MIT Technology Review – AI

  • A fundamental flaw leaves LLMs strikingly vulnerable to attack

    It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month. The claim has huge implications for the safety of this technology, which…

  • Building the enterprise environment for agentic AI

    For the enterprise, the promise of agentic AI is much more than just a better chatbot. It is software agents that execute business tasks end-to-end across people, business workflows, data, and systems. The platform best-suited to run agents is built with proper CPU capacity, resilient data access, policy-aware tool use, observability, memory management, and the…

  • Closing the data loop in AI-driven drug discovery

    Drug discovery is a high-cost, high-risk endeavor that is under growing pressure from a market increasingly defined by first-mover advantage. Since the 1950s, the cost of developing new pharmaceuticals has roughly doubled every nine years—a phenomenon known as Eroom’s Law. Today, bringing a new drug to market takes an average of 10-15 years and costs…

  • Here’s why AI agents lie and cheat to reach their goals

    MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. When two OpenAI models hacked into the website Hugging Face in July, they weren’t trying to make money or commit sabotage—they were just looking for answers…

  • How AI helps scientists design the next generation of medicines

    Designing and developing a new medicine is an expensive, failure-prone scientific challenge. A new drug can take many years to develop, at the cost of a significant investment. And even then, most possible candidates never reach the patient. For biologic medicines, therapies made from engineered proteins rather than synthetic chemistry (which are often used to…

AI Trends

  • Best Practices for Building the AI Development Platform in Government 

    By John P. Desmond, AI Trends Editor  The AI stack defined by Carnegie Mellon University is fundamental to the approach being taken by the US Army for its AI development platform efforts, according to Isaac Faber, Chief Data Scientist at the US Army AI Integration Center, speaking at the AI World Government event held in-person and virtually

  • Advance Trustworthy AI and ML, and Identify Best Practices for Scaling AI 

    By John P. Desmond, AI Trends Editor   Advancing trustworthy AI and machine learning to mitigate agency risk is a priority for the US Department of Energy (DOE), and identifying best practices for implementing AI at scale is a priority for the US General Services Administration (GSA).   That’s what attendees learned in two sessions at the AI

  • Promise and Perils of Using AI for Hiring: Guard Against Data Bias 

    By AI Trends Staff   While AI in hiring is now widely used for writing job descriptions, screening candidates, and automating interviews, it poses a risk of wide discrimination if not implemented carefully.  That was the message from Keith Sonderling, Commissioner with the US Equal Opportunity Commision, speaking at the AI World Government event held live and virtually in

  • Predictive Maintenance Proving Out as Successful AI Use Case 

    By John P. Desmond, AI Trends Editor   More companies are successfully exploiting predictive maintenance systems that combine AI and IoT sensors to collect data that anticipates breakdowns and recommends preventive action before break or machines fail, in a demonstration of an AI use case with proven value.   This growth is reflected in optimistic market forecasts.

  • Novelty In The Game Of Go Provides Bright Insights For AI And Autonomous Vehicles 

    By Lance Eliot, the AI Trends Insider   We already expect that humans to exhibit flashes of brilliance. It might not happen all the time, but the act itself is welcomed and not altogether disturbing when it occurs.    What about when Artificial Intelligence (AI) seems to display an act of novelty? Any such instance is bound to get our attention;

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