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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. We wanted to know what’s up with this surge, so we’ve asked our Director of Machine Learning, Fergal Reid , if we can pick his brain for today’s episode. It’s all about artificial intelligence and machine learning.

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Effective customer engagement is business critical – insights from Harvard Business Review Analytic Services

Intercom, Inc.

New research from Harvard Business Review Analytic Services reveals that businesses of all sizes – from small businesses to enterprises – are realizing the business value of personal, efficient customer engagement. Below, we take a deeper dive into the report’s key data and trends. But they’re facing big barriers.

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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. At Intercom, we have taken advantage of these technologies relatively early. It’s also easy to over- or under- invest in the technology. The cupcake approach to building bots.

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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. What does it mean for us as product managers?

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MLOps 101: The Foundation for Your AI Strategy

Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects?

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Why Machine Learning Solutions are Difficult to Implement without Machine Learning Operations?

The Product Coalition

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. MLOps is an innovative format for working between data scientists and operations specialists.

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Machine Learning (ML) Demystified: What Do You Need to Know About it?

The Product Coalition

The emergence and evolution of data science have been one of the biggest impacts of technology on enterprises. As the web world keeps growing and getting competitive, there’s a dire need for businesses to learn as much as they can about their consumers and the patterns impacting sales and profits. billion U.S. dollars.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology. Download the report to gain insights including: How to watch for bias in AI.

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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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The AI Superhero Approach to Product Management

Speaker: Conrado Morlan

In this engaging and witty talk, industry expert Conrado Morlan will explore how artificial intelligence can transform the daily tasks of product managers into streamlined, efficient processes. Tools and AI Gadgets 🤖 Overview of essential AI tools and practical implementation tips.

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The Recruiting Crossword Puzzle

On top of ever-increasing advancements on the technology front (hello, artificial intelligence), try adding record-low unemployment and candidates’ virtual omnipresence and you’ve got yourself a pretty passive, well-informed, and crowded recruiting landscape. The good news?