Latest news with #MLPerf
Yahoo
9 hours ago
- Business
- Yahoo
Why CoreWeave, Inc. (CRWV) Skyrocketed Today
We recently published a list of . In this article, we are going to take a look at where CoreWeave, Inc. (NASDAQ:CRWV) stands against other Wednesday's best-performing stocks. CoreWeave rallied for a fourth consecutive day on Wednesday, jumping 8.39 percent to close at $163.10 apiece following the unveiling of record-breaking performance results using Nvidia Corp.'s latest Grace Blackwell chips. In a statement, CoreWeave, Inc. (NASDAQ:CRWV) said that it used 2,496 Nvidia GPUs on its AI-optimized cloud platform, making its submission the largest-ever benchmarked under MLPerf. A close-up of a digital cloud, signifying the expansive reach of the software-as-a-service solution. CoreWeave, Inc. (NASDAQ:CRWV) said that the test was 34x larger than the only other submission from a cloud provider. 'AI labs and enterprises choose CoreWeave because we deliver a purpose-built cloud platform with the scale, performance, and reliability that their workloads demand,' said CoreWeave, Inc. (NASDAQ:CRWV) Chief Technology Officer Peter Salanki. 'These MLPerf results reinforce our leadership in supporting today's most demanding AI workloads,' he added. The unveiling followed the company's new $7-billion deal with Applied Digital Corporation (NASDAQ:APLD), which covered two 15-year lease agreements, under which the latter will deliver 250 megawatts of critical IT load to host its artificial intelligence (AI) and high-performance computing (HPC) infrastructure at its Ellendale, North Dakota data center campus. READ NEXT: 20 Best AI Stocks To Buy Now and 30 Best Stocks to Buy Now According to Billionaires. Disclosure: None. This article is originally published at Insider Monkey.
Business Wire
2 days ago
- Business
- Business Wire
Literal Labs Raises £4.6M Pre-seed Round to Develop Energy-efficient Logic-based AI Worldwide
NEWCASTLE, England--(BUSINESS WIRE)-- Literal Labs, the logic-based AI algorithm company led by ex-Arm VP Noel Hurley, today announces that it has raised £4.6M ($6.2M USD) in pre-seed funding. The round is led by Northern Gritstone, the science and tech-focused investment firm from Northern England, and co-led by Mercuri, the London-based fund focused on companies at the intersection of media, entertainment and technology sectors, with participation from Sure Valley Ventures, Cambridge Future Tech SPV, and several angel investors. Literal Labs is pioneering logic-based AI models that are orders of magnitude faster, more energy efficient and more explainable than today's neural networks. Its approach is inspired by the work of Mikhail Tsetlin; a mathematician and contemporary of John Macarthy who pioneered neural networks. Like neural networks, the Tsetlin machine can perform complex machine learning training. However, unlike neural networks, it is based on propositional logic which makes it more efficient in terms of computation and energy usage, whilst speeding up inferencing. Recent MLPerf Anomaly detection benchmarking shows Literal Labs can achieve 54x faster inferencing than 'classic techniques' for machine learning applications, with 52x less energy consumption than equivalent neural networks. It also achieved 250x faster performance than XGBoost for machine learning applications. Literal Labs was spun out of Newcastle University by world leaders in logic-based AI, Dr. Alex Yakovlev and Dr. Rishad Shafik, along with company builder Cambridge Future Tech. Noel Hurley was later appointed CEO of Literal Labs in 2023, after having spent more than 20 years at Arm where he led its product marketing as well as its CPU division – which accounted for over 70% of revenue, totalling approximately $1bn. Literal Labs doubled its headcount from 6 to 12 in 2024, including appointing Leon Fedden – formerly AI Deep Learning platform lead at AstraZeneca – as Chief Technology Officer. The fresh injection of funding will be used to further grow its engineering team and bring its first commercial product to market later in 2025 for customers with EdgeAI who need to: Replace GPU-heavy algorithms which are too large, expensive or energy-intensive Operate in strict social or regulatory markets, in which explainability of AI is essential Have more efficient AI models for battery-based products Noel Hurley, CEO of Literal Labs, said: 'We're at a pivotal moment for AI with adoption continuing to accelerate alongside sustainability and cost concerns. Our logic-based AI offers a new solution for those that want and need high-performing AI that is faster, more energy efficient and more explainable than what's currently available via neural networks. This funding comes at a time when we're ready to significantly speed up our product