Companies like Lovable, Base44, Replit, and Netlify use AI to let anyone build a web app in seconds--and in thousands of cases, spill highly sensitive data onto the public internet. As AI increasingly takes over the work of modern programmers, the cybersecurity world has warned that automated coding tools are sure to introduce a new bounty of hackable bugs into software. When those same vibe-coding tools invite anyone to create applications hosted on the web with a click, however, it turns out the security implications go beyond bugs to a total absence of any security--even, sometimes, for highly sensitive corporate and personal data. Security researcher Dor Zvi and his team at the cybersecurity firm he cofounded, RedAccess, analyzed thousands of vibe-coded web applications created using the AI software development tools Lovable, Replit, Base44, and Netlify and found more than 5,000 of them that had virtually no security or authentication of any kind. Many of these web apps allowed anyone who merely finds their web URL to access the apps and their data.

A top Google scientist warned EU antitrust regulators that its proposal requiring the company to share search engine data with rivals risked exposing users' private information. BRUSSELS - A top Google scientist sent a warning to EU antitrust regulators on Tuesday that its proposal requiring the company to share search engine data with rivals such as OpenAI risked exposing users' private information, the sternest rebuke yet in a tussle over Google's lucrative business model. The European Commission, which acts as the EU competition enforcer, has in recent years cracked down on Big Tech via a slew of legislation to ensure that users have more choices and that smaller rivals have room to compete. However, that has triggered the ire of the U.S. government. Sergei Vassilvitskii, with the title of distinguished scientist at Google since 2012 and regarded a leader in his field, will meet EU antitrust officials on Wednesday to voice his concerns and propose a broader approach with better guardrails.

A text scam impersonating state courts demands drivers pay $6.99 for fake traffic violations via QR codes. The scheme has hit residents in at least eight U.S. states.

More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. It is estimated that fewer than 2,500 mature Speartooth sharks remain in the wild. Breakthroughs, discoveries, and DIY tips sent six days a week. Combining lasers and sharks may sound like a bad idea, but marine ecologists are banking on it to help save some of the planet's most threatened species. By merging optical technology and geochemistry, a group of researchers in Australia are gaining far more accurate information on the snub-nosed speartooth shark's () age, as well as the health of its environment.

ChatGPT's new privacy policy states how the company uses cookies for tracking, to turn free users into paying subscribers. OpenAI is ready to target free users of its services with advertisements around the web, based on what it knows about them. On Thursday, OpenAI sent an email to users laying out major changes to the AI company's privacy policy in the US. "We'll now use cookies to promote OpenAI products and services on other websites," reads the email sent on April 30. "This does not impact your conversations in ChatGPT. Your conversations with ChatGPT are private and are not shared with marketing partners."

Insurance apps often collect driving, location and health data in exchange for premium discounts. Adjusting app permissions can help limit what information is shared.

The LinkedIn cofounder now has an AI drug discovery startup--and thinks not asking chatbots for medical advice is "bordering on committing malpractice." Following a three-decade career at the helm of some of Silicon Valley's most powerful companies--cofounding LinkedIn and sitting on the boards of PayPal and OpenAI-- Reid Hoffman recently turned his attention to health care. Hoffman's startup, Manas AI, is building an AI engine that aims to fast-track the traditionally slow process of drug discovery for various cancers. Inspired by a dinner with renowned cancer physician Siddhartha Mukherjee, the company's cofounder and CEO, its mission statement is to "shift drug discovery from a decade-long process to one that takes a few years." But Hoffman's enthusiasm for generative AI, in particular, stretches far beyond novel drug targets and small molecules.

Fi Mini and Tractive: Which Smart Cat Tracker Should You Buy? For months, I tested Tractive and Fi Mini smart collars on my cat to find the best for activity, sleep, and GPS tracking. Wearable health-monitoring devices, like smart rings, smartwatches, and fitness trackers, help people stay on top of key wellness markers. By providing data on steps, heart rate, sleep, and more, these gadgets allow people to better understand their health, along with the opportunity to improve it with lifestyle shifts. But why should humans have all the fun?

WIRED spoke with Bloomberg's chief technology officer about the big, chatbot-style changes coming to the iconic platform for traders. For its famous intractability, the Bloomberg Terminal has long inspired devotion, bordering on obsession . Among traders, the ability to chart a path through the software's dizzying scrolls of numbers and text to isolate far-flung information is the mark of a seasoned professional. But as a greater mass of data is fed into the Terminal--not only earnings and asset prices, but weather forecasts, shipping logs, factory locations, consumer spending patterns, private loans, and so on--valuable information is being lost. "It has become more and more untenable," says Shawn Edwards, chief technology officer at Bloomberg.

Enterprise AI hinges on high-accuracy outputs, requiring better data context, unified architectures, and rigorous measurement frameworks, says Bavesh Patel, senior vice president at Databricks, and Rajan Padmanabhan, unit technology officer at Infosys. Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data. While consumer-facing AI tools have dazzled users with speed and ease, enterprise leaders are discovering that deploying AI at scale requires something far less glamorous but far more consequential: data infrastructure that is unified, governed, and fit for purpose. That gap between AI ambition and enterprise readiness is becoming one of the defining challenges of this next phase of digital transformation. As Bavesh Patel, senior vice president of Databricks, puts it, "the quality of that AI and how effective that AI is, is really dependent on information in your ...