Latest news with #MarkPapermaster
Forbes
13-06-2025
- Business
- Forbes
AMD Surpasses AI Energy Efficiency Goal And Sets Critical Industry Bar
AMD Chief Technology Officer Mark Papermaster In a surprising achievement for the semiconductor industry, AMD announced that it has surpassed its ambitious 30x25 energy efficiency goal, accelerating its green initiatives in AI and high-performance computing systems. What started as a bold target in 2020 to improve energy efficiency by 30 times over a five year span, has culminated in a remarkable 38x improvement—a feat achieved ahead of schedule no less. As the industry faces the growing demands of AI workloads, AMD's latest achievement signals not only the company's technical chops but its commitment to driving more sustainable solutions in accelerated computing. AMD Surpasses Its 25x30 Energy Efficiency Goal Set Back In 2020 In a quick fireside chat with AMD's Chief Technology Officer, Mark Papermaster, I was able to glean more insight into how the company was approaching this greener footprint for AI data centers. Mark was quick to credit the company's success to a comprehensive, holistic approach to chip design and system architecture. 'Energy efficiency doesn't come from just one facet of technology,' Papermaster explained in our meeting. 'It's not just about the silicon, the chiplets, or even the software. It's all these elements coming together—architecture, design, packaging, software, and even data center infrastructure—that enables real efficiency at scale.' This integrated approach became especially evident in the design of AMD's MI300 accelerator, which saw key advancements in 3D stacking and chip interconnect. The latter, in particular, was pivotal in improving performance-per-watt metrics of the GPU. As Papermaster highlighted, 'When you stack chips vertically, you can achieve up to a 20x improvement in energy efficiency, compared to traditional lateral design approaches.' Looking forward, the next generation of AMD chips—AMD's MI350 Series, which was just announced yesterday—is expected to push the envelope even further. These cutting-edge chips, with 3nm GPU chiplets and new matrix math formats, are expected to boost energy efficiency by another 35x over the previous generation, positioning AMD to better compete against Nvidia's most powerful Blackwell GPUs and systems. That said, while the 38x energy efficiency gain is a milestone, it is not the end of the road for AMD. As AMD Senior Vice President Samuel Naffziger shared in a recent company release, AMD has already shifted focus to its next ambitious goal: a 20x improvement in rack-scale energy efficiency by 2030. 'The 20x by 2030 rack-scale goal reflects the next frontier, not just focused on chips, but smarter and more efficient systems, from silicon to full rack integration to address data center level power requirements.,' Naffziger explained. AMD has shown that node-level efficiency gains can be transformative, but as AI workloads scale, the most significant impact will be at the system level. By 2030, AMD aims to achieve a 20x improvement in energy efficiency for entire racks of AI systems. In addition, Papermaster explained that these efficiency goals were 'one of the motivators for AMD in acquiring ZT Systems, so that AMD now has 1000 rack design engineers to help us optimize, get those connection lengths minimized, you know, provide energy efficiency hooks wherever we can.' This new target, set with a 2024 baseline, signals a major shift in how AMD views AI energy efficiency. Instead of focusing purely on individual chip performance, the company is looking at full system optimization—from CPUs and GPUs to networking, memory, and storage. It's another lofty goal, but in a day and age where hyperscalers like Google, AWS and Azure are actively exploring nuclear power plants to feed their hungry data centers, it's also a necessary goal for the planet as well. AMD Rack-Scale 20X30 Efficiency Goal Consolidates 275 Racks Of AI Servers Into A Single Rack The potential impact of this new 20x by 2030 goal is significant. According to AMD's projections, this leap could reduce the operational electricity use of a typical AI rack by more than 95% and slash carbon emissions from around 3,000 metric tons of CO2 to just 100 metric tons for model training specifically. The improvements also promise dramatic gains in operational efficiency, potentially consolidating 275 racks into just one fully utilized rack. In addition, AMD's 20x30 vision isn't limited to hardware alone. While its energy efficiency goals primarily focus on silicon and system design, the company acknowledges that software will also play a significant role. As software developers continue to innovate with more efficient algorithms and lower-precision, quantized approaches, overall AI efficiency could improve by as much as 100x by the year 2030. For AMD, this will be driven by new opportunities for collaboration with the broader ecosystem. Through its open-source software initiatives, such as its ROCm (Radeon Open Compute platform), and close partnerships with AI innovators like OpenAI and others, AMD is targeting to position itself as a key enabler of sustainable AI solutions. As AMD closes out one chapter with the success of its 30x25 initiative, the company is already setting the stage for its next big efficiency challenge. With its sights set on the 20x by 2030 rack-scale goal, the company is attempting to push the limits of what's possible in AI energy efficiency. 'Think about the total cost of ownership equation too. It's how much you're charging for the product and how much floor space it consumes. And what's the power draw? Because I've got to pay for the power. Those are the elements of TCO. So this energy efficiency is directly in the buying consideration of all our customers,' notes Papermaster. Regardless, in this new era of AI-accelerated everything, where every watt counts, AMD appears committed to pushing both performance and energy efficiency. These efforts and goals could help to shape the future of how the industry scales AI—responsibly and sustainably.
