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Generative AI, ChatGPT and Large Language Models: A 101

Acuvate

The introduction of ChatGPT and other cutting-edge AI-led data analytics and visualization tools has sparked a lot of buzz in the tech world. The secret to these models’ success is Generative AI, which creates text that sounds remarkably human, enabling business users with data analytics outcomes that feels far more natural.

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Embrace AI-driven innovation, it is the future.

Paul Hobcraft

It has been amazing how AI generative thinking (GenAI) has taken hold. It has only been one year since the launch of ChatGPT, then with a follow-up of GPT-4. In a really fascinating routine or guide to how Generative AI developed, then you should read Bernard Marr’s post It is well worth the read.

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What Roles Could Generative AI Play on Your Team?

Harvard Business Review

The recent advances in ChatGPT are merely the first application of new AI technologies. As such, companies and leaders need to think about the various applications outlined here and use the framework described in the article to develop applications for your own company or organization.

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What Salespeople Get Wrong About Using GenAI

Harvard Business Review

Discussion of generative AI has maintained a fever pitch since OpenAI released ChatGPT-3.5 However, driving adoption of generative AI as a new way of working — leading sellers toward creative use of generative AI, and helping them to use it as a coaching and learning aid — requires a very different approach.

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GenAI Could Transform How Health Care Works

Harvard Business Review

The emergence of generative AI language models like ChatGPT, has much in common with this Napster-initiated inflection point: a breakthrough technology with breathtakingly fast adoption, appropriation of other people’s data (OPD), and predictions of doom and obsolescence.

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