Now that neural nets work, industry and government have started calling neural nets AI. And the people in AI who spent all their life mocking neural nets and saying they'd never do anything are now happy to call them AI and try and get some of the money.

Geoffrey Hinton’s quote highlights the evolving relationship between neural networks and artificial intelligence (AI). He points out that now that neural nets—a type of machine learning algorithm—have proven to be effective, both industry and government have started to refer to them as part of AI. This shift contrasts with the earlier skepticism from those in the AI community who once dismissed neural nets as a promising approach. Hinton humorously critiques those who once mocked neural nets and said they wouldn’t achieve anything significant, but are now eager to embrace them as part of AI to attract funding and attention.

The quote reflects the dynamic nature of technological trends and how rapidly changing breakthroughs can lead to shifts in perception. Hinton is commenting on the way AI has become a buzzword in both the private sector and government, with organizations now keen to associate their work with AI to gain investment or recognition. This highlights a broader pattern in the tech world, where hype and money can sometimes drive the language used around technologies, regardless of their actual scientific merits or the history behind them.

Hinton, known as one of the pioneers of neural networks, is well aware of the long history of skepticism that surrounded these technologies. His work in deep learning has revolutionized the field of AI, making neural nets one of the most powerful tools in the development of AI systems today. The quote originates from his frustration with how quickly the AI community has shifted its stance, often for financial gain, while overlooking the contributions and breakthroughs that led to the current advancements in machine learning.

In essence, Hinton’s quote is a critique of the hypocrisy he sees in the AI field, as it has evolved from dismissing neural nets to claiming them as an integral part of AI, all for the sake of funding and recognition. It reflects the shifting dynamics in the tech industry, where perceptions and terminology can change rapidly based on the success or popularity of a technology, sometimes ignoring the scientific and historical context behind it.