Yahoo
13-06-2025
- Business
- Yahoo
AMD (AMD) Unveils 1,400W MI355X AI GPU to Challenge Nvidia's Blackwell
AMD (AMD, Financials) officially launched its Instinct MI355X GPU accelerator Wednesday, showcasing a massive leap in compute power and energy demands as it competes with Nvidia's Blackwell Ultra B300. Warning! GuruFocus has detected 3 Warning Signs with AMD. The MI355X is part of AMD's new CDNA 4 architecture and is optimized for AI inference. With support for FP4, FP6, FP8, and FP16 precision, the MI355X delivers up to 20.1 PFLOPS in FP4/FP6 workloads and 10.1 PFLOPS in FP8, slightly ahead of Nvidia's B300 at 15 FP4 PFLOPS. To support this performance, the MI355X consumes 1,400W peak, nearly doubling the 750W required by its predecessor, the MI300X. AMD expects some users may still air-cool the chip, but liquid cooling is the standard. The GPU includes 288 GB of HBM3E memory with bandwidth reaching 8 TB/s. A scaled 8-way configuration brings system-level performance to 161 PFLOPS (FP4) and 80.5 PFLOPS. While raw compute marks a win on paper, AMD still trails Nvidia in deployment scale and software ecosystem. Pegatron is reportedly preparing a 128-way MI350X system, but Nvidia remains dominant in large-scale AI training clusters. AMD's Chief Technology Officer Mark Papermaster said zettascale supercomputing by 2035 will require processors consuming up to 2,000W each. He projected that future AI systems may need nuclear-scale powerup to 500 MW per machine. This article first appeared on GuruFocus. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Business Insider
08-06-2025
- Business
- Business Insider
Nvidia's competitors are gaining traction in these key industries
Startups selling alternatives to Nvidia's famed graphics processing units are unlikely to truly challenge Nvidia for a long time. But they defiantly claim superior performance, speed, energy efficiency, cost, or all of the above. Gusto is mandatory for teams wishing to compete against its 10-year headstart, virtually unlimited resources, and more than 70% market share. The answer to who's buying Nvidia alternatives is coming into focus alongside the financial value of AI tools and the total volume of AI use. "Competitors have a window to really carve out their niche," Karl Mozurkewich, senior principal AI architect for cloud firm Valdi, told Business Insider. For efficiency's sake Nvidia chips are considered at the cutting edge of accelerated computing. But they're also expensive and require immense power at scale, and in some cases, companies seek more targeted, energy or space-efficient solutions. When companies want to diversify away from Nvidia, they often turn to AMD, which also makes a GPU. Mark Papermaster, AMD's CTO, told BI that moving workloads from one GPU to another is always going to be the easiest move, from a technical perspective. And AMD is directing resources toward its software to make this as easy as possible. But some industries are particularly keen to look outside those two contenders. If inference volume is high enough and uniform enough, it makes financial sense to invest in making an alternative chip architecture work for certain workloads, Robert Wachen, cofounder of Etched, one of the newer entrants to the chips space, told BI. "When you're inferencing, it really matters to find the right processor that matches your use case," David Driggers, CEO of Cirrascale Cloud Services, which offers chips from startups Cerebras, SambaNova Systems, as well as Qualcomm, Nvidia, and AMD, told BI. Here are the industries turning to Nvidia alternatives. High-frequency trading High-frequency stock trading, or HFT, is an area where the speed and accuracy of computation is "mission-critical," Rodrigo Liang, CEO of SambaNova Systems, told BI. Firms like Citadel Securities, Susquehanna, and Jane Street can make millions by getting a fraction of a second ahead of market movements. "The entry point for the new chips is going to come in these higher value use cases first," Liang said. HFT firms hire top machine learning talent, often competing directly with frontier companies like OpenAI and Anthropic. Jane Street has thousands of H100 and H200 chips from Nvidia, according to the firm's website. However, the company also participated in Etched's $120 million Series A in 2024. Etched is betting on transformer models, the kind used for chatbots — models specifically suited to its Sohu chip. The company has also raised funds from PayPal founder Peter Thiel and GitHub CEO Thomas Dohmke, among others. In addition to a need for speed, HFT firms often require at least some of their computations to be completely private. "For a long time, hedge funds with truly proprietary code, that were truly trade secret strategies, were