Influencer marketplaces, collab hubs, brand portals — they go by many names, but serve the same purpose: being a place where creators and brands can work…

More machine learning systems now rely on AI agents, which makes careful safety evaluation essential. With more and more vulnerabilities coming to the fray, it’s nigh impossible for a single unified protocol to stay up to date with them all. This piece introduces MLflow as a practical framework for ...

In this tutorial, we demonstrate how to design a contract-first agentic decision system using PydanticAI, treating structured schemas as non-negotiable governance contracts rather than optional output formats. We show how we define a strict decision model that encodes policy compliance, risk ...

Pollution from textile production—dyes, chemicals, and heavy metals like lead and cadmium—is common in the waters of the Buriganga River as it runs through Dhaka, Bangladesh. It’s among many harms posed by a garment sector that was once synonymous with tragedy: In 2013, the eight-story Rana Plaza ...

NVIDIA AI research team released NitroGen, an open vision action foundation model for generalist gaming agents that learns to play commercial games directly from pixels and gamepad actions using internet video at scale. NitroGen is trained on 40,000 hours of gameplay across more than 1,000 games ...

We have entered the time of multi-agent artificial intelligence. However, there is a very important issue: in what way can remote AI agents produce rich and interactive experiences without exposing the system to security risks? Google A2UI (Agent-to-UI) protocol addresses this question in a very ...

Large language models are powerful, but on their own they have limitations. They cannot access live data, retain long-term context from previous conversations, or perform actions such as calling APIs or querying databases. LangChain is a framework designed to address these gaps and help developers ...

Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2 stack. The goal is simple, improve instruction following, knowledge tasks, and math for a small 3B class model that still ...

In this tutorial, we build an end-to-end, production-style agentic workflow using GraphBit that demonstrates how graph-structured execution, tool calling, and optional LLM-driven agents can coexist in a single system. We start by initializing and inspecting the GraphBit runtime, then define a ...

The role of a Data Analyst in 2026 looks very different from even a few years ago. Today’s analysts are expected to work with messy data, automate reporting, explain insights clearly to business stakeholders, and responsibly use AI to accelerate their workflow. This Data Analyst learning path for ...

SQL is one of those skills that shows up everywhere, data analytics, backend engineering, reporting, and even product roles. But when it comes to resources for learning it, they aren’t as omnipresent. The conventional ways of reading documentation or textbooks isn’t how everyone learns best. Some ...

Google has released FunctionGemma, a specialized version of the Gemma 3 270M model that is trained specifically for function calling and designed to run as an edge agent that maps natural language to executable API actions. But, What is FunctionGemma? FunctionGemma is a 270M parameter text only ...