AIAI London
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Build a Multi-Agent System for Integrated Transcriptomic, Proteomic, and Metabolomic Data Interpretation with Pathway Reasoning
In this tutorial, we construct a complicated multi-agent pipeline that interprets built-in omics information, together with transcriptomics, proteomics, and metabolomics, to uncover key organic insights. We start by producing coherent artificial datasets that mimic real looking organic tendencies and then transfer step-by-step by way of brokers designed for statistical evaluation, community inference, pathway enrichment, and…
Building Advanced Multi-Agent AI Workflows by Leveraging AutoGen and Semantic Kernel
In this tutorial, we walk you through the seamless integration of AutoGen and Semantic Kernel with Google’s Gemini Flash model. We begin by setting up our GeminiWrapper and SemanticKernelGeminiPlugin classes to bridge the generative power of Gemini with AutoGen’s multi-agent orchestration. From there, we configure specialist agents, ranging from code reviewers to creative analysts, demonstrating…
How to turn shadow AI into a safe agentic workforce: Lessons from Barndoor AI
At most enterprises proper now, AI adoption has a unusual break up persona. On the floor, there are the sanctioned initiatives: a strategic LLM partnership, a vendor-led pilot, and a few fastidiously worded coverage paperwork. Underneath, there’s the true exercise. Engineers quietly join AI purposes to enterprise information and SaaS instruments utilizing the mannequin context…
40 companies shaping Silicon Valley’s AI landscape in 2026
In 2026, the region’s AI landscape isn’t defined by one company or one model. It’s shaped by infrastructure providers, frontier research labs, platforms that turn models into systems, and companies applying AI where failure actually matters. Here are 40 companies with major operations in the Bay Area that help explain why Silicon Valley still matters….
Building Event-Driven AI Agents with UAgents and Google Gemini: A Modular Python Implementation Guide
In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to enable nested event loops, then configure your Gemini API key and instantiate the GenAI client. Next, we’ll define our communication contracts, Question and Answer…
