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Don’t Use Generative AI to Replace Discovery with Real Humans

Product Talk

I’m disappointed to see the rise of generative AI tools that are designed to replace discovery with real humans. I’m a big fan of generative AI. I’ll then share how and where I think generative AI can help, and clearly identify what we should avoid. Too many generative AI tools miss this point.

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Generative AI and Its Approach to Design

UX Planet

How New Heuristics Are Reshaping the Creative Process Between Humans andMachines Image generated byChatGPT When the wave of generative AI tools began flooding the market, I must confess my reaction was mixed: a sense of fascination for the possibilities and concern for the ethical challenges looming on the horizon.

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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.

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Generative AI in Your Business Strategy: From Concept to Reality

The Product Coalition

Generative AI is poised to bring about a significant transformation in the enterprise sector. According to a study by McKinsey, the application of generative AI use cases across various industries could generate an astounding $2.6 Many have a well-defined AI strategy and have made considerable progress.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. But building an AI application into a reliable, secure workflow agent isn’t as simple as plugging in an API.

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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). A recent study by Gartner revealed that more than 80% of enterprises will have used Generative AI APIs or deployed Generative AI-enabled applications by 2026, highlighting its potential to transform various functions.

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Y Oslo 2024: When It Comes to Discovery, Something is Better Than Nothing

Product Talk

How we build might change with generative AI. Maybe how we synthesize customer needs might change with generative AI, but those broad buckets, I think, are fairly stable. You just set up the system and now you’re regularly getting interviews on your calendar. I’m really excited about generative AI.

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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.

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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.