development and will enable us to bring our first product to market later this year.' Duncan Johnson, CEO of Northern Gritstone, said: 'Literal Labs is Northern Gritstone's first investment linked to Newcastle University, renowned for its technology-related research. We are delighted to support Noel Hurley and the Literal Labs team at a time when innovation can truly benefit from greater efficiency in AI.' Esha Vatsa, Partner at Mercuri said: 'We are excited to back Literal Labs as it redefines AI with a radically efficient alternative to existing neural networks. The team, combining deep research expertise and proven industry leadership, is uniquely positioned to commercialise this innovation.' About Literal Labs Literal Labs is an AI algorithm company that uses logic-based techniques to generate custom AI models, which benchmarking studies have proven to be orders of magnitude faster, more energy-efficient and more explainable than neural networks. Its models are for companies that want to replace GPU-heavy algorithms that are too large, expensive and energy-intensive, for companies that operate in strict social or regulatory markets in which explainability of AI is essential, or for companies needing more efficient AI models for battery-based products. The company was spun out of Newcastle University by world leaders in logic-based AI, Dr. Alex Yakovlev and Dr. Rishad Shafik, and is led by former Arm CPU division VP and semiconductor startup founder, Noel Hurley. Read more at About Northern Gritstone Northern Gritstone is an investment company, dedicated to supporting ambitious science and technology businesses in the North of England. Its philosophy is 'profit with purpose' combining strong returns for investors with wider positive, societal and economic impact, including high-skilled job creation and regional growth. Active since May 2022, the company has made 37 investments to date in some of the UK's most exciting future businesses including semiconductor design and manufacturing; novel materials; secure computing; AI; healthtech; and gene therapies. Together with NG Innovation Services, Northern Gritstone offers 'Capital+++' connecting early-stage company founders with funding and expertise to scale their businesses. In April 2025, Northern Gritstone announced that it had raised further funding bringing its total committed capital to £362 million. About Mercuri Mercuri is an early-stage venture capital fund that leads pre-seed and seed funding rounds for UK technology companies. The firm is dedicated to backing outstanding entrepreneurs who are at the forefront of developing tech-driven products designed for the new age of enterprise and the digital lifestyle of the consumer. For more information, please go to:
Yahoo
2 days ago
- Business
- Yahoo
Literal Labs Raises £4.6M Pre-seed Round to Develop Energy-efficient Logic-based AI Worldwide
Led by ex-Arm VP Noel Hurley, Literal Labs uses logic-based techniques to generate AI models that are orders of magnitude faster, more energy efficient and more explainable than today's neural networks. The round is led by Northern Gritstone, the science and tech-focused investment firm from Northern England, and co-led by Mercuri, the London-based fund focused on companies at the intersection of media, entertainment, and technology sectors. Headquartered in Newcastle, Literal Labs will use the capital to bring its first commercial product to market, grow its engineering team and continue delivering on its vision for AI that improves life for all and treads lightly on our environment. NEWCASTLE, England, June 03, 2025--(BUSINESS WIRE)--Literal Labs, the logic-based AI algorithm company led by ex-Arm VP Noel Hurley, today announces that it has raised £4.6M ($6.2M USD) in pre-seed funding. The round is led by Northern Gritstone, the science and tech-focused investment firm from Northern England, and co-led by Mercuri, the London-based fund focused on companies at the intersection of media, entertainment and technology sectors, with participation from Sure Valley Ventures, Cambridge Future Tech SPV, and several angel investors. Literal Labs is pioneering logic-based AI models that are orders of magnitude faster, more energy efficient and more explainable than today's neural networks. Its approach is inspired by the work of Mikhail Tsetlin; a mathematician and contemporary of John Macarthy who pioneered neural networks. Like neural networks, the Tsetlin machine can perform complex machine learning training. However, unlike neural networks, it is based on propositional logic which makes it more efficient in terms of computation and energy usage, whilst speeding up inferencing. Recent MLPerf Anomaly detection benchmarking shows Literal Labs can achieve 54x faster inferencing