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How to Use Generative AI and LLMs to Improve Search

TechEmpower Innovation

Artificial Intelligence (AI), and particularly Large Language Models (LLMs), have significantly transformed the search engine as we’ve known it. With Generative AI and LLMs, new avenues for improving operational efficiency and user satisfaction are emerging every day.

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Generative AI – The End of Empty Textboxes

TechEmpower Innovation

On a different project, we’d just used a Large Language Model (LLM) - in this case OpenAI’s GPT - to provide users with pre-filled text boxes, with content based on choices they’d previously made. This gives Mark more control over the process, without requiring him to write much, and gives the LLM more to work with.

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Innovation on Steroids: Next Generation AI-Powered Phases and Gates

Leapfrogging

AI technologies bring a new dimension of analytical capabilities and insights that were previously unattainable. By harnessing the power of AI, organizations are able to process vast amounts of data, identify patterns, and make more informed decisions at every phase of the innovation process.

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Embracing the Future: Fractional Executives and Generative AI

Tullio Siragusa

Embracing the Future: Fractional Executives and Generative AI The concept of fractional executives has emerged as a game-changer for companies of all sizes. The rise of Generative Artificial Intelligence (AI) has further empowered fractional executives, enabling them to produce full-time results in significantly less time.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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Managing the Risks of Generative AI

Harvard Business Review

Generative artificial intelligence (AI) has become widely popular, but its adoption by businesses comes with a degree of ethical risk. Organizations must prioritize the responsible use of generative AI by ensuring it is accurate, safe, honest, empowering, and sustainable.

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Is Your Company’s Data Ready for Generative AI?

Harvard Business Review

While CDOs and data leaders are excited about generative AI, they have much work to do to get ready for it. Despite excitement, companies have yet to see clear value from generative AI and need to do significant work to prepare their data.

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A Tale of Two Case Studies: Using LLMs in Production

Speaker: Tony Karrer, Ryan Barker, Grant Wiles, Zach Asman, & Mark Pace

Join our exclusive webinar with top industry visionaries, where we'll explore the latest innovations in Artificial Intelligence and the incredible potential of LLMs. We'll walk through two compelling case studies that showcase how AI is reimagining industries and revolutionizing the way we interact with technology.

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Building User-Centric and Responsible Generative AI Products

Speaker: Shyvee Shi - Product Lead and Learning Instructor at LinkedIn

In the rapidly evolving landscape of artificial intelligence, Generative AI products stand at the cutting edge. This presentation unveils a comprehensive 7-step framework designed to navigate the complexities of developing, launching, and scaling Generative AI products.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.