This includes the use of specialized neural engines in devices like the iPhone 15 Pro, which are optimized for AI tasks such as machine learning and natural language processing. This configuration allows for new experiences such as real-time AI image generation, language translation and advanced search functionalities like the “Recall” feature, which records and analyzes device activity to improve user interaction with AI models. The integration of AI into personal computers is facilitated by the emergence of specialized AI chipsets, such as neural processing units (NPUs), which enhance PCs’ ability to perform AI tasks locally. AI PCs are designed to efficiently execute AI workloads using a combination of CPUs, GPUs and NPUs, allowing them to handle tasks such as generative AI models more effectively than previous PC generations. According to Gartner Global Chief of Research Chris Howard, AI will also involve more small language models (SLMs) powering non-chatbot use cases running close to the edge rather than the cloud. Nvidia Graphics Processing Units (GPUs) are crucial in AI because they handle parallel processing efficiently, which is necessary for machine learning and deep learning. 2 min read - Summary The first of a series of blog posts has been published detailing a vulnerability in the Common Unix Printing System (CUPS), which purportedly allows attackers to gain remote access to UNIX-based systems. 3 min read - Artificial intelligence and machine learning are becoming increasingly crucial to cybersecurity systems. Apple has made several hardware changes to accommodate and empower AI capabilities in its devices. The popular generative AI revolution began in November 2022 and resulted in big hardware changes to accommodate power-hungry AI use cases. The surge in artificial intelligence (AI) usage over the past two and a half years has dramatically changed not only software but hardware as well. Organizations need professionals with a strong background that mixes AI/ML knowledge with cybersecurity skills, bringing on board people like Nicole Carignan, Vice President of Strategic Cyber AI at Darktrace, who has a unique blend of technical and soft skills. Big tech giants like Microsoft, Google and Meta accelerated the development and public availability of their offerings, and Silicon Valley quickly saw the emergence of companies like Anthropic and Perplexity offering AI tools. A significant development is the integration of Apple silicon, specifically designed to handle advanced AI processing. 2 min read - Last year, the highest volume of cyberattacks (30%) started in the same way: a cyber criminal using valid credentials to gain access. This report provides insights into the evolving threat landscape, identifying the most prevalent and dangerous cyberattack techniques that organizations need to prepare for.This year’s report also highlighted the main takeaways from the SANS keynote hosted at the annual conference. This optimization enables AI PCs to run AI applications with improved performance, power efficiency and privacy by processing data locally rather than relying on cloud-based solutions. These PCs feature new silicon capable of performing over 40 trillion operations per second (TOPS), providing all-day battery life and access to advanced AI models. These neural engines enhance the efficiency and speed of AI operations, enabling features like real-time language translation and image recognition. 4 min read - The SANS Institute — a leading authority in cybersecurity research, education and certification — released its annual Top Attacks and Threats Report. TPUs are custom ASICs developed by Google to accelerate machine learning workloads. One of the significant steps includes developing and integrating its own hardware to support AI models like Gemini. 2 min read - The restaurant industry has been hit with a rising number of cyberattacks in the last two years, with major fast-food chains as the primary targets. 4 min read - At the beginning of August, CISA announced that it had appointed Lisa Einstein, Senior Advisor of its artificial intelligence division, as its new chief AI officer. Another primary hardware type is the Field-Programmable Gate Array (FPGA) from Intel and other companies. FPGAs can be integrated with popular AI frameworks like TensorFlow and PyTorch using tools like the Intel FPGA AI Suite and the OpenVINO toolkit. This reorganization has led to the creation of a new Platforms and Devices team, consolidating various Google products like Pixel, Android, Chrome and ChromeOS under a single leadership. Google has made several changes to its hardware to accommodate AI. This move aims to accelerate AI integration and improve the synergy between hardware and software. We can look forward to AI-specific hardware trickling down beyond PCs and phones and into wearables, Internet of Things devices and more.
This Cyber News was published on securityintelligence.com. Publication date: Thu, 03 Oct 2024 14:13:07 +0000