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News, analysis, and insights for IT leaders navigating the risks and rewards of AI.

AI in the Enterprise

January 30, 2024

Top 4 LLM threats to the enterprise

Prompt injection, prompt extraction, new phishing schemes, and poisoned models are the most likely risks organizations face when using large language models.

Image: Building AI agents with Semantic Kernel

Building AI agents with Semantic Kernel

Microsoft’s LLM orchestration tools might finally deliver on the three-decade-old promise of autonomous software agents.

7 ways to use Microsoft Copilot right

The free version of Microsoft’s generative AI chatbot is available in Windows and on the web. Here’s how to make the most of it.

Forward Networks boosts digital twin platform with generative AI

AI Assist lets IT teams use natural language prompts in Forward Networks' flagship digital-twin platform to more quickly identify configuration issues and security vulnerabilities across network devices.

Top 10 AI graduate degree programs

Thinking about getting your graduate degree in artificial intelligence? Here are 10 of the top schools with AI degrees worth pursuing.

Teaching machines to code

Great documentation is important for humans, but more so for machines. The concept of ‘tiered documentation’ means that both developers and LLMs get what they need.

Grape expectations: How genAI reshaped a wine company’s customer service team

Wine Enthusiast, an online retailer of all things wine, used genAI to monitor tens of thousands of customer calls, gaining insights into why consumers were calling and using that data to quickly catch and fix product defects.

3 technologies coming to generative AI’s aid in 2024

Three powerful new approaches have emerged to improve the reliability of large language models by developing a fact-checking layer to support them.

Azure AI Studio: A nearly complete toolbox for AI development

Azure AI Studio, while still in preview, checks most of the boxes for a generative AI application builder, with support for prompt engineering, RAG, agent building, and low-code or no-code development.

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