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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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The AI API : The Twilio Moment for Machine Learning

Tom Tunguz

Training, deploying, & optimizing machine learning models has historically required teams of dedicated researchers, production engineers, data collection & labeling teams. Even fully staffed, teams required years to develop models with reasonably accurate performance. The last one is the most striking.

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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?” It’s all about artificial intelligence and machine learning.

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How to Identify a SaaS Market that Machine Learning Will Disrupt

Tom Tunguz

In SaaS, machine learning has become an essential component to many different products. Whether it’s automating responses to inbound sales queries, identifying expense reports for audit, or surfacing anomalies in data, machine learning improves workflow software. Why is this the case?

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How to Use Machine Learning to Improve Your Digital Marketing

Neil Patel

Machine learning is on the verge of transforming the marketing sector. According to Gartner , 30% of companies will use machine learning in one part of their sales process by 2020. In other words, machine learning isn’t just for computer scientists. What Is Machine Learning?

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The Five Important Trends in Data, and the One Megatrend Powering Them All

Tom Tunguz

Each team, using their data systems, develops their proprietary data products: analyses, dashboards, machine learning systems, even new product features. Data engineers stand on the shoulders of 70 years of software development experience and take many of the learnings from that discipline.

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Usage as the Moat in AI

Tom Tunguz

In response, startups must develop moats to stake out their market. Machine learning systems, like any complex program, benefit from more use. In addition, researchers have observed an emergent property of machine learning models : something we didn’t anticipate but we can see. What are these moats?