AI能做什么？无所不能么

1.1.Artificial intelligence(AI)is already delivering wide societal benefits,from medical advances1 to mitigating climate change.2 For example,an AI technology developed by DeepMind,a UKbased business,can now predict the structure of almost every protein known to science.3 This breakthrough will accelerate scientific research and the development of life-saving medicines–it has already helped scientists to make huge progress in combating malaria,antibiotic resistance,and plastic waste.2.2.The UK Science and Technology Framework4 sets out government’s strategic vision and identifies AI as one of five critical technologies.The framework notes the role of regulation in creating the environment for AI to flourish.We know that we have yet to see AI technologies reach their full potential.Under the right conditions,AI will transform all areas of life5 and stimulate the UK economy by unleashing innovation and driving productivity,6 creating new jobs and improving the workplace.3.3.Across the world,countries and regions are beginning to draft the rules for AI.The UK needs to act quickly to continue to lead the international conversation on AI governance and demonstrate the value of our pragmatic,proportionate regulatory approach.The need to act was highlighted by Sir Patrick Vallance in his recent Regulation for Innovation review.The report identifies the short time frame for government intervention to provide a clear,pro-innovation regulatory environment in order to make the UK one of the top places in the world to build foundational AI companies.74.4.While we should capitalise on the benefits of these technologies,we should also not overlook the new risks that may arise from their use,nor the unease that the complexity of AI technologies can produce in the wider public.We already know that some uses of AI could1The use of AI in healthcare and medicine is booming,Insider Intelligence,2023.2 How to fight climate change using AI,Forbes,2022;Tackling Climate Change with Machine Learning,Rolnick et al.,2019.

AI can enable scientific discovery.A computer vision model was used to piece together the first ever image of a black hole 55 million light years away,combining images from eight telescopes around the world.29AI solves decades old protein-folding puzzleAn AI company based in the UK trained neural networks to predict the structures of proteins,solving a problem that had long stumped scientists.The predictions are advancing the field of structural biology:scientists have already used them to prevent antibiotic resistance,30 advance disease research,31 and accelerate the fight against plastic pollution.32 As we find more uses for AI,it will rewrite scientific fields and change the way we learn about our world.Deep learning AI could improve breast cancer screeningAI could transform how diseases are detected,prevented,and treated.Doctors are testing if deep learning can be applied to breast cancer screening.Currently,every mammogram is double-checked by radiologists but this is labour-intensive and causes diagnosis delays.A UK medical technology company is working with the28See,for example,What are Large Language Models used for?NVIDIA,2023.29 Black hole pictured for first time–in spectacular detail,Nature,2019.30 Accelerating the race against antibiotic resistance,Deepmind,2022.31 Stopping malaria in its tracks,Deepmind,2022.32 Creating plastic-eating enzymes that could save us from pollution,Deepmind,2022.9A pro-innovation approach to AI regulationNHS to test AI for the second screening,meaning greater numbers of patients could be screened faster and clinicians could spend more time with patients and provide faster access to treatment.33Farming efficiency increased by AI robots

Won’t AI Eventually Be Able to Do Everything?Particularly given its recent surprise successes,there’s a somewhat widespread belief that eventually AI will be able to“do everything”,or at least everything we currently do.So what about science?Over the centuries we humans have made incremental progress,gradually building up what’s now essentially the single largest intellectual edifice of our civilization.But despite all our efforts,there are still all sorts of scientific questions that remain.So can AI now come in and just solve all of them?特别是考虑到它最近取得的令人惊讶的成功，人们普遍相信人工智能最终将能够“做一切”，或者至少是我们目前所做的一切。那么科学又如何呢？几个世纪以来，我们人类取得了渐进的进步，逐渐建造了现在基本上是我们文明中最大的智力大厦。但尽管我们付出了一切努力，仍然存在各各样的科学问题。那么人工智能现在可以介入并解决所有这些问题吗？To this ultimate question we’re going to see that the answer is inevitably and firmly no.But that certainly doesn’t mean AI can’t importantly help the progress of science.At a very practical level,for example,LLMs provide a new kind of linguistic interface to the computational capabilities that we’ve spent so long building in the Wolfram Language.And through their knowledge of“conventional scientific wisdom”LLMs can often provide what amounts to very high-level“autocomplete”for filling in“conventional answers”or“conventional next steps”in scientific work.对于这个终极问题，我们将看到答案不可避免且坚决是否定的。但这当然并不意味着人工智能不能重要地帮助科学进步。例如，在非常实用的层面上，LLMs为我们花了很长时间在Wolfram语言中构建的计算功能提供了一种新的语言接口。通过他们的“传统科学智慧”知识LLMs通常可以提供相当于非常高水平的“自动完成”，用于填写科学工作中的“传统答案”或“传统的后续步骤”。