than "classic techniques" for machine learning applications, with 52x less energy consumption than equivalent neural networks. It also achieved 250x faster performance than XGBoost for machine learning applications. Literal Labs was spun out of Newcastle University by world leaders in logic-based AI, Dr. Alex Yakovlev and Dr. Rishad Shafik, along with company builder Cambridge Future Tech. Noel Hurley was later appointed CEO of Literal Labs in 2023, after having spent more than 20 years at Arm where he led its product marketing as well as its CPU division – which accounted for over 70% of revenue, totalling approximately $1bn. Literal Labs doubled its headcount from 6 to 12 in 2024, including appointing Leon Fedden – formerly AI Deep Learning platform lead at AstraZeneca – as Chief Technology Officer. The fresh injection of funding will be used to further grow its engineering team and bring its first commercial product to market later in 2025 for customers with EdgeAI who need to: Replace GPU-heavy algorithms which are too large, expensive or energy-intensive Operate in strict social or regulatory markets, in which explainability of AI is essential Have more efficient AI models for battery-based products Noel Hurley, CEO of Literal Labs, said: "We're at a pivotal moment for AI with adoption continuing to accelerate alongside sustainability and cost concerns. Our logic-based AI offers a new solution for those that want and need high-performing AI that is faster, more energy efficient and more explainable than what's currently available via neural networks. This funding comes at a time when we're ready to significantly speed up our product development and will enable us to bring our first product to market later this year." Duncan Johnson, CEO of Northern Gritstone, said: "Literal Labs is Northern Gritstone's first investment linked to Newcastle University, renowned for its technology-related research. We are delighted to support Noel Hurley and the Literal Labs team at a time when innovation can truly benefit from greater efficiency in AI." Esha Vatsa, Partner at Mercuri said: "We are excited to back Literal Labs as it redefines AI with a radically efficient alternative to existing neural networks. The team, combining deep research expertise and proven industry leadership, is uniquely positioned to commercialise this innovation." About Literal Labs Literal Labs is an AI algorithm company that uses logic-based techniques to generate custom AI models, which benchmarking studies have proven to be orders of magnitude faster, more energy-efficient and more explainable than neural networks. Its models are for companies that want to replace GPU-heavy algorithms that are too large, expensive and energy-intensive, for companies that operate in strict social or regulatory markets in which explainability of AI is essential, or for companies needing more efficient AI models for battery-based products. The company was spun out of Newcastle University by world leaders in logic-based AI, Dr. Alex Yakovlev and Dr. Rishad Shafik, and is led by former Arm CPU division VP and semiconductor startup founder, Noel Hurley. Read more at About Northern Gritstone Northern Gritstone is an investment company, dedicated to supporting ambitious science and technology businesses in the North of England. Its philosophy is 'profit with purpose' combining strong returns for investors with wider positive, societal and economic impact, including high-skilled job creation and regional growth. Active since May 2022, the company has made 37 investments to date in some of the UK's most exciting future businesses including semiconductor design and manufacturing; novel materials; secure computing; AI; healthtech; and gene therapies. Together with NG Innovation Services, Northern Gritstone offers 'Capital+++' connecting early-stage company founders with funding and expertise to scale their businesses. In April 2025, Northern Gritstone announced that it had raised further funding bringing its total committed capital to £362 million. About Mercuri Mercuri is an early-stage venture capital fund that leads pre-seed and seed funding rounds for UK technology companies. The firm is dedicated to backing outstanding entrepreneurs who are at the forefront of developing tech-driven products designed for the new age of enterprise and the digital lifestyle of the consumer. For more information, please go to: View source version on Contacts Media contact Connor Mitchellconnor@ Commplicated Fehler beim Abrufen der Daten Melden Sie sich an, um Ihr Portfolio aufzurufen. Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten Fehler beim Abrufen der Daten
Globe and Mail
07-05-2025
- Business
- Globe and Mail
Intel Excels in Stringent AI Benchmark: Should You Buy the Stock?
