As Google and Microsoft continue to surge, the AWS chief lays out his pitch: cheaper, reliable AI delivered at hyperscale. You might think Amazon's biggest swing in the AI race was its $8 billion investment in Anthropic. But AWS has also been building in-house foundation models, new chips, massive data centers, and agents meant to keep enterprise customers locked inside its ecosystem. The company believes these offerings will give it an edge as businesses of all shapes and sizes deploy AI in the real world. WIRED sat down with AWS CEO Matt Garman ahead of the company's annual re:Invent conference in Las Vegas to discuss his AI vision, and how he plans to extend Amazon's lead in the cloud market over its fast-rising competitors, Microsoft and Google.

Financial bubbles often arrive without much warning, but create long-lasting economic effects. For example, during the dot-com bubble, innovative technologies created market disruptions through excitement for a promised bright future. Such technologies originated from research where scientists had developed them for years prior to their entry into the markets. That raises a question on the possibility of analyzing scientific publishing data (e.g. citation networks) leading up to a bubble for signals that may forecast the rise and fall of similar future bubbles. To that end, we utilized temporal SNAs to detect possible relationships between the publication citation networks of scientists and financial market data during two modern eras of rapidly shifting technology: 1) dot-com era from 1994 to 2001 and 2) AI era from 2017 to 2024. Results showed that the patterns from the dot-com era (which did end in a bubble) did not definitively predict the rise and fall of an AI bubble. While yearly citation networks reflected possible changes in publishing behavior of scientists between the two eras, there was a subset of AI era scientists whose publication influence patterns mirrored those during the dot-com era. Upon further analysis using multiple analysis techniques (LSTM, KNN, AR X/GARCH), the data seems to suggest two possibilities for the AI era: unprecedented form of financial bubble unseen or that no bubble exists. In conclusion, our findings imply that the patterns present in the dot-com era do not effectively translate in such a manner to apply them to the AI market.

Melania Trump's AI Era Is Upon Us The ever elusive first lady has emerged with a brief to exert thought leadership over AI, for the children. Some insiders are excited; others won't touch the subject with a 10-foot pole. Even more so than the first time around, Melania Trump's tenure as first lady thus far has been more notable for her absence than her presence. But that's beginning to change. The ever elusive first lady, who has been highly sparing in her public appearances, emerged in recent weeks to highlight the newest addition to her slim policy portfolio: artificial intelligence, for the children.

The (generative) artificial intelligence (AI) era has profoundly reshaped the meaning and value of data. No longer confined to static content, data now permeates every stage of the AI lifecycle from the training samples that shape model parameters to the prompts and outputs that drive real-world model deployment. This shift renders traditional notions of data protection insufficient, while the boundaries of what needs safeguarding remain poorly defined. Failing to safeguard data in AI systems can inflict societal and individual, underscoring the urgent need to clearly delineate the scope of and rigorously enforce data protection. In this perspective, we propose a four-level taxonomy, including non-usability, privacy preservation, traceability, and deletability, that captures the diverse protection needs arising in modern (generative) AI models and systems. Our framework offers a structured understanding of the trade-offs between data utility and control, spanning the entire AI pipeline, including training datasets, model weights, system prompts, and AI-generated content. We analyze representative technical approaches at each level and reveal regulatory blind spots that leave critical assets exposed. By offering a structured lens to align future AI technologies and governance with trustworthy data practices, we underscore the urgency of rethinking data protection for modern AI techniques and provide timely guidance for developers, researchers, and regulators alike.

NVIDIA CEO and co-founder Jensen Huang commends President Donald Trump's A.I. agenda and outlines what the country's job future will look like on'Special Report.' Classical and character-based education may seem to some antiquated concepts in the new AI-driven world. However, two recent and prominent AI developments definitively prove the opposite to be true. Going back to our nation's founding, great minds were universal in the belief that the survival of the Republic depended on an educated and virtuous public. Now, if AI experts are to be believed, classical and character education is fundamental to the very survival of humanity.

Elon Musk's so-called Department of Government Efficiency (DOGE) operates on a core underlying assumption: The United States should be run like a startup. So far, that has mostly meant chaotic firings and an eagerness to steamroll regulations. But no pitch deck in 2025 is complete without an overdose of artificial intelligence, and DOGE is no different. AI itself doesn't reflexively deserve pitchforks. It has genuine uses and can create genuine efficiencies. It is not inherently untoward to introduce AI into a workflow, especially if you're aware of and able to manage around its limitations.

Reachy 2 is touted as a "lab partner for the AI era." Director James Cameron attends the "Avatar: The Way Of Water" World Premiere at Odeon Luxe Leicester Square in 2022 in London, England. 'I'LL BE BACK': James Cameron's stance on artificial intelligence has evolved over the past few years, and he feels Hollywood needs to embrace it in a few different ways. MADE IN AMERICA: Nvidia on Monday announced plans to manufacture its artificial intelligence supercomputers entirely in the U.S. for the first time. RIDEABLE 4-LEGGED ROOT: Kawasaki Heavy Industries has introduced something that feels straight out of a video game: CORLEO, a hydrogen-powered, four-legged robot prototype designed to be ridden by humans.

The birth of ChatGPT brought a collection of anxieties regarding how large language models allow users to quickly subvert processes that once required human time, effort, passion, and understanding. And further, the tech sector's often stormy relationship with regulation and ethical oversight have left many fearful for a future where artificial intelligence replaces humans at work and stymies human creativity. While much of this alarm is well founded, we should also consider the possibility that human creativity can blossom in the age of AI. In 2025, we will start to see this manifest in our collective cultural response to technology. To examine how culture and creativity might adapt to the age of AI, we'll use hip-hop as an example.

Data practitioners are among those whose roles are experiencing the most significant change, as organizations expand their responsibilities. Rather than working in a siloed data team, data engineers are now developing platforms and tools whose design improves data visibility and transparency for employees across the organization, including analytics engineers, data scientists, data analysts, machine learning engineers, and business stakeholders. This report explores, through a series of interviews with expert data practitioners, key shifts in data engineering, the evolving skill set required of data practitioners, options for data infrastructure and tooling to support AI, and data challenges and opportunities emerging in parallel with generative AI. The report's key findings include the following: This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff.

Current consumer hype about AI, specifically ChatGPT, shakes many tech giants' status quo. Microsoft had its hand shoved early into the technology company making this quake. And it quickly stepped up to secure its seat by setting a product vision and letting people know. Whereas Google, believed to have owned a better tech, scrambled to set a seat in the hype. But the highly expected demonstration seems to be arranged haphazardly, falling short of enthusiasts' expectations.