The Product Coalition
FEBRUARY 29, 2024
Let’s talk confidently about how to select the perfect LLM companion for your project. The AI landscape is buzzing with Large Language Models (LLMs) like GPT-4, Llama2, and Gemini, each promising linguistic prowess. They excel at crafting captivating content, translating languages, and summarizing information.
The Product Coalition
APRIL 3, 2023
AI is having its Cambrian explosion moment (although perhaps not its first), led by the recent developments in large language models and their popularization. link] Veterans in the NLP space are anxious about how suddenly every problem is an LLM problem. This meme sums it up nicely.
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UX Planet
JUNE 14, 2024
Using AI to Gather, Analyze, and Act on User Feedback More Effectively to Improve UX For those who are unaware of UX design, a fast-paced yet steadily growing industry, let it be stated that feedback is a true commodity of the trade. However, opening a new chapter is the entrance of a new player into the field- AI.
Mind the Product
APRIL 5, 2022
In this weeks' podcast episode, we spoke with Ha Phan, Director of Discovery Products at Pluralsight, to develop a stronger understanding of how we can best use ML in product management. [.]
Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software
It's no secret that CTOs need to have a full understanding if they want to be successful, but does that make them responsible for developer productivity? While advancements in software development and testing have come a long way, there is still room for improvement.
Intercom, Inc.
SEPTEMBER 9, 2022
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?” Des Traynor: Welcome to Intercom On Product, episode 18.
The Product Coalition
APRIL 11, 2022
According to Gartner , 85% of machine learning solutions fail because they use raw data. Data scientists work in isolation from operations specialists, and enterprises spend up to three months deploying an ML model. In this article, we will tell you what MLOps is and why businesses need to implement machine learning solutions.
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