the last holdouts to cloud," Sourcegraph CEO Quinn Slack told BI. On-premises data centers are more likely to have space and energy-related constraints that Nvidia alternatives are looking to seize upon. Targeting and recommendations Some of the earliest returns on the billions of dollars invested in AI were from within tech giants' social media and e-commerce businesses. "AI has already made us better at targeting and finding the audiences that will be interested in their products than many businesses are themselves, and that keeps improving," Mark Zuckerberg said on Meta's April earnings call. Using AI to improve recommendations across the platform has led users of Instagram, Threads, and Facebook to spend more time on the apps. "There are a lot of opportunities also for us to improve our core business by putting more compute against our ads and recommendation work," Zuckerberg said. Wachen told BI recommendations workloads are primed for alternatives to Nvidia, especially as ad-targeting becomes custom-generated ads. Ad targeting and content recommendations are also major use cases for the chips that cloud firms have developed themselves. Google's TPU, a chip originally designed in partnership with Broadcom, for instance, is particularly suited for these tasks. Sovereign AI Sovereign clouds — state-developed data centers built for national security and other purposes, often share some constraints with the financial services sector. Saudi entities have been particularly committed to diversifying their chips. Saudi Aramco, for example, has deals with Cerebras, Groq, SambaNova Systems (as well as AMD and Nvidia). G42, a major Saudi AI data center project, has partnered with Cerebras, AMD, and Nvidia. Humain, the latest entity to emerge from Saudi Arabia's voracious appetite for AI, which was first announced during President Donald Trump's recent visit to the Kingdom, counts Groq, Nvidia, and AMD as partners. Canadian telecom firm Bell Canada just announced Groq as its inference provider. And SambaNova chips are installed in one of SoftBank's data centers in Japan. Up the stack When Meta introduced its Llama 4 model, it also launched a first-of-its-kind API — a direct way for developers to access the model from Meta itself, with computing power coming from Cerebras and Groq. Both companies have their own novel chip architectures; they also offer their own inference service alongside selling chips. The inference market is crowded. But setting up their own data centers to provide it as a service, allows chip startups to bring in revenue faster than the much longer process of selling the chips themselves. Still, there are tradeoffs. Hardware choices present both opportunity and risk for companies, said Driggers. Going with an alternative to Nvidia can save on time and money in some cases, but most alternatives are less flexible than a GPU. That the risk of commitment in these early days of AI is what's keeping many companies from buying non-Nvidia chips, he said. In the meantime, startups are contending with a very finicky inference market. "If our offering is better, customers will stay," said Liang. "If somebody else has a better offering, the market will move."
Yahoo
20-05-2025
- Business
- Yahoo
Vocxi Health Wins 2025 Startup World Cup Silicon Valley Regional Competition
SAN JOSE, Calif., May 20, 2025--(BUSINESS WIRE)--Startup World Cup, one of the biggest and richest startup pitch competitions in the world, successfully hosted its highly anticipated flagship Startup World Cup Silicon Valley Regional competition on May 1, 2025. Out of the Top 15 finalists, Vocxi Health, which is a breakthrough breath-based diagnostic platform that detects diseases like cancer, infections, and injuries in under a minute—anywhere, anytime, became the champion. This achievement paves the way for their participation in the Startup World Cup Grand Finale to be held in San Francisco on October 17, 2025 for an opportunity to win a $1,000,000 investment prize. The event was organized and by Pegasus Tech Ventures, a Silicon Valley-based global venture capital firm. A panel of independent venture capital investors from Kholsa Ventures, Samsung Ventures, First Round, Lightspeed, Engineering Capital, and more judged the pitches of the finalists and ultimately awarded Vocxi Health as the winner. "We are delighted by the quality and enthusiasm of the entrepreneurs who were competing, and the energy was amazing," said Anis Uzzaman, Founder and CEO of Pegasus Tech Ventures, who created the Startup World Cup competition in 2016. "Each year we are impressed by the quality of startups who apply and present. I look forward to seeing Vocxi Health on the Grand Finale stage." With more speakers to come, Mark Papermaster (CTO