Artificial intelligence has rapidly transformed software engineering. Generative AI and large language models (LLMs) can create huge volumes of code and documentation; machine-learning algorithms can monitor performance and detect security vulnerabilities. But when the task is to conceive, design, and make a complex physical system such as a jet engine, are those AI tools equally transformative' This past semester, the JARVIS Challenge (Jet-engine AI Research and Validation Intensive Sprint) set out to explore whether AI can compress the design-build-test cycle, asking MIT undergraduates to discover whether AI can help them to build faster and better. 'The JARVIS challenge showed that AI can substantially accelerate safety-critical hardware engineering, but engineering judgment remains the decisive differentiator. An AI-native engineer is not defined by using AI, but by leading it ' knowing when to trust it, when to challenge it, and how to translate AI outputs into working hardware. Manufacturing ' not engineering design or analysis ' remained the fundamental rate-limiting step,' says Professor Zolti Spakovszky, director of the MIT Gas Turbine Laboratory....

Earlier this week, a picture circulated online that seemed to show Kentucky Senator Mitch McConnell covered in tubes in a hospital bed in a state of extreme distress. The image was shared widely on Reddit and X, but by Wednesday, the revered fact-checking site Snopes had debunked the image, noting that, when checked, the image registers as containing the SynthID watermark designed by Google to identify AI-generated pictures. Senator McConnell's health has been the subject of intense speculation since he checked into the hospital after an emergency call on June 14. Since that time, he's been largely absent from the public eye, fueling speculation that his health may be failing. In this case, however, the evidence proved to be entirely fake. Launched at Google's I/O developer conference in 2025, SynthID works as an invisible signature, visible to SynthID algorithms but designed to be unnoticeable to the casual observer. Because the signature is built into the image itself, it survives even when an image is screencaptured across multiple platforms, as the McConnell image was....

In today's world, artificial intelligence chatbots such as ChatGPT and Claude can perform many functions, such as composing work emails and planning travel itineraries. These chatbots are systems built around large vision-language models (VLMs): AI trained on a massive dataset that includes books, websites, code, and images. The AI algorithms are then refined on massive amounts of human-generated feedback to follow instructions and avoid harmful or unwanted output, and use that "knowledge" to produce text or images based on input from a user. Although chatbots have clear limitations, they can be very helpful for a wide range of tasks, including in some areas that traditionally require specialized skills, like computer programming. As part of a project for the U.S. Department of the Air Force'MIT AI Accelerator's Phantom Program, U.S. Air Force cadet Joshua Lynch ' with the help of his mentor, Laura Niss, a technical staff member in the Embedded and AI Systems Group at MIT Lincoln Laboratory ' wanted to determine if, as a complete novice to coding, he could develop a fully functional program. He used a process called "vibe-coding," in which a user relies entirely on prompts to guide a generative AI chatbot to write and refine code....

Three former DeepMind researchers who created an AI that beat humans at poker have now applied the same technology to trading stocks ' and the bet appears to be paying off. Their Prague-based AI lab, EquiLibre Technologies, is now valued at $500 million after raising an undisclosed-sum Series A, TechCrunch learned. The round was led by Creandum, and, although the VC also declined to disclose the size of the round, vice president Cameron Sellers confirmed that it was the largest single investment the firm 'has ever made in one go into a company,' he told TechCrunch.The common denominator between poker and Wall Street is that they are well suited for reinforcement learning, an AI training technique where self-learning models are incentivized by rewards. According to Martin Schmid, EquiLibre CEO, 'The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make'' This isn't just game money. In partnership with quant firm Tower Research Capital, EquiLibre's algorithms have been trading billions in daily volume across the S&P 500 and Nasdaq. The startup claims its agents have been doing well since their rollout on crypto markets in 2025, and now on stock exchanges, with 'a perfect record of zero negative months since inception,' meaning they have finished each month with their investments up overall....