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When did you first become aware of artificial intelligence (AI)? Notwithstanding science fiction, when did you realize AI has practical applications for business? For most people, that door opened in late 2022 when ChatGPT was released to the public. What’s remarkable is how quickly the business community has embraced AI. Aberdeen Strategy & Research reports nearly 80% of companies are turning to AI for their data-driven business activities, specifically customer interactions.
Summer’s here in the U.S., which hopefully means you’ve got a bit more downtime. Let’s use that to boost your product management career with some top-notch reading. Did you know the average CEO reads about 52 books a year? That’s one book a week! As product managers, we should aim high too. With longer days and some well-deserved time off, there are more opportunities to dive into a good book.
Sequoia Capital called it a firestorm. Gartner says it rocketed to the top of their Hype Cycle. ChatGPT reached 100 million monthly active users (MAU) in just six weeks, feeding into the Generative Artificial Intelligence (Gen AI) frenzy. But for most businesses and consumers, Gen AI hasn’t lived up to the hype. As Sequoia Capital points out, Gen AI is having a value problem.
It’s no surprise business is responding to the rapidly evolving field of Generative Artificial Intelligence (GenAI). It’s driven by tools like ChatGPT and Gemini, and nothing has captured attention quite so effectively since social media hit the scene promising free technology to get closer to their customers. So, it makes sense that Customer Experience (CX) leaders want to explore how AI can help them find new ways to connect with their customers while gaining competitive advantage.
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. 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 m
The world is on fire right now with anticipation about how artificial intelligence (AI) is going to change the business landscape. There’s good reason for it – early adopters are already seeing massive benefits in productivity, innovation, and automation that are returning solid commercial gain. While there’s been a lot of hype about what artificial intelligence (AI) technology can do, there’s also recognition we’ve entered a new climate for business growth.
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