Latest news with #MachineLearning
Business Wire
20 hours ago
- Business
- Business Wire
Renesas Sets New MCU Performance Bar with 1-GHz RA8P1 Devices with AI Acceleration
TOKYO--(BUSINESS WIRE)--Renesas Electronics Corporation (TSE:6723), a premier supplier of advanced semiconductor solutions, today introduced the RA8P1 microcontroller (MCU) Group targeted at Artificial Intelligence (AI) and Machine Learning (ML) applications, as well as real-time analytics. The new MCUs establish a new performance level for MCUs by combining 1GHz Arm ® Cortex ® -M85 and 250MHz Cortex-M33 CPU cores with the Arm Ethos™-U55 Neural Processing Unit (NPU). This combination delivers the highest CPU performance of over 7300 CoreMarks and AI performance of 256 GOPS at 500 MHz. Designed for Edge/Endpoint AI The RA8P1 is optimized for edge and endpoint AI applications, using the Ethos-U55 NPU to offload the CPU for compute intensive operations in Convolutional and Recurrent Neural Networks (CNNs and RNNs) to deliver up to 256 MACs per cycle that yield 256 GOPS performance at 500 MHz. The new NPU supports most commonly used networks, including DS-CNN, ResNet, Mobilenet TinyYolo and more. Depending on the neural network used, the Ethos-U55 provides up to 35x more inferences per second than the Cortex-M85 processor on its own. Advanced Technology The RA8P1 MCUs are manufactured on the 22ULL (22nm ultra-low leakage) process from TSMC, enabling ultra-high performance with very low power consumption. This process also enables the use of embedded Magnetoresistive RAM (MRAM) in the new MCUs. MRAM offers faster write speeds along with higher endurance and retention compared with Flash. 'There is explosive growth in demand for high-performance edge AIoT applications. We are thrilled to introduce what we believe are the best MCUs to address this trend,' said Daryl Khoo, Vice President of Embedded Processing Marketing Division at Renesas. 'The RA8P1 devices showcase our technology and market expertise and highlight the strong partnerships we have built across the industry. Customers are eager to employ these new MCUs in multiple AI applications.' 'The pace of innovation in the age of AI is faster than ever, and new edge use cases demand ever-improving performance and machine learning on-device,' said Paul Williamson, senior vice president and general manager, IoT Line of Business at Arm. 'By building on the advanced AI capabilities of the Arm compute platform, Renesas' RA8P1 MCUs meet the demands of next generation voice and vision applications, helping to scale intelligent, context-aware AI experiences.' 'It is gratifying to see Renesas harness the performance and reliability of TSMC 22ULL embedded MRAM technology to deliver outstanding results for its RA8P1 devices,' said Chien-Hsin Lee, Senior Director of Specialty Technology Business Development at TSMC. 'As TSMC continues to advance our embedded non-volatile memory (eNVM) technologies, we look forward to strengthening our long-standing collaboration with Renesas to drive innovation in future groundbreaking devices.' Robust, Optimized Peripheral Set for AI Renesas has integrated dedicated peripherals, ample memory and advanced security to address Voice and Vision AI and Real-time Analytics applications. For vision AI, a 16-bit camera interface (CEU) is included that supports sensors up to 5 megapixels, enabling camera and demanding Vision AI applications. A separate MIPI CSI-2 interface offers a low pin-count interface with two lanes, each up to 720Mbps. In addition, multiple audio interfaces including I 2 S and PDM support microphone inputs for voice AI applications. The RA8P1 offers both on-chip and external memory options for efficient, low latency neural network processing. The MCU includes 2MB SRAM for storing intermediate activations or graphics framebuffers. 1MB of on-chip MRAM is also available for application code and storage of model weights or graphics assets. High-speed external memory interfaces are available for larger models. SIP options with 4 or 8 MB of external flash in a single package are also available for more demanding AI applications. New RUHMI Framework Along with the RA8P1 MCUs, Renesas has introduced RUHMI (Renesas Unified Heterogenous Model Integration), a comprehensive framework for MCUs and MPUs. RUHMI offers efficient AI deployment of the latest neural network models in a framework agnostic manner. It enables model optimization, quantization, graph compilation and conversion, and generates efficient source code. RUHMI provides native support for machine-learning AI frameworks such as TensorFlow Lite, Pytorch & ONNX. It also provides the necessary tools, APIs, code-generator, and runtime needed to deploy a pre-trained neural network, including ready-to-use application examples and models optimized for RA8P1. RUHMI is integrated with Renesas's own e 2 