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How to Succeed with AI in 2025

Piyanka Jain

And not because AI itself is broken, but because companies keep treating it like a science project instead of a tool that actually needs to solve problems. Some common AI failurestories: The Data Hoarders : Companies that think collecting more data will somehow lead to an AI breakthrough. Ready to see where data is headednext?

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529: Is this the best AI-powered market research approach? – with Carmel Dibner

Product Innovation Educators

How AI captures customer needs that human product managers miss Watch on YouTube TLDR In my recent conversation with Carmel Dibner from Applied Marketing Science, we explored how artificial intelligence is transforming Voice of the Customer (VOC) research for product teams. However, these early efforts faced significant limitations.

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517: How to conduct an AI Design Sprint – with Mike Hyzy

Product Innovation Educators

Using a custom ChatGPT model combined with collaborative team workshops, product teams can rapidly move from initial customer insights to validated prototypes while incorporating strategic foresight and market analysis. Instead of focusing solely on today’s customer problems, product teams need to look 2-5 years into the future.

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Choose the Right Large Language Model (LLM) for Your Product

The Product Coalition

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. Data Richness: A wealth of data opens doors to training bespoke models.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Register today to save your seat! December 6th, 2023 at 11:00am PST, 2:00pm EST, 7:pm GMT

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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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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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How Banks Are Winning with AI and Automated Machine Learning

Banks have always relied on predictions to make their decisions. Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. How today’s banks can handle the data science talent shortage. Brought to you by Data Robot.

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The Role of Artificial Intelligence in Pandemic Response: Lessons Learned From COVID-19

As the disease tragically took more and more lives, policymakers were confronted with widely divergent predictions of how many more lives might be lost and the best ways to protect people. This whitepaper reviews lessons learned from applying AI to the pandemic’s response efforts, and insights to mitigating the next pandemic.

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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. Download the report to gain insights including: How to watch for bias in AI. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.

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Resilient Machine Learning with MLOps

But we can take the right actions to prevent failure and ensure that AI systems perform to predictably high standards, meet business needs, unlock additional resources for financial sustainability, and reflect the real patterns observed in the outside world. We do not know what the future holds.

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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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How to Choose an AI Vendor

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. This report explores why it is so challenging to choose an AI vendor and what you should consider as you seek a partner in AI.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.

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Democratizing AI for All: Transforming Your Operating Model to Support AI Adoption

Democratization puts AI into the hands of non-data scientists and makes artificial intelligence accessible to every area of an organization. Brought to you by Data Robot. Aligning AI to your business objectives. Identifying good use cases. Building trust in AI.