Remove Artificial Inteligence Remove Generative AI Remove Learning
article thumbnail

Enhancing Consumer Insights with Artificial Intelligence

Leapfrogging

Artificial Intelligence (AI) is revolutionizing the field of innovation management by providing powerful tools to enhance consumer insights. By leveraging AI, you can gain a deeper understanding of consumer behavior, preferences, and trends, which are crucial for driving innovation and staying competitive in the market.

article thumbnail

Improving Idea Validation with Artificial Intelligence

Leapfrogging

By leveraging AI, you can enhance the efficiency and effectiveness of idea validation. By incorporating AI into your innovation management processes, you can enhance your ability to validate new ideas effectively, ensuring that your organization remains competitive and innovative in a rapidly changing market.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Identify Emerging Opportunities with Artificial Intelligence

Leapfrogging

Artificial Intelligence (AI) is revolutionizing the field of innovation management by providing advanced tools and methodologies to enhance creativity and efficiency. As an innovation professional, you can leverage AI to analyze vast amounts of data, identify patterns, and predict future trends.

article thumbnail

Leveraging AI to Drive the Innovation Lifecycle

Leapfrogging

Introduction to Leveraging AI in Innovation Artificial Intelligence (AI) has the potential to revolutionize how you manage the Innovation Lifecycle. By leveraging AI, you can improve accuracy, speed, and creativity in every phase of ILM. Explore our insights on ai-driven market research.

article thumbnail

Launching LLM-Based Products: From Concept to Cash in 90 Days

Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage

In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.

article thumbnail

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.

article thumbnail

Facilitating Collaboration Across Ecosystems with AI

Leapfrogging

Artificial Intelligence (AI) is revolutionizing the field of innovation management. By leveraging AI, you can enhance your innovation processes, streamline collaboration, and drive more effective outcomes. For more details, visit our article on ai for idea generation. Lead Successful Innovation Projects!

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.

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 Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation metrics for at-scale production guardrails.

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

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

Executive leaders and board members are pushing their teams to adopt Generative AI to gain a competitive edge, save money, and otherwise take advantage of the promise of this new era of artificial intelligence.