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Building Resolution Bot: How to apply machine learning in product development

Intercom, Inc.

We are at the start of a revolution in customer communication, powered by machine learning and artificial intelligence. So, modern machine learning opens up vast possibilities – but how do you harness this technology to make an actual customer-facing product? The cupcake approach to building bots.

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Deep dive: Engineering artificial intelligence for trust

Mind the Product

Read more » The post Deep dive: Engineering artificial intelligence for trust appeared first on Mind the Product. Explore the intricate challenges of building AI-native products that prioritize user trust.

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The new dawn of Machine Learning

Intercom, Inc.

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?” Today, we have an interesting topic to discuss.

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Large Language Models for the Rest of Us

The Product Coalition

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. Boom, you’re off to a great start.

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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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5 Machine Learning Lessons for Product Managers

Mind the Product

Artificial intelligence (AI) is probably the biggest commercial opportunity in today’s economy. We all use AI or machine learning (ML)-driven products almost every day, and the number of these products will be growing exponentially over the next couple of years. Lesson 3: Account for Model Mistakes and Biases.

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How to build machine learning-based products

Mind the Product

In this article, written for product managers, data scientists, and engineering teams we cover some growth areas and ideas on how to achieve more impact while working on building ML-based products. [.] Read more » The post How to build machine learning-based products appeared first on Mind the Product.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)