through intuition and trial-and-error. Google DeepMind researchers proposes AlphaEvolve, an LLM-powered evolutionary coding agent […]

The post Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts appeared first on MarkTechPost.

In the current landscape of computer vision, the standard operating procedure involves a modular ‘Lego-brick’ approach: a pre-trained vision encoder for feature extraction paired with a separate decoder for task prediction. While effective, this architectural separation complicates scaling and bottlenecks the interaction between language and vision. The Technology Innovation Institute (TII) research team is challenging […]

The post TII Releases Falcon Perception: A 0.6B-Parameter Early-Fusion Transformer for Open-Vocabulary Grounding and Segmentation from Natural Language Prompts appeared first on MarkTechPost.

In this tutorial, we build a complete end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a deep learning model directly in Google Colab. We start by setting up the environment and preparing the CIFAR-10 dataset, then define a ResNet architecture and train it to establish a strong baseline. From there, we apply […]

The post Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning appeared first on MarkTechPost.

The landscape of open-source artificial intelligence has shifted from purely generative models toward systems capable of complex, multi-step reasoning. While proprietary ‘reasoning’ models have dominated the conversation, Arcee AI has released Trinity Large Thinking. This release is an open-weight reasoning model distributed under the Apache 2.0 license, positioning it as a transparent alternative for developers […]

The post Arcee AI Releases Trinity Large Thinking: An Apache 2.0 Open Reasoning Model for Long-Horizon Agents and Tool Use appeared first on MarkTechPost.

Run Google’s latest omni-capable open models faster on NVIDIA RTX AI PCs, from NVIDIA Jetson Orin Nano, GeForce RTX desktops to the new DGX Spark, to build personalized, always-on AI assistants like OpenClaw without paying a massive “token tax” for every action. The landscape of modern AI is shifting rapidly. We are moving away from […]

The post Defeating the ‘Token Tax’: How Google Gemma 4, NVIDIA, and OpenClaw are Revolutionizing Local Agentic AI: From RTX Desktops to DGX Spark appeared first on MarkTechPost.

IBM has announced the release of Granite 4.0 3B Vision, a vision-language model (VLM) engineered specifically for enterprise-grade document data extraction. Departing from the monolithic approach of larger multimodal models, the 4.0 Vision release is architected as a specialized adapter designed to bring high-fidelity visual reasoning to the Granite 4.0 Micro language backbone. This release […]

The post IBM Releases Granite 4.0 3B Vision: A New Vision Language Model for Enterprise Grade Document Data Extraction appeared first on MarkTechPost.

In this tutorial, we build a complete AgentScope workflow from the ground up and run everything in Colab. We start by wiring OpenAI through AgentScope and validating a basic model call to understand how messages and responses are handled. From there, we define custom tool functions, register them in a toolkit, and inspect the auto-generated […]

The post How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent Pipelines appeared first on MarkTechPost.

In the field of vision-language models (VLMs), the ability to bridge the gap between visual perception and logical code execution has traditionally faced a performance trade-off. Many models excel at describing an image but struggle to translate that visual information into the rigorous syntax required for software engineering. Zhipu AI’s (Z.ai) GLM-5V-Turbo is a vision […]

The post Z.ai Launches GLM-5V-Turbo: A Native Multimodal Vision Coding Model Optimized for OpenClaw and High-Capacity Agentic Engineering Workflows Everywhere appeared first on MarkTechPost.

In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible, and easy-to-follow step-by-step manner. We begin by installing the required libraries, securely authenticating with our Hugging Face token, and loading the tokenizer and model onto the available device with […]

The post How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inference appeared first on MarkTechPost.

Hugging Face has officially released TRL (Transformer Reinforcement Learning) v1.0, marking a pivotal transition for the library from a research-oriented repository to a stable, production-ready framework. For AI professionals and developers, this release codifies the Post-Training pipeline—the essential sequence of Supervised Fine-Tuning (SFT), Reward Modeling, and Alignment—into a unified, standardized API. In the early stages […]

The post Hugging Face Releases TRL v1.0: A Unified Post-Training Stack for SFT, Reward Modeling, DPO, and GRPO Workflows appeared first on MarkTechPost.

