article thumbnail

How to Use Generative AI and LLMs to Improve Search

TechEmpower - Product Management

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.

article thumbnail

Generative AI – The End of Empty Textboxes

TechEmpower - Product Management

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.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Image generation AI: A paradigm shift in creativity and governance

Mind the Product

Read more » The post Image generation AI: A paradigm shift in creativity and governance appeared first on Mind the Product. We look for a way forward that will harness its immense possibilities while also ensuring safety, transparency and responsible governance.

article thumbnail

Generative AI Solutions: Revolutionizing the Content Industry

The Product Coalition

Artificial Intelligence (AI) has greatly evolved in many areas, including speech and picture recognition, autonomous driving, and natural language processing. However, generative AI, a relatively new area, has become a game-changer in data generation and content creation.

article thumbnail

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.

article thumbnail

How to keep your head about generative AI (when everyone is losing theirs) by Claire Woodcock

Mind the Product

In her keynote at #mtpcon London 2023, Claire Woodcock, Director of Product, ML, at Mozilla explains how to keep your head about generative AI, when everyone else loses theirs. Read more » The post How to keep your head about generative AI (when everyone is losing theirs) by Claire Woodcock appeared first on Mind the Product.

article thumbnail

Unlocking Efficiency: Harnessing the Power of Generative AI in Business Operations

The Product Coalition

However, a new era of possibilities has dawned with the emergence of Generative AI (GenAI). Imagine a tool that not only automates tasks but also learns, adapts, and innovates — genAI development company, a technology that is already capturing significant attention. How can generative AI transform your business operations?

article thumbnail

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.

article thumbnail

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.

article thumbnail

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.