Agentic AI

Agentic AI AI Agents

Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts
ByRicardo April 3, 2026April 3, 2026

Designing algorithms for Multi-Agent Reinforcement Learning (MARL) in imperfect-information video games — eventualities the place gamers act sequentially and can’t see one another’s non-public data, like poker — has traditionally relied on handbook iteration. Researchers determine weighting schemes, discounting guidelines, and equilibrium solvers by means of instinct and trial-and-error. Google DeepMind researchers proposes AlphaEvolve, an…

Read More Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts
Agentic AI AI Infrastructure

Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning
ByRicardo April 3, 2026April 3, 2026

In this tutorial, we construct a whole end-to-end pipeline utilizing NVIDIA Model Optimizer to practice, prune, and fine-tune a deep studying mannequin immediately in Google Colab. We begin by establishing the atmosphere and getting ready the CIFAR-10 dataset, then outline a ResNet structure and practice it to set up a robust baseline. From there, we…

Read More Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning
Agentic AI AI Shorts

Arcee AI Releases Trinity Large Thinking: An Apache 2.0 Open Reasoning Model for Long-Horizon Agents and Tool Use
ByRicardo April 3, 2026

The panorama of open-source synthetic intelligence has shifted from purely generative fashions towards techniques able to advanced, multi-step reasoning. While proprietary ‘reasoning’ fashions have dominated the dialog, Arcee AI has launched Trinity Large Thinking. This launch is an open-weight reasoning mannequin distributed beneath the Apache 2.0 license, positioning it as a clear different for builders…

Read More Arcee AI Releases Trinity Large Thinking: An Apache 2.0 Open Reasoning Model for Long-Horizon Agents and Tool Use
Agentic AI AI Agents

Defeating the ‘Token Tax’: How Google Gemma 4, NVIDIA, and OpenClaw are Revolutionizing Local Agentic AI: From RTX Desktops to DGX Spark
ByRicardo April 2, 2026

Run Google’s newest omni-capable open fashions quicker on NVIDIA RTX AI PCs, from NVIDIA Jetson Orin Nano, GeForce RTX desktops to the new DGX Spark, to construct personalised, always-on AI assistants like OpenClaw with out paying a large “token tax” for each motion. The panorama of contemporary AI is shifting quickly. We are shifting away…

Read More Defeating the ‘Token Tax’: How Google Gemma 4, NVIDIA, and OpenClaw are Revolutionizing Local Agentic AI: From RTX Desktops to DGX Spark
Agentic AI AI Shorts

IBM Releases Granite 4.0 3B Vision: A New Vision Language Model for Enterprise Grade Document Data Extraction
ByRicardo April 2, 2026April 2, 2026

IBM has introduced the discharge of Granite 4.0 3B Vision, a vision-language mannequin (VLM) engineered particularly for enterprise-grade doc information extraction. Departing from the monolithic method of bigger multimodal fashions, the 4.0 Vision launch is architected as a specialised adapter designed to carry high-fidelity visible reasoning to the Granite 4.0 Micro language spine. This launch…

Read More IBM Releases Granite 4.0 3B Vision: A New Vision Language Model for Enterprise Grade Document Data Extraction
Agentic AI AI Agents

How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent Pipelines
ByRicardo April 2, 2026

In this tutorial, we construct a whole AgentScope workflow from the bottom up and run every part in Colab. We begin by wiring OpenAI by way of AgentScope and validating a fundamental mannequin name to perceive how messages and responses are dealt with. From there, we outline customized software features, register them in a toolkit,…

Read More How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent Pipelines
Agentic AI AI Shorts

Z.ai Launches GLM-5V-Turbo: A Native Multimodal Vision Coding Model Optimized for OpenClaw and High-Capacity Agentic Engineering Workflows Everywhere
ByRicardo April 2, 2026April 2, 2026

In the sector of vision-language fashions (VLMs), the flexibility to bridge the hole between visible notion and logical code execution has historically confronted a efficiency trade-off. Many fashions excel at describing a picture however wrestle to translate that visible info into the rigorous syntax required for software program engineering. Zhipu AI’s (Z.ai) GLM-5V-Turbo is a…

Read More Z.ai Launches GLM-5V-Turbo: A Native Multimodal Vision Coding Model Optimized for OpenClaw and High-Capacity Agentic Engineering Workflows Everywhere
Agentic AI AI Shorts

How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inference
ByRicardo April 1, 2026

In this tutorial, we construct and run a Colab workflow for Gemma 3 1B Instruct utilizing Hugging Face Transformers and HF Token, in a sensible, reproducible, and easy-to-follow step-by-step method. We start by putting in the required libraries, securely authenticating with our Hugging Face token, and loading the tokenizer and mannequin onto the accessible system…

Read More How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inference
Agentic AI AI in Industry

How AIRA2 breaks AI research bottlenecks
ByRicardo April 1, 2026

The promise of AI brokers that may conduct real scientific research has lengthy captivated the machine studying group, and, let’s be sincere, barely haunted it too. A brand new system known as AIRA2, developed by researchers at Meta’s FAIR lab and collaborating establishments, represents a major leap ahead on this quest… The three partitions holding…

Read More How AIRA2 breaks AI research bottlenecks
Agentic AI AI in Industry

5 lessons we can learn from Sora: Hype vs reality
ByRicardo April 1, 2026

For a quick second, Sora appeared like the way forward for AI video technology. Then, nearly as rapidly because it appeared, it quietly disappeared. Sora’s rise and disappearance supply a uncommon glimpse into the sensible realities of growing cutting-edge AI. For AI leaders, engineers, and decision-makers, it supplies a real-world view of what it takes…

Read More 5 lessons we can learn from Sora: Hype vs reality

Agentic AI

Google DeepMind’s Research Lets an LLM Rewrite Its Own Game Theory Algorithms — And It Outperformed the Experts

Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning

Arcee AI Releases Trinity Large Thinking: An Apache 2.0 Open Reasoning Model for Long-Horizon Agents and Tool Use

Defeating the ‘Token Tax’: How Google Gemma 4, NVIDIA, and OpenClaw are Revolutionizing Local Agentic AI: From RTX Desktops to DGX Spark

IBM Releases Granite 4.0 3B Vision: A New Vision Language Model for Enterprise Grade Document Data Extraction

How to Build Production Ready AgentScope Workflows with ReAct Agents, Custom Tools, Multi-Agent Debate, Structured Output and Concurrent Pipelines

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

How to Build a Production-Ready Gemma 3 1B Instruct Generation AI Pipeline with Hugging Face Transformers, Chat Templates, and Colab Inference

How AIRA2 breaks AI research bottlenecks

5 lessons we can learn from Sora: Hype vs reality

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