Confronting the AI/energy conundrum

Confronting the AI/energy conundrum

The explosive growth of AI-powered computing centers is creating an unprecedented surge in electricity demand that threatens to overwhelm power grids and derail climate goals. At the same time, artificial intelligence technologies could revolutionize energy systems, accelerating the transition to clean power. “We’re at a cusp of potentially gigantic change throughout the economy,” said William…

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Building Advanced Multi-Agent AI Workflows by Leveraging AutoGen and Semantic Kernel

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…

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Spritle’s Plugin-First MCP Architecture: The Hidden Tech Behind Fast AI Rollouts

Spritle’s Plugin-First MCP Architecture: The Hidden Tech Behind Fast AI Rollouts

Introduction In the fast-moving world of AI, time-to-market can be the difference between industry leadership and playing catch-up. For business owners and product leaders, the promise of AI is no longer just theoretical — it’s operational. But behind every smooth AI rollout lies an often-overlooked secret: architectural design. At Spritle, we’ve engineered that edge with…

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A Coding Guide to Build a Functional Data Analysis Workflow Using Lilac for Transforming, Filtering, and Exporting Structured Insights

A Coding Guide to Build a Functional Data Analysis Workflow Using Lilac for Transforming, Filtering, and Exporting Structured Insights

In this tutorial, we demonstrate a fully functional and modular data analysis pipeline using the Lilac library, without relying on signal processing. It combines Lilac’s dataset management capabilities with Python’s functional programming paradigm to create a clean, extensible workflow. From setting up a project and generating realistic sample data to extracting insights and exporting filtered…

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Melding data, systems, and society

Melding data, systems, and society

Research that crosses the traditional boundaries of academic disciplines, and boundaries between academia, industry, and government, is increasingly widespread, and has sometimes led to the spawning of significant new disciplines. But Munther Dahleh, a professor of electrical engineering and computer science at MIT, says that such multidisciplinary and interdisciplinary work often suffers from a number…

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Getting Started with MLFlow for LLM Evaluation

Getting Started with MLFlow for LLM Evaluation

MLflow is a powerful open-source platform for managing the machine learning lifecycle. While it’s traditionally used for tracking model experiments, logging parameters, and managing deployments, MLflow has recently introduced support for evaluating Large Language Models (LLMs). In this tutorial, we explore how to use MLflow to evaluate the performance of an LLM—in our case, Google’s…

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Google AI Releases Gemini CLI: An Open-Source AI Agent for Your Terminal

Google AI Releases Gemini CLI: An Open-Source AI Agent for Your Terminal

Google has unveiled Gemini CLI, an open-source command-line AI agent that integrates the Gemini 2.5 Pro model directly into the terminal. Designed for developers and technical power users, Gemini CLI allows users to interact with Gemini using natural language directly from the command line—supporting workflows such as code explanation, debugging, documentation generation, file manipulation, and…

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