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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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Harnessing the Power of Generative AI in CRM

SugarCRM

However, with recent technological advancements, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have become infused in all sorts of tools, and CRMs are no exception. Today’s CRM tools have been infused with predictive analytics and machine learning capabilities. Generative CRM: What Is It?

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B2B: When & Where AI for Customer Experience Fits

InteractionMetrics

“…for most [machine learning] projects, the buzzword “AI” goes too far. Unstructured data is invaluable for understanding customers’ feelings and thoughts, but only if your analysis respects the nuances. But for many companies, adding AI to analyzing unstructured data is not always required.

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Glossary of AI terms: Understanding GPT, neural networks, and more

Intercom

Deep learning algorithms are highly effective at processing complex and unstructured data, such as images, audio, and text, and have enabled significant advances in a wide range of applications such as natural language processing, speech recognition, and image recognition systems that include facial recognition, self-driving cars, etc.

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The Dark Data Goldmine and How Can AI Help Companies Unlock It

SugarCRM

For most companies using mediocre software, dark data can pose more risk than opportunity. But there’s light at the end of this data black hole: Artificial intelligence (AI) developers learned how to leverage unstructured data to generate predictive capabilities, helping companies utilize the unused data.