Small modular reactors (SMRs) are emerging as a viable clean-energy solution to satisfy the soaring electricity demands of next-generation artificial intelligence data centers. Industrial partnerships, such as Dow collaborating with X-energy to deploy high-temperature gas-cooled reactors at a Texas chemical site, demonstrate how SMRs can deliver continuous, zero-carbon steam and power. Compared to traditional nuclear plants, SMRs offer significantly smaller footprints, quicker construction timelines, and passive safety systems. As scaling AI workloads strain existing energy infrastructure, major technology providers are increasingly looking to nuclear energy to secure stable baseload power without increasing carbon emissions.

Major technology companies are attempting to redefine digital privacy, shifting the standard from strict data minimization to secure data processing. Under this reframed definition, companies argue that harvesting massive volumes of user data for AI model training and targeted advertising remains privacy-compliant as long as the information is encrypted, anonymized, or processed within secure enclaves without direct human oversight. However, privacy advocates counter that technical safeguards applied after collection fail to eliminate risks like function creep, security vulnerabilities, and pervasive tracking. Genuine privacy protection requires minimizing data collection at the source rather than merely securing mass data pipelines.

Security research revealed that applications generated using the AI app-building platform Lovable exposed sensitive user data, including passport scans, API keys, and over 200,000 private messages. The vulnerability stemmed from misconfigured database backends, where AI-generated code automatically set up Supabase databases without proper Row Level Security (RLS) policies. Consequently, publicly accessible application keys allowed anyone to read and dump entire database tables. The findings highlight systemic security risks in AI-driven platform development when automated code generation fails to enforce access controls by default. Lovable was notified of the issues and subsequently deployed fixes and security warnings to protect affected applications.

AT&T is expanding its artificial intelligence strategy beyond basic generative chatbots by deploying agentic AI to automate complex, multi-step enterprise workflows. These autonomous AI agents integrate with legacy systems and cloud infrastructure to orchestrate tasks across network management, IT troubleshooting, supply chain logistics, and customer service. By allowing agents to execute multi-step operations rather than merely generating text responses, AT&T aims to streamline operations and reduce manual intervention. The telecommunications provider maintains human-in-the-loop oversight to ensure system reliability, security, and governance as these agentic systems handle increasingly critical business processes.

Private technology companies are partnering with school districts across the United States to equip school buses with AI-powered stop-arm cameras designed to automatically identify and ticket drivers who illegally pass stopped buses. Companies such as BusPatrol install and maintain the surveillance hardware at minimal upfront cost to local governments in exchange for a substantial share of the revenue collected from civil fines. While advocates emphasize that automated enforcement deters dangerous driving around children, critics and motorists contend that revenue-sharing models incentivize aggressive ticketing. This commercial structure has sparked debate over steep fine amounts, automated camera accuracy, and whether private profit motives are undermining public safety goals.

Canva recently introduced its own AI image generator, claiming benchmark performance behind only OpenAI. A head-to-head evaluation comparing the free versions of Canva's generator and ChatGPT across five prompt tests—evaluating detail, text rendering, photorealism, and style—showed that ChatGPT still offers superior accuracy, complex prompt adherence, and finer visual quality. However, Canva's model performed competitively, generating images rapidly and offering direct integration within its design suite. While ChatGPT remains the stronger standalone image creator, Canva provides a convenient in-workflow option for quick visual creation without requiring a paid subscription.

ggml-org has released version 1.0.0 of GGML, an open-source tensor library designed for efficient machine learning inference. The release establishes a stable foundation for low-level tensor operations, memory management, and hardware acceleration across CPU, CUDA, Metal, and Vulkan backends. Built to power high-performance local execution of large language models and neural networks, version 1.0.0 offers developers a standardized framework for embedding low-latency machine learning capabilities into cross-platform applications.

A growing number of residents in College Station, Texas, are raising concerns about the high-pitched noise generated by Amazon's Prime Air delivery drones, comparing the sound to a loud swarm of bees or a chainsaw. The autonomous drone system flies low-altitude routes to deliver lightweight packages quickly, but frequent flights have disrupted local neighborhoods and outdoor activities. Amazon has acknowledged the noise issues and is developing its next-generation MK30 drone, designed to be quieter and operate in light rain, but current disturbance highlights the ongoing challenges of integrating commercial drone logistics into residential areas.

Neuroscientists recorded brain activity in macaque monkeys while the animals watched movies such as Minions and Despicable Me to better understand how primates process dynamic visual stimuli. Unlike traditional experiments that rely on static images, full-motion video allowed researchers to map neural responses across multiple areas of the visual cortex over time. The researchers used this continuous dataset to evaluate artificial neural networks and AI vision models, improving how computational systems simulate real-time visual processing in biological brains.

Cybercriminals are increasingly leveraging generative artificial intelligence to scale up ransomware operations, creating a heightened threat for organizations. Attackers use AI models to craft convincing, grammatically flawless phishing communications across multiple languages, automate network reconnaissance, and refine malicious code. These capabilities significantly lower the technical barrier to entry, enabling less sophisticated actors to launch complex extortion campaigns. While cybersecurity teams are adopting defensive AI tools to detect anomalies faster, the accelerated speed and volume of attacks make rapid patching and strict access controls essential to prevent breaches.

