
A 0.85% fall leaves Dow Jones futures trading at around 51,170 in early European trading on Friday. By contrast, S&P 500 futures edge up 0.06% to around 7,390, while Nasdaq 100 futures gain 0.90% to around 26,990.

The sharpest one-day losses in major US indices since the tariff-related turmoil of April 2025 have left stock futures trading without a clear direction. Wall Street's heavy sell-off reflected growing fears that Democrats could introduce stricter regulation of the artificial intelligence sector.
Thursday's regular trading session saw the Nasdaq Composite lose 5.5%, compared with declines of 4.4% for the S&P 500 and 3.4% for the Dow. Those losses left the technology-heavy Nasdaq more than 10% below its recent high, formally returning it to correction territory.
Fears that Democratic policies could hold back data centre expansion left AI infrastructure companies bearing the heaviest losses. Semiconductor and memory stocks were particularly badly affected, with Nvidia, AMD, Micron and SanDisk among the chipmakers posting steep declines.
Attention now turns to the forthcoming US Nonfarm Payrolls (NFP) report. Traders expect the release to be crucial in determining market expectations for the Federal Reserve's (Fed) December policy decision.
At its core, artificial intelligence is an academic field devoted to reproducing human cognitive functions, logical understanding, perception and pattern recognition in machines. Commonly shortened to AI, it encompasses several specialisms: artificial neural networks, machine learning or predictive analytics, symbolic reasoning, deep learning, natural language processing, speech recognition, image recognition and expert systems. The overarching objective is to develop artificial general intelligence, or AGI: a machine capable of solving arbitrary problems without having been trained to tackle them.
Artificial intelligence has a broad range of uses. Among the best known are generative AI platforms, including ChatGPT and Google’s Bard platform, which are trained on large language models (LLMs) to respond to text-based queries. Another example is Midjourney, a programme that produces original images from text supplied by users. Probabilistic techniques underpin other forms of AI, allowing them to assess an entity's characteristics or how it is perceived. Upstart’s lending platform, for example, employs an AI-enhanced credit rating system to assess applicants' creditworthiness, searching the internet for information about their careers, wealth profiles and relationships. In scientific research, other AI systems draw on extensive databases of studies to propose potential new pharmaceuticals for laboratory testing. Meanwhile, content aggregators such as YouTube, Spotify and Facebook collect and organise information about viewing habits, using AI applications to recommend personalised content.
Semiconductor group Nvidia (NVDA) produces AI-focused computer chips as well as some of the platforms engineers use to develop AI applications. Because it supplies the tools needed for further applications of artificial intelligence, many supporters regard Nvidia as a picks-and-shovels investment in the AI revolution. Palantir Technologies (PLTR), a “big data” analytics business, holds substantial contracts with the US intelligence community. Its Gotham platform enables that community to sift through data, identify intelligence leads and support pattern recognition. Large corporations use its Foundry product to monitor employee and customer data for predictive analytics and anomaly detection. Microsoft (MSFT), meanwhile, holds a significant stake in OpenAI, the privately held creator of ChatGPT, and has incorporated OpenAI’s technology into its Bing search engine.
The public launch of ChatGPT in late 2022 sparked gains across many AI-related shares. In the six months after its release, Nvidia, for example, rose well over 200%. Wall Street commentators quickly questioned whether another technology bubble was taking hold. Stanley Druckenmiller, the well-known investor who has held sizeable investments in both Palantir and Nvidia, argued that bubbles never last just six months. In his view, if enthusiasm for AI did turn into a bubble, extreme valuations would persist for at least two and a half years or longer, as they did during the DotCom bubble of the late 1990s. By mid-2023, the best assessment was that the market was not in a bubble, at least for the time being. Although Nvidia was then valued at 27 times forward sales, analysts forecast exceptionally strong revenue growth for years ahead. For comparison, the NASDAQ 100 traded at 60 times earnings at the peak of the DotCom bubble, against 25 times earnings in mid-2023.