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Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

Lets be real: building LLM applications today feels like purgatory. Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. Leadership gets excited.

Testing 168
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How to Evaluate a Large Language Model (LLM)?

Analytics Vidhya

Introduction With the release of Chatgpt and other Large Language Models (LLMs), there has been a significant increase in the number of models available. New LLMs are being released every other day. Despite this, there is still no fixed or standardized way to evaluate the quality of these Large Language models.

Modeling 328
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Moving Beyond Guesswork: How to Evaluate LLM Quality

Dataiku

Ninety percent of leaders are already investing in Generative AI in some way, but there's a common challenge: How can you objectively measure whether an LLM's output is actually "good enough"? For instance, imagine you’re using an LLM to power a conversational Q&A chatbot.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

The hype around large language models (LLMs) is undeniable. They promise to revolutionize how we interact with data, generating human-quality text, understanding natural language and transforming data in ways we never thought possible. In life sciences, LLMs can analyze mountains of research papers to accelerate drug discovery.

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The New O’Reilly Answers: The R in “RAG” Stands for “Royalties”

O'Reilly on Data

And what will happen to the quality of content in a future of LLMs? However, RAG engines are not generative AI models so much as they are directed reasoning systems and pipelines that use generative LLMs to create answers grounded in sources. Can hallucinations really be controlled? It is possible.

Metadata 293
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What CIOs should learn now that DeepSeek is here

CIO Business Intelligence

DeepSeeks advancements could lead to more accessible and affordable AI solutions, but they also require careful consideration of strategic, competitive, quality, and security factors, says Ritu Jyoti, group VP and GM, worldwide AI, automation, data, and analytics research with IDCs software market research and advisory practice.

Modeling 117
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5 top business use cases for AI agents

CIO Business Intelligence

At the time, the best AIs couldnt pass the 5% mark on the SWE-bench, a challenging benchmark designed to see how well AI can solve real-world coding problems. The next evolution of AI has arrived, and its agentic. The technology is relatively new, but all the major players are already on board. Devin scored nearly 14%.

Software 143