Studio IDE to allow seamless AI development. This integration will facilitate a common development platform for MCUs and MPUs. Advanced Security Features The RA8P1 MCUs provide leading-edge security for critical applications. The new Renesas Security IP (RSIP-E50D) includes numerous cryptographic accelerators, including CHACHA20, Ed25519, NIST ECC curves up to 521 bits, enhanced RSA up to 4K, SHA2 and SHA3. In concert with Arm TrustZone ®, this provides a comprehensive and fully integrated secure element-like functionality. The new MCUs also provides strong hardware Root-of-Trust and Secure Boot with First Stage Bootloader (FSBL) in immutable storage. XSPI interfaces with decryption-on-the-fly (DOTF) allow encrypted code images to be stored in external flash and decrypted on the fly as it is securely transferred to the MCU for execution. Ready to Use Solutions Renesas provides a wide range of easy-to-use tools and solutions for the RA8P1 MCUs, including the Flexible Software Package (FSP), evaluation kits and development tools. FreeRTOS and Azure RTOS are supported, as is Zephyr. Several Renesas software example projects and application notes are available to enable faster time to market. In addition, numerous partner solutions are available to support development with the RA8P1 MCUs, including a driver monitoring solution from and a traffic/pedestrian monitoring solution from Irida Labs. Other solutions can be found at the Renesas RA Partner Ecosystem Solutions Page. Key Features of the RA8P1 MCUs Processors: 1GHz Arm Cortex-M85, 500MHz Ethos-U55, 250 MHz Arm Cortex-M33 (Optional) Memory: 1MB/512KB On-chip MRAM, 4MB/8MB External Flash SIP Options, 2MB SRAM fully ECC protected, 32KB I/D caches per core Graphics Peripherals: Graphics LCD controller supporting resolutions up to WXGA (1280x800), parallel RGB and MIPI-DSI display interfaces, powerful 2D Drawing engine, parallel 16bit CEU and MIPI CSI-2 camera interfaces, 32bit external memory bus (SDRAM and CSC) interface Other Peripherals: Gigabit Ethernet and TSN Switch, XSPI (Octal SPI) with XIP and DOTF, SPI, I2C/I3C, SDHI, USBFS/HS, CAN-FD, PDM and SSI audio interfaces, 16bit ADC with S/H circuits, DAC, comparators, temperature sensor, timers Security: Advanced RSIP-E50D cryptographic engine, TrustZone, Immutable storage, secure boot, tamper resistance, DPA/SPA attack protection, secure debug, secure factory programming, Device Lifecycle management Packages: 224BGA, 289BGA Winning Combinations Renesas has combined the new RA8P1 MCUs with numerous compatible devices from its portfolio to offer a wide array of Winning Combinations, including Video Conferencing Camera with AI Capabilities, AI Drawing Robot Arm and AI-Enabled Surveillance Camera. These designs are technically vetted system architectures from mutually compatible devices that work together seamlessly to bring an optimized, low-risk design for faster time to market. Renesas offers more than 400 Winning Combinations with a wide range of products from the Renesas portfolio to enable customers to speed up the design process and bring their products to market more quickly. They can be found at Availability The RA8P1 MCUs are available now. Renesas is also shipping an RA8P1 Evaluation Kit. More information is available at Samples and kits can be ordered either on the Renesas website or through distributors. Renesas MCU Leadership A world leader in MCUs, Renesas ships more than 3.5 billion units per year, with approximately 50% of shipments serving the automotive industry, and the remainder supporting industrial and Internet of Things applications as well as data center and communications infrastructure. Renesas has the broadest portfolio of 8-, 16- and 32-bit devices, delivering unmatched quality and efficiency with exceptional performance. As a trusted supplier, Renesas has decades of experience designing smart, secure MCUs, backed by a dual-source production model, the industry's most advanced MCU process technology and a vast network of more than 250 ecosystem partners. For more information about Renesas MCUs, visit About Renesas Electronics Corporation Renesas Electronics Corporation (TSE: 6723) empowers a safer, smarter and more sustainable future where technology helps make our lives easier. A leading global provider of microcontrollers, Renesas combines our expertise in embedded processing, analog, power and connectivity to deliver complete semiconductor solutions. These Winning Combinations accelerate time to market for automotive, industrial, infrastructure and IoT applications, enabling billions of connected, intelligent devices that enhance the way people work and live. Learn more at Follow us on LinkedIn, Facebook, X, YouTube and Instagram. (Remarks). All names of products or services mentioned in this press release are trademarks or registered trademarks of their respective owners.