Google has announced the release of Veo 3.1 Lite, a new model tier within its generative video portfolio designed to address the primary bottleneck for production-scale deployments: pricing. While the generative video space has seen rapid progress in visual fidelity, the cost per second of generated content has remained high, often prohibitive for developers building […]

The post Google AI Releases Veo 3.1 Lite: Giving Developers Low Cost High Speed Video Generation via The Gemini API appeared first on MarkTechPost.

In the current landscape of generative AI, the ‘scaling laws’ have generally dictated that more parameters equal more intelligence. However, Liquid AI is challenging this convention with the release of LFM2.5-350M. This model is actually a technical case study in intelligence density with additional pre-training (from 10T to 28T tokens) and large-scale reinforcement learning The […]

The post Liquid AI Released LFM2.5-350M: A Compact 350M Parameter Model Trained on 28T Tokens with Scaled Reinforcement Learning appeared first on MarkTechPost.

In this tutorial, we work directly with the A-Evolve framework in Colab and build a complete evolutionary agent pipeline from the ground up. We set up the repository, configure an OpenAI-powered agent, define a custom benchmark, and build our own evolution engine to see how A-Evolve actually improves an agent through iterative workspace mutations. Through […]

The post How to Build and Evolve a Custom OpenAI Agent with A-Evolve Using Benchmarks, Skills, Memory, and Workspace Mutations appeared first on MarkTechPost.

The landscape of multimodal large language models (MLLMs) has shifted from experimental ‘wrappers’—where separate vision or audio encoders are stitched onto a text-based backbone—to native, end-to-end ‘omnimodal’ architectures. Alibaba Qwen team latest release, Qwen3.5-Omni, represents a significant milestone in this evolution. Designed as a direct competitor to flagship models like Gemini 3.1 Pro, the Qwen3.5-Omni […]

The post Alibaba Qwen Team Releases Qwen3.5 Omni: A Native Multimodal Model for Text, Audio, Video, and Realtime Interaction appeared first on MarkTechPost.

Microsoft has announced the release of Harrier-OSS-v1, a family of three multilingual text embedding models designed to provide high-quality semantic representations across a wide range of languages. The release includes three distinct scales: a 270M parameter model, a 0.6B model, and a 27B model. The Harrier-OSS-v1 models achieved state-of-the-art (SOTA) results on the Multilingual MTEB […]

The post Microsoft AI Releases Harrier-OSS-v1: A New Family of Multilingual Embedding Models Hitting SOTA on Multilingual MTEB v2 appeared first on MarkTechPost.

In the world of voice AI, the difference between a helpful assistant and an awkward interaction is measured in milliseconds. While text-based Retrieval-Augmented Generation (RAG) systems can afford a few seconds of ‘thinking’ time, voice agents must respond within a 200ms budget to maintain a natural conversational flow. Standard production vector database queries typically add […]

The post Salesforce AI Research Releases VoiceAgentRAG: A Dual-Agent Memory Router that Cuts Voice RAG Retrieval Latency by 316x appeared first on MarkTechPost.

In the development of autonomous agents, the technical bottleneck is shifting from model reasoning to the execution environment. While Large Language Models (LLMs) can generate code and multi-step plans, providing a functional and isolated environment for that code to run remains a significant infrastructure challenge. Agent-Infra’s Sandbox, an open-source project, addresses this by providing an […]

The post Agent-Infra Releases AIO Sandbox: An All-in-One Runtime for AI Agents with Browser, Shell, Shared Filesystem, and MCP appeared first on MarkTechPost.

In this tutorial, we build and explore the CAI Cybersecurity AI Framework step by step in Colab using an OpenAI-compatible model. We begin by setting up the environment, securely loading the API key, and creating a base agent. We gradually move into more advanced capabilities such as custom function tools, multi-agent handoffs, agent orchestration, input […]

The post How to Build Advanced Cybersecurity AI Agents with CAI Using Tools, Guardrails, Handoffs, and Multi-Agent Workflows appeared first on MarkTechPost.

A team of researchers associated with Amazon has released A-Evolve, a universal infrastructure designed to automate the development of autonomous AI agents. The framework aims to replace the ‘manual harness engineering’ that currently defines agent development with a systematic, automated evolution process. The project is being described as a potential ‘PyTorch moment’ for agentic AI. […]

The post Meet A-Evolve: The PyTorch Moment For Agentic AI Systems Replacing Manual Tuning With Automated State Mutation And Self-Correction appeared first on MarkTechPost.