Scientists at Stanford have used AI to design viruses capable of killing antibiotic-resistant Escherichia coli (E. coli). Using models called Evo 1 and Evo 2, they generated complete viral genomes, producing hundreds of potential bacteriophages.

When tested in the lab, 16 of these AI-designed phages successfully infected and killed resistant E.Coli strains that natural viruses could not. This marks the first time AI has been able to write genome-scale sequences, a step beyond previous work with proteins or small DNA strands. Researchers believe the technology could lead to new therapies in the fight against antibiotic resistance, one of the world’s most pressing health challenges.

By designing tailored viruses, doctors may one day have powerful tools where antibiotics fail. The work, shared on bioRxiv and not yet peer-reviewed, shows both the promise and risks of AI in biotechnology. On the one hand, it highlights AI’s potential to revolutionize medicine. On the other, it raises questions about biosafety and the implications of using machines to design life itself.

Autonomous retail startup Xpand (formerly 1MRobotics) has launched its first European store in Vienna, right next to Mariahilferstraße, the city’s busiest shopping street. The project is a collaboration with CAMPO Group, a robotics and AI automation platform provider.

The store introduces Xpand’s “store-in-a-box” technology to European consumers, offering a full convenience selection of ambient, chilled, and frozen products. With no staff on-site, the shop runs entirely on AI, robotics, and real-time inventory management, providing frictionless, 24/7 shopping and built-in loss prevention.

This milestone comes shortly after a funding round led by Ibex Investors and Emerge, with support from Xpand’s leadership team. The new capital will fuel international growth, with Vienna serving as the blueprint for a global rollout of autonomous convenience stores.

PlanoMate just launched in Kosovo, bringing a fresh way for brands to stay in control of their retail presence. The platform combines photo verified shelf execution, AI-driven compliance checks, GPS tracking, and real-time dashboards, so companies can see exactly how their products and promotions are being displayed across the country. Instead of waiting for slow reports or relying on guesswork, customers get instant visibility into what’s happening in stores.

What sets PlanoMate apart is the mix of technology and trained merchandisers? They cover more than 200 stores nationwide, ensuring planograms, campaigns, and seasonal promotions are rolled out quickly and consistently.

For brands investing heavily in retail, this means fewer stock-outs, stronger compliance, and better ROI on every campaign. In short, it’s a big step forward for retail execution in Kosovo.

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This one is for the geeks. For centuries, mathematicians have been wrestling with the complex equations that describe how fluids move, from the spin of a hurricane to the lift that keeps airplanes in the air. These equations are powerful, but sometimes they predict impossible scenarios, like infinite pressure or velocity. These “blow ups,” known as singularities, are not just mathematical curiosities. They highlight the limits of our understanding and push us closer to solving fundamental questions about how the physical world really works.

In collaboration with researchers from Brown, NYU, and Stanford, Google Deepmind project has introduced a completely new family of singularities to some of the toughest fluid equations. What makes this breakthrough especially exciting is the role of AI. By training specialized neural networks to respect the laws of physics, Deepmind from Google was able to find patterns and solutions that had eluded traditional methods. This approach combines the precision of mathematics with the adaptability of machine learning, opening new doors for research in mathematics, physics, and engineering.

By blending mathematical insight with cutting-edge AI, Google managed to turn a neural network technique called PINNs (Physics-Informed Neural Networks) into a discovery engine for elusive solutions. The precision reached is remarkable, like measuring the Earth’s diameter to within a few centimeters. Beyond fluid dynamics, this work points toward a new era of computer-assisted mathematics, where AI helps tackle century-old puzzles with accuracy once thought impossible.

ChatGPT has quietly become part of daily life for millions. By mid-2025, it’s handling billions of conversations each week and nearly one in ten adults worldwide have tried it. What’s surprising is how much of the use is now outside of work. More than 70% of chats are about everyday things like learning, advice, writing, and curiosity, not just productivity.

The research shows that most people use ChatGPT in three ways: to get practical guidance, to look up information, and to help with writing. At work, it’s mostly about editing, critiquing, or translating text rather than writing something completely new. Coding is a much smaller slice than many expect. Almost half of the time, people are asking for advice or clarity, while the rest is split between asking the tool to “do” something or simply chatting. It’s clear that people see ChatGPT both as a thinking partner and a hands-on helper.

For those of us building products, startups, or strategies, this shift matters. The real opportunity isn’t just automating tasks but supporting better decisions. As more people use AI in their personal lives, expectations for work tools will rise. They’ll need to feel natural, trustworthy, and useful. The big transformation is how people learn, decide, and communicate with the help of AI and the ones who act on this early will have an advantage.

I’ve been spending time with a new research project called Learn Your Way, and it’s one of those moments where you can see how AI might completely reshape something we have known the traditional way.

Instead of handing students static pages to memorize, Learn Your Way reimagines that same material in different forms: mind maps, audio lessons, interactive quizzes, even personalized summaries based on a student’s grade level and interests. It’s built on LearnLM, now running inside Gemini 2.5 Pro.

What I love about it is the sense of agency it gives students. They can explore the material in the format that clicks for them and get real-time feedback along the way. In fact, in a recent study, students using Learn Your Way scored 11 percentage points higher on long-term recall than those using a standard digital reader. If you’re curious, you can check out the full details on Google’s Research blog and Tech Report, or sign up through Google Labs to try it out yourself.

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