Time of India
a day ago
- Business
- Time of India
IBM SkillsBuild AI & Cloud Internship 2025: Key dates, benefits, eligibility, application deadline & more
Live Events Why Should You Join? Key Perks Eligibility Criteria Requirements (You can now subscribe to our (You can now subscribe to our Economic Times WhatsApp channel The IBM SkillsBuild for Academia Internship 2025, conducted in collaboration with Edunet Foundation, is a 4-week intensive virtual internship designed to help students gain hands-on skills in Artificial Intelligence, Machine Learning, and IBM Cloud technologies according to initiative is part of IBM's global commitment to building job-ready digital talent, and is an ideal opportunity for students aiming to boost their technical profile and industry exposure—all from the comfort of Edunet Foundation in collaboration with IBM SkillsBuildStart Date: 10th July 2025Duration: 4 weeksMode: Online [Open PAN India]Stipend: Unpaid (Certificate + Digital Industry Badges Provided)Application Deadline: 3rd July 2025Gain real-world knowledge in AI, ML, and Cloud Computing, which are among the most sought-after tech skills in hands-on cloud-based projects, work in collaborative environments, and build a portfolio to enhance your IBM's industry-grade cloud software and learning resources to simulate real-world development successful completion, receive IBM SkillsBuild Certificates and digital badges that can be showcased on LinkedIn or your from professional mentors and trainers with experience in cutting-edge AI and cloud Certification from IBM and Edunet FoundationHands-on Cloud and AI TrainingPeer Collaboration on real-time projectsAccess to IBM's Learning Platform free of costSkill Development Workshops with guided mentorshipThe internship is open to students across India from the following streams:Engineering: BE/BTech in CS, IT, Electronics, or Allied fieldsComputer Applications: BCA/MCADiploma/Vocational: IT, CS, or ITIPreference: Pre-final and final-year studentsValid college email ID for IBM Cloud registrationBasic understanding of Python, AI/ML conceptsAccess to a PC/Laptop with internet for project work
The Hindu
a day ago
- Business
- The Hindu
AI in Legal Education: The Hindu's webinar with experts from NUJS, KS Legal and Law Firm Ready
Case backlogs have been a persistent issue for the Indian judiciary. To resolve it, AI-powered technologies—including Machine Learning (ML), Natural Language Processing (NLP), Optical Character Recognition (OCR), and Predictive Analytics are now being leveraged to automate administrative tasks, improve case tracking, and enhance crime prevention. The Government of India has allocated a total of ₹7210 Crore for the e-Courts Phase III project for judicial digital transformation. Within this budget, ₹53.57 Crore is specifically earmarked for the integration of AI and Blockchain technologies across High Courts in India. This deployment of AI is not limited to the judiciary, but top-tier law firms in the country have also adapted AI tools for routine work. AI has changed workflows by streamlining research, drafting, and due diligence while raising important questions around ethics, bias, and the future of legal education. To keep up with these developments, law schools need to update their curricula with AI integration to ensure students remain employable. Some institutes have taken initial steps towards AI teaching and learning. In the long run, though, institutes will need to provide students with practical, hands-on exposure to AI tools. Students need to be taught to adapt to technology while preserving the core principles of legal education. They need to sharpen their critical assessment skills to verify AI-generated content, check legal citations, and ensure jurisdictional relevance. To discuss how this change can be brought forth, The Hindu will host a webinar titled 'Gamechanger: Teaching AI to law students, lawyers', on July 5 at 5:00 p.m. The panellists include Shouvik Kumar Guha, Associate Professor, NUJS; Sonam Chandwani, Managing Partner, KS Legal & Associates; Rohit Sharma, Founder, Law Firm Ready. The webinar will be moderated by Ravina Warkad, who works at the education vertical of The Hindu. Register now for free to ask questions and interact with the panellists. Those who ask the three best questions will receive a free online subscription to The Hindu. Panellists Shouvik Kumar Guha, Associate Professor, NUJS Shouvik Kumar Guha is currently serving as an Associate Professor of Law and Technology at The