Fri.Sep 09, 2022

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Class is now in session! Learn to drive Customer Success through Community

Gainsight

It’s that time of year when students are returning to school. But how about you? Customer Success pros can always learn something new or refresh their skills. What about your knowledge of Digital Customer Success? You may be thinking, what is the difference between traditional CS and Digital CS? . Digital CS utilizes effective core components that allow your teams to scale without additional headcount or resources.

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The new dawn of Machine Learning

Intercom, Inc.

In the past five years, we’ve seen neural network technology really take off into its own. GPT-3 can create human-like text on demand, and DALL-E, a machine learning model that generates images from text prompts, has exploded in popularity on social media, answering the world’s most pressing questions such as, “what would Darth Vader look like ice fishing?

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The Market Requirements Document (MRD): What Product Managers Need To Know

The Product Coalition

Product managers come in different shapes and sizes (i.e., specializations). Some PMs work on features execution while others focus on optimizing a particular business metric. However, if there’s one skill that is common to all product managers, it’s continuous market monitoring and research. That’s where a market requirements document comes into play.

Document 148
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Building a Sticky App: Features That Sell Themselves

The Product Coalition

Over the past decade, the product manager is one role that has become more prominent and defined. The increased demand for product managers revolves around digital transformation and companies adopting a product growth-based thought process. Companies understand the importance of the holistic approach to deliver value to customers-which is no longer exclusive to product viability.

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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. 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