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Default passwords and outdated firmware are turning your home camera into a public livestream, report warnsThousands of exposed webcams are offering a front-row seat into private and corporate lifeA simple web browser is all it takes to peek into 40,000 unsecured camera feedsThousands of internet-connected webcams, intended to enhance safety and convenience, are now unintentionally offering a window into private lives and secure environments.Research by Bitsight claims over 40,000 webcams around the world are publicly accessible online, often without their owners’ knowledge.These include security cameras, baby monitors, office surveillance systems, and even devices inside hospitals and factories.A growing digital threat, not a hypothetical oneThe investigation highlights just how easily accessible these cameras are.“No passwords. No protections. Just out there,” wrote João Cruz, Principal Security Research Scientist at Bitsight TRACE, noting it requires neither elite hacking skills nor expensive software. In many cases, all it takes is a web browser and a valid IP address.“We first raised the alarm in 2023, and based on this latest study, the situation hasn’t gotten any better.”Exposed footage ranges from innocent scenes, like bird feeders, to far more sensitive views, such as home entry points, live feeds from living rooms, whiteboards in office spaces, and even operations inside data centers.Worryingly, disturbing conversations have emerged on dark web forums, where some users share methods for locating exposed cameras, or even sell access to live feeds.“This isn’t hypothetical: this is happening right now,” Cruz emphasized.The United States leads with roughly 14,000 exposed cameras, followed by Japan, Austria, Czechia, and South Korea. These aren’t isolated incidents but part of a broader failure in how internet-connected cameras are deployed and managed.Bitsight’s team scanned for both HTTP- and RTSP-based cameras, and the results suggest these figures may only scratch the surface.Many of the exposed devices result from basic setup errors: default credentials, open internet access, and outdated firmware that leave systems vulnerable.While vendors and manufacturers must improve device security, users also share responsibility.Choosing products vetted for cybersecurity can help, but users should also pair their camera setups with tools like leading antivirus software and top-rated parental control solutions, which often include network monitoring to flag unusual access or unprotected devices.Ultimately, private users should always check remote accessibility settings, change default passwords, update firmware regularly, and, especially for enterprises, enforce firewall protections and require VPN access.You might also likeThese are the best VPN with antivirus solutionsTake a look at our pick of the best password managersEpson launches subscription where you pay "just" $7.99 to rent a printer and print 50 pages every month

AMD is aggressively acquiring talent to bridge the Instinct and Blackwell GPU performance gapBrium’s compiler expertise could help AMD accelerate inference without hardware-specific dependenciesUntether AI's team joins AMD, but existing customers are left without product supportAMD’s recent moves in the AI sector have centered around strategic acquisitions aimed at strengthening its position in a market largely dominated by Nvidia.These include the acquisitions of Brium, Silo AI, Nod.ai, and the engineering team from Untether AI, each targeted at bolstering AMD’s AI software, inference optimization, and chip design capabilities.The goal is clear: narrow the performance and ecosystem gap between AMD’s Instinct GPUs and Nvidia’s Blackwell line.Calculated acquisitions amid a competitive ecosystemAMD described the acquisition of Brium as a key step toward enhancing its AI software capabilities.“Brium brings advanced software capabilities that strengthen our ability to deliver highly optimized AI solutions across the entire stack,” the company said.Brium's strengths lie in compiler technology and end-to-end AI inference optimization, areas that could be crucial for achieving better out-of-the-box performance and making AMD’s software stack less reliant on specific hardware configurations.While this makes for a strong technical case, it also suggests that AMD is still playing catch-up in the AI software ecosystem, rather than leading it.Brium’s integration will affect several ongoing projects, including OpenAI Triton and SHARK/IREE, which are seen as instrumental in boosting AMD’s inference and training capabilities.The use of precision formats such as MX FP4 and FP6 points to a strategy of squeezing higher performance from existing hardware. But the industry has already seen similar moves from Nvidia, which continues to lead in both raw processing power and software maturity.Another notable move was AMD’s absorption of the entire engineering team from Untether AI, a Canadian startup known for its energy-efficient inference processors. AMD didn’t acquire the company, only the talent, leaving Untether’s products unsupported.“AMD has entered into a strategic agreement to acquire a talented team of AI hardware and software engineers from Untether AI,” the company confirmed, highlighting a focus on compiler and kernel development along with SoC design.This signals a strong push into inference-specific technologies, which are becoming increasingly critical as training-based GPU revenue faces potential decline.“AMD’s acquisition of Untether’s engineering group is proof that the GPU vendors know model training is over, and that a decline in GPU revenue is around the corner,” said Justin Kinsey, president of SBT Industries.While that may overstate the situation, it reflects a growing sentiment in the industry: energy efficiency and inference performance are the next frontiers, not simply building the fastest systems for training large models.Despite AMD’s optimism and commitment to “an open, scalable AI software platform,” questions remain about its ability to match Nvidia’s tight integration between hardware and CUDA-based software.Ultimately, while AMD is taking calculated steps to bridge the gap, Nvidia still holds a considerable lead in both hardware efficiency and software ecosystem.These acquisitions may bring AMD closer, but for now, Nvidia’s Blackwell remains the benchmark for what is widely regarded as the best GPU for AI workloads.You might also likeThese are the best video cards for video editing you can buy right nowTake a look at the best virtual machine softwareFake Cloudflare CAPTCHA page laden with malware uncovered in the wild