Intel Corporation INTC recently announced that it has successfully achieved industry-first full NPU (Neural Processing Unit) compliance in the MLPerf Client v0.6 benchmark. MLPerf is an industry-standard benchmarking suite created to assess AI system performance. The newly released MLPerf Client v0.6 Benchmark is a subset of MLPerf designed to evaluate client devices such as laptops and PCs with a strong emphasis on large language model acceleration and NPU performance. It offers a clear assessment of hardware and software capabilities in swiftly handling AI tasks such as content generation and summarization. During the process, Intel Core Ultra Series 2 processors showcased the fastest NPU response time with an impressive token latency of just 1.09 seconds and the highest NPU throughput at 18.55 tokens per second. Intel also demonstrated remarkable GPU performance during the process. Intel Core Ultra processor is the only NPU to achieve complete compliance, accentuating its strong AI compute capabilities. Intel Rides on AI Traction, Portfolio Optimization Intel has been taking several strategic decisions to gain a firmer footing in the expansive AI sector, spanning cloud and enterprise servers to networks, volume clients, and ubiquitous edge environments, in line with the evolving market dynamics. Intel's Xeon 6 processors with Performance-cores have garnered significant industry attention owing to their high-performance AI processing. Intel XEON platforms offer extensive performance improvements coupled with energy efficiency and easy-to-deploy software. With these features, Intel XEON has set a new benchmark in 5G cloud native core, which is driving demand from software vendors and independent telecom manufacturers. The company is witnessing solid market traction in the AI PC market. Backed by strong demand for its core Ultra Chips, Intel remains firmly on track to power more than 100 million AI PCs by the end of 2025. Intel is also venturing into the automotive market to capitalize on the growing AI proliferation in that industry. The company's second-generation AI-powered software-defined vehicle system-on-chip with multi-process node chiplet architecture brings advanced capabilities. The chip offers 10x performance enhancement for generative and multimodal AI, 3x graphics performance, and enhances camera and image processing features. Such state-of-the-art features will boost Intel's new AI chip demand in Advanced Driver Assistance Systems. Intel is divesting 51% of its Altera business to Silver Lake, a prominent global technology investment firm. The move highlights Intel's strategy to reshape its portfolio, optimize cost structure, strengthen its liquidity position, and boost focus on core operations. One-Year INTC Stock Price Performance Intel has plunged 33.3% in the past year against the industry 's growth of 18.7%. The company has underperformed its peer NVIDIA Corporation NVDA but outperformed Advanced Micro Devices, Inc. AMD. INTC Plagued by Margin Woes Despite investing heavily in new chip design and manufacturing, Intel is playing a catch-up game with NVIDIA and AMD. In the CPU space, AMD has gained a strong foothold with its Ryzen and EPYC processors. AMD's strategy of offering competitive pricing with high performance has challenged Intel's dominance in the CPU market. In the graphics and AI acceleration space, NVIDIA has made significant inroads. It is witnessing strong demand for generative AI and large language models using GPUs based on NVIDIA Hopper and Blackwell architectures. Backed by strong industry expertise, both NVIDIA and AMD are aiming to expand their influence in the automotive segment. Intensifying competition with NVIDIA and AMD across multiple end markets is weighing on Intel's margin. Intel's debt-to-capital ratio stands at 32% compared to the industry average of 17.3%. As of March 31, 2025, Intel had cash and cash equivalents of $8.95 billion with $44.91 billion of long-term debt. A high debt level may limit sufficient cash flow generation, which is required to meet future debt