Just over a decade ago, Andrew Ng was part of a Google Brain project that showed the power of deep learning technology. For three days, Ng’s team fed a neural network millions of unlabelled images from YouTube videos. After training, the system could identify features such as cats in images it had not encountered before — even though it had not been explicitly taught how. This research became known informally as the “Cat Paper” and laid the groundwork for future advances in artificial intelligence. At around the same time, from his perch as a Stanford professor, Ng pushed into online teaching, making a course on machine learning available to anyone with an internet connection. Its popularity, along with that of other “massive open online courses”, or Moocs, at the time, led Ng and his colleague Daphne Koller to found online education provider Coursera. A few years later Ng moved to Baidu, the Chinese search giant, to help deepen its autonomous driving and AI research efforts. Today he invests in and builds an array of AI start-ups, runs one of his own, and continues to teach courses on AI. When the FT visited Ng’s Palo Alto offices, he pulled out a laptop and turned off its WiFi to demonstrate how an open-source large language model (LLM) from French AI start-up Mistral can run without needing to send data to the cloud. “The model is saved on my hard disc and then it’s using the GPU and CPU [graphics processing unit and central processing unit] on my laptop to just run inference,” he said. When it was given the question of what a reporter should ask Andrew Ng about AI, the background it delivered on Ng and his work looked like the kind of response one would get from ChatGPT, OpenAI’s hit LLM-powered chatbot. An advocate of open-source AI development, Ng has emerged as an outspoken critic of some government efforts to regulate it. Here he speaks about AI’s current capabilities, why warnings of extinction risk are overblown, and what good regulation would look like.
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