West Bengal National university of Juridical Sciences (NUJS). He is also the Founding Director of the Centre for Law, Literature and Popular Culture, the Associate Director of the Centre for Aviation and Space Laws, and the Assistant Director of the Centre for Financial and Regulatory Governance Studies, the Centre for Competition Laws and Centre for Law and Technology at NUJS. He is also a TEDx speaker, a Senior Research Fellow (Non-Resident) at the Vidhi Centre for Law and Policy, Associate Research Fellow (Non-Resident) at the Centre for Responsible Artificial Intelligence (CeRAI), IIT Madras, a Visiting Faculty at the Rajiv Gandhi School of Intellectual Property Law, IIT Kharagpur, and at the Indian Institute of Management, Rohtak, as well as an Honorary Adjunct Professor at the Institute for Advancing Intelligence (IAI) of TCG Centres for Research and Education in Science and Technology (TCG CREST). Sonam Chandwani, Managing Partner, KS Legal & Associates Sonam Chandwani is the Managing Partner at KS Legal & Associates and heads the firm's Corporate Litigation Practice. She specialises in commercial structures, commercial litigation, mergers and acquisitions generally, with an emphasis on large-scale and complex commercial litigation including contract law, trade practices, real estate disputes and finance issues across a range of industry sectors. She advises on insolvency matters and her expertise covers all forms of dispute resolution, arbitration and mediation. Rohit Sharma, Founder, Law Firm Ready Rohit Sharma is an alumnus from the National University of Juridical Sciences (NUJS), Kolkata. After working with organisations such as Cyril Amarchand Mangaldas, Jansahas, he founded Awaaz Leadership Labs(ALL) and Law Firm Ready. His organisation has so far trained 10,000+ law students from over 650 law schools in the country. He is currently working on building differential learning pedagogies in legal education and working towards reforms in clinical legal education. Mr. Sharma has also served as researcher at Lakshmi Mittal South Asian Institute, Harvard University, where he researches on 'History of Punishment in India'. (2022-2025). He is the conceptualiser of NUJS Diversity Report, MP Migrants Report, Vernacular Legal Blogs Series(JILS) and Reforms in Legal education Interview Series (JILS). (For any feedback or suggestions, reach out to us at education@
Al Etihad
a day ago
- Business
- Al Etihad
TRENDS study explores the use of AI in journalism
1 July 2025 10:44 ABU DHABI (ALETIHAD)TRENDS Research & Advisory has released a new study — AI-Generated Content in Journalism: The Rise of Automated Reporting — examining the profound transformation within the media sector due to rapid advances in artificial intelligence (AI) by lead researcher Nour Al-Mazrouei, Head of the AI and Advanced Technology Program at TRENDS, the study highlights how AI tools based on Natural Language Processing (NLP) and Machine Learning (ML) are being used to produce fast and accurate news content—particularly in data-driven fields such as financial, sports, and weather study emphasises key outcomes, notably the increase in production reporting systems, such as those used by the Associated Press for financial coverage, can generate thousands of articles in record it also warns of the risk of 'hallucination' in AI models—where systems may produce inaccurate or biased information due to limitations in training study stresses the importance of upholding traditional journalistic values such as integrity and diversity while leveraging AI efficiency. It recommends enhancing human review mechanisms for AI-generated content, developing ethical frameworks to guide AI use in newsrooms, and investing in training journalists to work with digital tools. This publication is part of TRENDS' research series on the impact of emerging technologies on vital sectors, and their role in shaping the future of media. Source: Aletihad - Abu Dhabi
Techday NZ
a day ago
- Business
- Techday NZ
How AI agents can help enterprise teams to scale