obligations. Additionally, Intel has a significant presence in China. Growing Sino-U.S. trade hostilities can impact its operations. Estimate Revision Trend of INTC Earnings estimates for Intel for 2025 have moved down 37.5% to 30 cents over the past 60 days, while the same for 2026 has declined 28.32% to 81 cents. The negative estimate revision depicts bearish sentiments for the stock. End Note Intel's strong AI focus and the expansion of its portfolio offerings for AI PCs, data centers, and automotive markets are commendable. Its effort to lower costs and improve liquidity with strategic divestiture is a positive. However, intensifying competition in the commercial PC, server, storage and networking markets remains a major headwind. In addition, its high dependence on China, imposition of trade tariffs, and Beijing's move to replace U.S.-made chips with domestic alternatives are impeding Intel's commercial prospects. Its high debt levels make it vulnerable to economic downturns and growing geopolitical unrest. Declining earnings estimate revisions underscore dwindling investors' confidence. Despite heavy investment in chipset innovation and AI acceleration, Intel's ability to regain a competitive edge appears to be a challenging endeavor. Intel carries a Zacks Rank #3 (Hold) at present. You can see the complete list of today's Zacks #1 Rank (Strong Buy) stocks here. 5 Stocks Set to Double Each was handpicked by a Zacks expert as the #1 favorite stock to gain +100% or more in 2024. While not all picks can be winners, previous recommendations have soared +143.0%, +175.9%, +498.3% and +673.0%. Most of the stocks in this report are flying under Wall Street radar, which provides a great opportunity to get in on the ground floor. Today, See These 5 Potential Home Runs >> Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Intel Corporation (INTC): Free Stock Analysis Report NVIDIA Corporation (NVDA): Free Stock Analysis Report
Reuters
02-04-2025
- Business
- Reuters
New AI benchmarks test speed of running AI applications
SAN FRANCISCO, April 2 (Reuters) - Artificial intelligence group MLCommons unveiled two new benchmarks that it said can help determine how quickly top-of-the-line hardware and software can run AI applications. Since the launch of OpenAI's ChatGPT over two years ago, chip companies have begun to shift their focus to making hardware that can efficiently run the code that allows millions of people to use AI tools. As the underlying models must respond to many more queries to power AI applications such as chatbots and search engines, MLCommons developed two new versions of its MLPerf benchmarks to gauge speed. One of the new benchmarks is based on Meta's (META.O), opens new tab so-called Llama 3.1 405-billion-parameter AI model, and the test targets general question answering, math and code generation. The new format tests a system's ability to process large queries and synthesize data from multiple sources. Nvidia (NVDA.O), opens new tab submitted several of its chips for the benchmark, and so did system builders such as Dell Technologies (DELL.N), opens new tab. There were no Advanced Micro Devices (AMD.O), opens new tab submissions for the large 405-billion-parameter benchmark, according to data provided by MLCommons. For the new test, Nvidia's latest generation of artificial intelligence servers - called Grace Blackwell, which have 72 Nvidia graphics processing units (GPUs) inside - was 2.8 to 3.4 times faster than the previous generation, even when only using eight GPUs in the newer server to create a direct comparison to the older model, the company said at a briefing on Tuesday. Nvidia has been working to speed up the connections of chips inside its servers, which is important in AI work where a chatbot runs on multiple chips at once. The second benchmark is also based on an open-source AI model built by Meta and the test aims to more closely simulate the performance expectations set by consumer AI applications such as ChatGPT. The goal is to tighten the response time for the benchmark and make it close to an instant response.