A 1994 Jeep Cherokee owner successfully used Anthropic's Claude AI and a $3 Arduino microcontroller to reverse-engineer the vehicle's engine control unit logic and pass California's strict emissions test. Facing obsolete replacement parts, the owner extracted disassembled assembly code from the 30-year-old vehicle's electronics and fed it to Claude to interpret the undocumented system. The AI analyzed the legacy code and helped write a C++ program for the inexpensive Arduino to accurately emulate missing hardware signals. The project demonstrates how generative AI models can assist with legacy software preservation and lower technical barriers for DIY engineering.

WIRED evaluated leading smart notebooks and digital pens designed to bridge physical handwriting with digital organization. Top choices cater to varied preferences, ranging from dedicated E Ink writing tablets like the reMarkable Paper Pro and Amazon Kindle Scribe for distraction-free note-taking, to reusable notebooks like Rocketbook that digitize handwritten pages through smartphone scanning. Smart pens like the Neo Smartpen capture pen strokes on specialized paper in real time while offering audio syncing and text conversion. Selecting the optimal device depends on whether users prioritize paper-like tactile feel, cloud auto-syncing, or handwriting-to-text search capabilities.

Nvidia CEO Jensen Huang recently completed a pre-arranged 10b5-1 trading plan, selling six million company shares worth over $700 million ahead of schedule. While Huang remains Nvidia's chief executive, the market reaction—combined with Nvidia's ongoing supply constraints and regulatory scrutiny—has created a strategic opening for competitors AMD and Google. AMD is leveraging this momentum by expanding adoption of its Instinct MI300X accelerators with major cloud providers like Microsoft and Meta, while Google is increasingly positioning its custom Tensor Processing Units (TPUs) as a viable, cost-effective alternative to Nvidia's dominant AI hardware ecosystem.

WIRED consulted fashion editors from Vogue and GQ alongside professional stylists to propose a wardrobe refresh for Nvidia CEO Jensen Huang, whose trademark black leather jacket has become synonymous with the company's AI-driven rise. The stylists suggested alternatives that elevate his look—ranging from unstructured Italian tailoring and sleek luxury outerwear to rich textural layers—while preserving his approachable, rock-star executive persona. The proposed makeovers demonstrate how high-level tech leaders can refine their personal branding to match their company's massive market influence without losing their signature identity.

Startups developing autonomous aircraft are pushing to introduce pilotless cargo and passenger flights to alleviate pilot shortages and reduce operational costs, but the transition faces severe hurdles from air traffic control. Current air traffic management relies heavily on human controllers using voice communications, a system already strained by chronic staffing shortages and outdated technology. Integrating automated planes into shared airspace threatens to increase controller workload unless air traffic infrastructure is modernized with automated data exchanges and updated safety standards. Without synchronized technological and regulatory upgrades, scaling self-flying aircraft could exacerbate existing aviation bottlenecks and delay commercial deployment.

Apple's HomeView display is designed primarily as a dedicated hub for smart home management rather than a standard tablet. Built for stationary placement on counters or walls, the device focuses on controlling HomeKit and Matter devices, monitoring security camera streams, presenting glanceable widgets, and processing Siri voice requests. It lacks access to the full iPad app ecosystem, open web browsing, and portable media features. Consumers seeking a versatile iPad alternative for casual browsing or entertainment will find the device restrictive, but users wanting a centralized, always-on control panel for home automation will gain a streamlined smart interface.

AskAnyModel AI Pro Plan offers a lifetime subscription for $31.99, allowing users to send a single prompt to six different artificial intelligence models at once. By displaying generated responses side by side, the platform enables users to compare outputs, formatting, and performance across models such as GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5 Pro without managing multiple subscriptions or toggling between tabs. The Pro Plan provides 3,000 monthly credits, helping creators, researchers, and professionals evaluate AI responses and select the most accurate or suitable output for their specific tasks.

Nvidia is facing allegations of engineering artificial GPU scarcity by funding AI startups that subsequently purchased its high-end hardware. Through venture investments and strategic backing of specialized cloud providers like CoreWeave, Nvidia provided capital that enabled these companies to place massive orders for AI accelerators such as the H100. Critics argue this circular financing arrangement artificially inflated GPU demand, manufactured perceived market shortages, and significantly boosted Nvidia’s data center revenues and market valuation. While defenders contend these investments are standard tech industry practices designed to expand the broader AI ecosystem, the reliance on vendor-backed purchasing raises questions regarding the sustainability of genuine AI hardware demand.

OpenAI has introduced ChatGPT Wallet, a payment integration designed to allow AI agents within ChatGPT to securely execute financial transactions on behalf of users. The feature enables autonomous handling of end-to-end tasks, such as booking travel, subscribing to services, or purchasing products, directly within conversational workflows. To address security and user control, the wallet incorporates customizable spending limits, transaction pre-authorizations, and explicit approval prompts for high-value actions. By streamlining online checkouts into agentic interactions, OpenAI aims to transition ChatGPT from an informational assistant into an actionable agent capable of managing real-world economic activities.

As children increasingly interact with conversational AI chatbots for companionship, education, and entertainment, concerns are growing over the lack of age-appropriate safeguards and content moderation in India. High-profile incidents abroad, including teenagers developing harmful emotional dependencies or receiving unsafe responses, highlight potential risks such as mental health distress and exposure to inappropriate content. While India's Digital Personal Data Protection Act addresses children's data privacy, experts note that current laws do not adequately regulate the actual output generated by AI models. To mitigate these risks, safety advocates are calling for mandatory age verification, parental controls, real-time content filtering, and clearer regulatory standards for AI developers.