As the pace of change in the business world constantly increases, enterprise leaders are faced with mounting challenges. These include rising costs, complex operations, and increasing board pressure to do more with less while delivering upon the promised land of AI. Traditional approaches to scaling, such as hiring more staff or relying on rigid automation, are proving inadequate. Instead, a new paradigm is taking shape, built around the power of AI agents. According to Gartner, by 2028, 33% of enterprises will be using agentic AI systems - a dramatic increase from less than 1% today. This signals a strategic pivot in how organisations operate and grow. AI agents are not just a technology trend but are quickly becoming a critical component of the modern enterprise toolkit. From automation to adaptation The concept of AI agents goes well beyond conventional automation. While older tools follow pre-programmed rules, AI agents are designed to be intelligent, adaptive, and responsive in real-time. Using technologies such as Natural Language Understanding (NLU), Machine Learning (ML), and large language models (LLMs), these agents can understand context, make decisions, and act autonomously. Rather than replacing workers, these AI agents operate alongside them anticipating needs, streamlining processes, and enabling businesses to scale efficiently without proportionally increasing their overheads. Reinventing workflows with intelligence The impact of AI agents on productivity is profound. In today's workplace, time is often lost in mundane tasks such as resolving routine issues, switching between disconnected systems, or searching endlessly for relevant information. AI agents address these inefficiencies head-on. By analysing historical data, they can proactively identify patterns and respond to business needs before they become problems. For example, IT support AI agents can detect common issues and resolve them automatically, minimising downtime. In sales, they can recommend tailored strategies based on past performance and customer behaviour. Another area where AI agents shine is in orchestrating complex workflows. They connect tools and platforms across an organisation including Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and Human Resources (HR). This ensures data flows smoothly and teams work cohesively. Perhaps most notably, these agents bring intelligence to everyday interactions. A smart enterprise search function, for instance, doesn't just return keyword matches. With retrieval-augmented generation (RAG) technology, it understands user intent and delivers contextually relevant, actionable information drawn from multiple systems in just seconds. Addressing the problem of fragmentation Information silos have long plagued enterprises. Studies indicate that knowledge workers spend nearly a third of their time simply searching for information. This inefficiency translates into massive productivity losses. AI agents can offer a solution here too. RAG-powered enterprise search breaks down silos by aggregating and interpreting data from across platforms. It gives users exactly what they need, when they need it, thus eliminating the frustrating and time-consuming process of switching between tools. Beyond finding information, these agents can act on it. They can trigger tasks, populate reports, or initiate workflows without human intervention. What sets enterprise-ready AI agents apart While the AI market is crowded, not all agents are created equally. Truly transformative systems share several core characteristics that enable scale without sacrificing control. First, contextual understanding is essential. The best agents, powered by LLMs and other AI models, grasp the meaning behind queries and provide not just answers but insights. Second, the ability to work in tandem with other agents and systems allows for seamless execution of multi-step, cross-platform workflows. Ease of customisation is also critical. Here, no-code tools that make it possible for non-technical users to build and tailor agents to their specific needs make AI deployment accessible across departments and delivered at pace. And finally, enterprise-grade security ensures that these innovations don't come at the expense of compliance or data integrity. With robust governance frameworks, companies can scale AI usage with confidence. The smarter way to scale The evolution of AI agents represents more than a technological advance. It marks a fundamental shift in how enterprises approach growth. It's no longer about adding more people or investing in rigid systems. It's about creating intelligent, agile workplaces where humans and machines collaborate to achieve more. Enterprises now have the tools to scale without friction, unify their operations, and adapt rapidly to market changes. As the corporate landscape becomes more dynamic and complex, AI agents are poised to be the force multipliers of the future, helping organisations not just survive, but thrive.
