Category: AI

Why Your AI Projects are Built on a House of Cards

This week’s latest from Project Flux We’re in the middle of an AI gold rush, with businesses pouring billions into artificial intelligence, hoping to strike it rich with unprecedented efficiency and innovation. Yet, for all the investment and hype, a staggering number of projects are quietly imploding. A recent report from S&P Global highlights a deeply concerning trend: the failure rate of AI projects is not only high but rising [1]. This isn’t just a minor setback; it’s a systemic crisis rooted in a fundamental misunderstanding of how we measure success. We are, in essence, building complex, expensive, and potentially world-changing systems on a foundation of flawed and inadequate metrics. A groundbreaking MIT report has peeled back the curtain on this uncomfortable reality, revealing that our current methods for evaluating AI are not just failing but are actively misleading us [2]. The traditional benchmarks and leaderboards we rely on to gauge AI performance are often disconnected from real-world applications, creating a dangerous gap between what we think our AI can do and what it actually delivers. This isn’t just an academic debate; it’s a critical business issue with profound implications for project delivery professionals. As the people responsible for turning AI’s promise into reality,…

Scientists Use Generative AI to Design New Drugs That Combat Drug-Resistant Bacteria

Researchers from MIT have used generative artificial intelligence (AI) to design a new class of antibiotics capable of killing two difficult-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). The research team used generative AI algorithms to create over 36 million possible compounds. After computationally screening them for antimicrobial properties, they found top candidates that are structurally different from any existing antibiotics. These new compounds appear to work by disrupting bacterial cell membranes through novel mechanisms, a strategy that could be applied to identify drugs against other species of bacteria. James Collins, a professor at MIT and senior author of the study, said: “We’re excited about the new possibilities that this project opens up for antibiotics development. Our work shows the power of AI from a drug design standpoint, and enables us to exploit much larger chemical spaces that were previously inaccessible.” The findings were published in the journal Cell. Exploring New Chemical Territory Over the last 45 years, the majority of new antibiotics have been variants of existing drugs, while bacterial resistance has continued to grow. Globally, it is estimated that drug-resistant bacterial infections cause nearly 5 million deaths per year. To combat this, the Antibiotics-AI Project at…