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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. I’ll do my best to update it as the technology evolves.

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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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519: Product verification, most important of the 19 activities of product management – with Nishant Parikh

Product Innovation Educators

Drawing from his 20+ years of technology experience and extensive research, Nishant shared insights about how these activities vary across different organizational contexts – from startups to enterprises, B2B to B2C, and Agile to Waterfall environments.

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Addressing Top Enterprise Challenges in Generative AI with DataRobot

The buzz around generative AI shows no sign of abating in the foreseeable future. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments.

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AI and Product Strategy

Roman Pichler

Customer Insights and Idea Generation AI tools can analyse market data, customer feedback, and emerging trends to suggest new products and features, assuming that enough relevant data is available. For example, you can use an AI tool to analyse support tickets to discover and address common issues.

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The Innovation Ambition Matrix

Roman Pichler

Additionally, you may have to investigate new technologies and review whether the current business model needs to be adapted. It has to discontinue some of the practices that have helped it become successful, acquire new skills, find new business models, and often embrace, and in some cases develop, new technologies. [4]

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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.

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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. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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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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A Tale of Two Case Studies: Using LLMs in Production

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

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

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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

Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days.

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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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How to Achieve High-Accuracy Results When Using LLMs

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

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale.

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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

Putting the right LLMOps process in place today will pay dividends tomorrow, enabling you to leverage the part of AI that constitutes your IP – your data – to build a defensible AI strategy for the future. Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications.