When you purchase through links in our articles, we may earn a small commission. How AI is writing phishing emails that look real Cyber criminals are using AI tools to attack their victims faster and more effectively. Users must now be even more vigilant. Back in February 2025, several media outlets warned of a new threat targeting users of Google's Gmail email service. Attackers used AI technology to perfect phishing emails and make them look more convincing.

Trump's UK visit: What to know What did Jimmy Kimmel say about Charlie Kirk? How tariffs are unraveling India's textile industry Nvidia to become one of Intel's biggest shareholders with new investment Nvidia says it will invest $5bn into Intel, throwing its heft behind the struggling US chip company, but has stopped short of giving Intel a crucial manufacturing deal. Nvidia, which is based in Santa Clara, California, announced the investment on Thursday. TSMC currently manufactures Nvidia's flagship processors, a business that the world's most valuable company could one day extend to Intel. AMD, which competes with Intel for supplying chips to data centres, also stands to lose because of Nvidia's backing of Intel.

The chief financial officer for the chip manufacturer Intel, David Zinsner, has announced his company received 5.7bn as part of a deal negotiated with the administration of United States President Donald Trump. During an investor conference on Thursday, Zinsner said that Intel, a leader in the US development of semiconductor chips, received the funds on Wednesday evening. Last week, the White House revealed the federal government would take a 10 percent stake in the struggling tech giant, based in Santa Clara, California. As part of the deal, the government negotiated a five-year warrant for an additional 5 percent of Intel's shares, in case the company should cease to own more than 51 percent of its manufacturing operations. "I don't think there's a high likelihood that we would take our stake below 50 percent," Zinsner said.

The EufyCam S3 Pro 2-Cam Kit delivers sharp, reliable, and fully independent home security without locking you into ongoing fees. Cloud subscriptions that lock your security camera footage behind a monthly fee are a frustrating reality for homeowners. The EufyCam S3 Pro 2-Cam Kit offers a way out. With 4K video resolution, smart AI detection, and solar panels integrated into the two cameras, it delivers top-shelf performance without roping you into a payment plan. Eufy does offer cloud storage as an option, but the cameras in this offering store their recordings locally on Eufy's HomeBase 3 hub--a NAS box (network-attached storage), essentially--enhancing your privacy while saving you money on subscription fees.

When veteran engineer and executive Pat Gelsinger returned to Intel as CEO in 2021, the once-great chipmaker was in a slump. After failing to adapt to the mobile era and then missing several steps in cutting-edge microprocessor manufacturing, it was now also falling behind in supplying chips to feed the tech industry's growing hunger for artificial intelligence. With optimism that at times seemed reckless, Gelsinger promised that Intel would make an epic comeback. He vowed to shake up its sleepy corporate culture, refocus on core engineering, and deliver a revitalized manufacturing plan that would put rivals TSMC and Samsung on notice. This week, Gelsinger declared Intel's comeback plan well and truly on track. He announced a rebrand of the company's "foundry" business, which manufactures chips designed by other companies, saying that Intel's latest manufacturing process would later this year yield silicon chips as efficient and capable as ones from TSMC.

Call it a comeback--with consequences not just for Intel but also the US government's hopes of maintaining a lead in artificial intelligence. The troubled chipmaker's CEO, Pat Gelsinger, announced today that Intel is relaunching and expanding its foundry business, which manufactures chip designs for other companies. Microsoft CEO Satya Nadella also appeared at the Intel event, where he announced that his company will use Intel's relaunched foundry to make future chips. That's a major coup for the chipmaker as it seeks to become relevant again and compete with the world's leading foundry, Taiwan's TSMC, which makes chips for customers that include Apple and Google. "We will need a reliable supply of the most advanced high-performance and high-quality semiconductors," Nadella said.

Improving energy efficiency in industrial production processes is crucial for competitiveness, and compliance with climate policies. This paper introduces a data-driven approach to identify optimal melting patterns in induction furnaces. Through time-series K-means clustering the melting patterns could be classified into distinct clusters based on temperature profiles. Using the elbow method, 12 clusters were identified, representing the range of melting patterns. Performance parameters such as melting time, energy-specific performance, and carbon cost were established for each cluster, indicating furnace efficiency and environmental impact. Multiple criteria decision-making methods including Simple Additive Weighting, Multiplicative Exponential Weighting, Technique for Order of Preference by Similarity to Ideal Solution, modified TOPSIS, and VlseKriterijumska Optimizacija I Kompromisno Resenje were utilized to determine the best-practice cluster. The study successfully identified the cluster with the best performance. Implementing the best practice operation resulted in an 8.6 % reduction in electricity costs, highlighting the potential energy savings in the foundry.

ChatGPT 4 is coming, and rumors suggest it might bring massive improvements to the already incredibly impressive language skills of OpenAI's ChatGPT. To be clear, ChatGPT 4 is unlikely to be the name of OpenAI's next product, but we took a bit of creative license and combined the ChatGPT name with the improved AI model that will drive it in the future, GPT-4. Let's dig into GPT-4, how ChatGPT works now, and when OpenAI might release its next major upgrade. GPT-4 is a new language model being created by OpenAI that can generate text that is similar to human speech. It will advance the technology used by ChatGPT, which is based on GPT-3.5.

Stealthy hardware Trojans (HTs) inserted during the fabrication of integrated circuits can bypass the security of critical infrastructures. Although researchers have proposed many techniques to detect HTs, several limitations exist, including: (i) a low success rate, (ii) high algorithmic complexity, and (iii) a large number of test patterns. Furthermore, the most pertinent drawback of prior detection techniques stems from an incorrect evaluation methodology, i.e., they assume that an adversary inserts HTs randomly. Such inappropriate adversarial assumptions enable detection techniques to claim high HT detection accuracy, leading to a "false sense of security." Unfortunately, to the best of our knowledge, despite more than a decade of research on detecting HTs inserted during fabrication, there have been no concerted efforts to perform a systematic evaluation of HT detection techniques. In this paper, we play the role of a realistic adversary and question the efficacy of HT detection techniques by developing an automated, scalable, and practical attack framework, ATTRITION, using reinforcement learning (RL). ATTRITION evades eight detection techniques across two HT detection categories, showcasing its agnostic behavior. ATTRITION achieves average attack success rates of $47\times$ and $211\times$ compared to randomly inserted HTs against state-of-the-art HT detection techniques. We demonstrate ATTRITION's ability to evade detection techniques by evaluating designs ranging from the widely-used academic suites to larger designs such as the open-source MIPS and mor1kx processors to AES and a GPS module. Additionally, we showcase the impact of ATTRITION-generated HTs through two case studies (privilege escalation and kill switch) on the mor1kx processor. We envision that our work, along with our released HT benchmarks and models, fosters the development of better HT detection techniques.

The cornerstone of collaboration is based on knowledge transfer; sharing of research tools, methodologies and findings; and sometimes combining mutual funding resources to meet shortfalls necessary to build prototypes and commercialize technologies. Collaborations often involve combinations of government, industry and academia who work together to meet difficult challenges and cultivate new ideas. A growing trend for many leading companies is creating technology specific innovation centers, labs, and foundries to accelerate collaboration and invention. As the development of new technologies continues to grow exponentially and globally, collaboration has more value as a resource for adapting to the rapidly emerging technologies landscape by establishing pivotal connections between companies, technologies and stakeholders. In the US Federal government, the National Labs (including: Lawrence Livermore, Oak Ridge, Argonne, Sandia, Idaho National Laboratory, Battelle, and Brookhaven, and Federally Funded Research and Development Centers (FFRDC's), and federally funded Centers For Excellence have been outlets for innovation and public/private cooperation.