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Using Generative AI to Drive Corporate Impact

TechEmpower Innovation

Generative AI is revolutionizing how corporations operate by enhancing efficiency and innovation across various functions. Focusing on generative AI applications in a select few corporate functions can contribute to a significant portion of the technology's overall impact.

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Innovation thinking in Ecosystem and Generative AI design.

Paul Hobcraft

Innovation is undergoing a radical change, in opening up to technology, collaborative thinking and the value of generative AI thinking. For me, ecosystem innovation and generative AI have arrived at that pivotal point to significantly influence future innovation design. Innovation needs reinventing.

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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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The 7 Levels of A.I. usage: How advanced are you?

Idea to Value

.: AI is not used at all, and most processes are still performed manually (whether digitally or physically) Level 1: Unaware A.I.: AI is embedded in everyday tools without strategic intent. Organizations experiment with generative AI for simple, high-impact tasks. Level 2: Basic A.I.: Level 3: In-App A.I.: Level 6: A.I.-driven

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. The number of use cases/corner cases that the system is expected to handle essentially explodes. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases.

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Accelerating Product Development with AI Tools

Leapfrogging

AI tools can analyze vast amounts of data, identify patterns, and provide insights that would be impossible to achieve manually. AI’s role in innovation management includes: Idea Generation : AI algorithms can analyze market trends and consumer behavior to suggest new product ideas.

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Leveraging AI to Drive the Innovation Lifecycle

Leapfrogging

Key areas where AI can make a significant impact include: AI for Idea Generation : Using machine learning algorithms to analyze data and generate novel ideas ( ai for idea generation ). AI-Driven Market Research : Conducting in-depth market analysis swiftly and accurately ( ai-driven market research ).

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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.

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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.