![]() The downside to such versatility is that, for now, generative AI can sometimes provide less accurate results, placing renewed attention on AI risk management. One foundation model, for example, can create an executive summary for a 20,000-word technical report on quantum computing, draft a go-to-market strategy for a tree-trimming business, and provide five different recipes for the ten ingredients in someone’s refrigerator. ![]() In contrast, previous generations of AI models were often “narrow,” meaning they could perform just one task, such as predicting customer churn. Foundation models can be used for a wide range of tasks. And, as with other breakthrough technologies such as the personal computer or iPhone, one generative AI platform can give rise to many applications for audiences of any age or education level and in any location with internet access.Īll of this is possible because generative AI chatbots are powered by foundation models, which are expansive neural networks trained on vast quantities of unstructured, unlabeled data in a variety of formats, such as text and audio. Users don’t need a degree in machine learning to interact with or derive value from it nearly anyone who can ask questions can use it. Its out-of-the-box accessibility makes generative AI different from all AI that came before it. It democratized AI in a manner not previously seen while becoming by far the fastest-growing app ever. The public-facing version of ChatGPT reached 100 million users in just two months. This article is a collaborative effort by Michael Chui, Roger Roberts, Tanya Rodchenko, Alex Singla, Alex Sukharevsky, Lareina Yee, and Delphine Zurkiya, representing views from the McKinsey Technology Council and QuantumBlack, AI by McKinsey, which are both part of McKinsey Digital.
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