of AMD), Charly Kevers (CFO of Carta), Camilla Matias (COO of Brex), Ben Kus (CTO of Box), and more are already confirmed to speak at the Grand Finale on October 17th, 2025 in San Francisco. ( Event Details: Startup World Cup 2025 Grand FinaleOctober 17, 2025San Francisco Hilton Union Square Grand Finale Tickets: Check out the Grand Finale video highlights here. About Startup World Cup Startup World Cup is a global conference and competition with the goal of bridging startup ecosystems worldwide. The competition gives startup companies from all over the world a chance to win a US $1,000,000 prize in the form of an investment. This year, there will be 100+ regional events across North America, South America, Europe, Africa, and Asia, leading up to the Grand Finale in San Francisco in September. Startup World Cup is organized by Pegasus Tech Ventures, a Silicon Valley-based global venture capital firm. About Startup World Cup 2025 Grand Finale: The Startup World Cup Grand Finale will take place in San Francisco, October 17, 2025. Past Startup World Cup Grand Finale events featured prominent figures from the high-tech community, including Steve Wozniak (Co-Founder of Apple), Reid Hoffman (Founding CEO of LinkedIn), Vinod Khosla (Co-Founder of Sun Microsystems), Adam Cheyer (Co-Founder of Siri), Marc Randolph (Co-Founder of Netflix), and John Chambers (Former CEO of Cisco). The Grand Finale judging panels have included prominent investors from Kleiner Perkins, Lightspeed, NEA, Intel Capital, DFJ, Social Capital, and Index Ventures. View source version on Contacts Janice MokSenior Marketing ManagerEmail: janice@ Phone: +1 (408) 645-5532
Business Wire
20-05-2025
- Business
- Business Wire
Vocxi Health Wins 2025 Startup World Cup Silicon Valley Regional Competition
SAN JOSE, Calif.--(BUSINESS WIRE)--Startup World Cup, one of the biggest and richest startup pitch competitions in the world, successfully hosted its highly anticipated flagship Startup World Cup Silicon Valley Regional competition on May 1, 2025. Out of the Top 15 finalists, Vocxi Health, which is a breakthrough breath-based diagnostic platform that detects diseases like cancer, infections, and injuries in under a minute—anywhere, anytime, became the champion. This achievement paves the way for their participation in the Startup World Cup Grand Finale to be held in San Francisco on October 17, 2025 for an opportunity to win a $1,000,000 investment prize. The event was organized and by Pegasus Tech Ventures, a Silicon Valley-based global venture capital firm. A panel of independent venture capital investors from Kholsa Ventures, Samsung Ventures, First Round, Lightspeed, Engineering Capital, and more judged the pitches of the finalists and ultimately awarded Vocxi Health as the winner. "We are delighted by the quality and enthusiasm of the entrepreneurs who were competing, and the energy was amazing," said Anis Uzzaman, Founder and CEO of Pegasus Tech Ventures, who created the Startup World Cup competition in 2016. "Each year we are impressed by the quality of startups who apply and present. I look forward to seeing Vocxi Health on the Grand Finale stage." With more speakers to come, Mark Papermaster (CTO of AMD), Charly Kevers (CFO of Carta), Camilla Matias (COO of Brex), Ben Kus (CTO of Box), and more are already confirmed to speak at the Grand Finale on October 17 th, 2025 in San Francisco. ( Event Details: Startup World Cup 2025 Grand Finale October 17, 2025 San Francisco Hilton Union Square Grand Finale Tickets: Check out the Grand Finale video highlights here. About Startup World Cup Startup World Cup is a global conference and competition with the goal of bridging startup ecosystems worldwide. The competition gives startup companies from all over the world a chance to win a US $1,000,000 prize in the form of an investment. This year, there will be 100+ regional events across North America, South America, Europe, Africa, and Asia, leading up to the Grand Finale in San Francisco in September. Startup World Cup is organized by Pegasus Tech Ventures, a Silicon Valley-based global venture capital firm. About Startup World Cup 2025 Grand Finale: The Startup World Cup Grand Finale will take place in San Francisco, October 17, 2025. Past Startup World Cup Grand Finale events featured prominent figures from the high-tech community, including Steve Wozniak (Co-Founder of Apple), Reid Hoffman (Founding CEO of LinkedIn), Vinod Khosla (Co-Founder of Sun Microsystems), Adam Cheyer (Co-Founder of Siri), Marc Randolph (Co-Founder of Netflix), and John Chambers (Former CEO of Cisco). The Grand Finale judging panels have included prominent investors from Kleiner Perkins, Lightspeed, NEA, Intel Capital, DFJ, Social Capital, and Index Ventures.
