Latest news with #Graviton4
Yahoo
9 hours ago
- Business
- Yahoo
Amazon's Powerful AWS Custom Chip To Get An Upgrade - Why Is It Important?
Inc (NASDAQ:AMZN) Amazon Web Services could soon announce an update to its Graviton4 chip, sparking a rivalry with Intel Corp (NASDAQ:INTC) and Advanced Micro Devices (NASDAQ:AMD). The chip could include 600 gigabits per second of network bandwidth, CNBC reported on Wednesday. Benzinga has reached out to Amazon for its comment. Hyperscalars like Amazon, Microsoft Corp (NASDAQ:MSFT), Alphabet Inc (NASDAQ:GOOGL), and Meta Platforms (NASDAQ:META) migrated towards custom chips to curtail costs, tackle compatibility issues, and address supply crises. Trending: Maker of the $60,000 foldable home has 3 factory buildings, 600+ houses built, and big plans to solve housing — According to Amazon, its latest cloud computing chip, Graviton4, offers significant advancements in performance and energy efficiency. It's the fourth generation of AWS's custom-engineered data center chips, first introduced in 2018. Graviton4, based on Arm-architecture, boasts four times the performance of Graviton1 and is even more energy-efficient than its predecessor, Graviton3. With 73 billion transistors, it's being adopted by major customers like SAP and Epic Games for high-performance and reliable cloud experiences. This innovation, alongside other custom AWS chips like Trainium and Inferentia for AI, underscores Amazon's leadership in cloud computing technology. Amazon manufactures Graviton4 central processing unit at its Annapurna Labs in Austin, Texas. Rami Sinno, director of engineering at Amazon Web Services (AWS) Annapurna Labs, cited strong demand for chips that outpaced the supply. AWS Senior Director Gadi Hutt told CNBC about Amazon's initiatives to provide an alternative to Nvidia Corp's (NASDAQ:NVDA) costly graphics processing units. Hutt told CNBC. that Anthropic's Claude Opus 4 AI model launched on Trainium2 GPUs and Project Rainier. Trainium3 is coming up in 2025, he has committed $8 billion to Anthropic. Also, Amazon chief Andy Jassy recently highlighted the company's extensive leveraging of Generative AI to drive value. Jassy highlighted Generative AI's crucial role within AWS for developers and optimizing internal functions such as fulfillment and customer service. He also pointed to developing AI agents to automate tasks and accelerate innovation. As Amazon commits huge spending and Capex to AI, it is imperative that it design its own chips based on custom needs rather than relying on NVIDIA. Jassy stated that this AI-driven transformation might reduce the corporate workforce in the coming years. Read Next: Invest early in CancerVax's breakthrough tech aiming to disrupt a $231B market. Back a bold new approach to cancer treatment with high-growth potential. If there was a new fund backed by Jeff Bezos offering a 7-9% target yield with monthly dividends would you invest in it? Photo by Deep Pixel via Shutterstock Up Next: Transform your trading with Benzinga Edge's one-of-a-kind market trade ideas and tools. Click now to access unique insights that can set you ahead in today's competitive market. Get the latest stock analysis from Benzinga? This article Amazon's Powerful AWS Custom Chip To Get An Upgrade - Why Is It Important? originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved.
Yahoo
2 days ago
- Business
- Yahoo
Amazons AWS fires back at Nvidia with Graviton4 and Trainium3
Amazon's AWS is sharpening its AI edge with custom chipsan upgraded Graviton4 CPU and a forthcoming Trainium3 GPUthat could start chipping away at Nvidia's (NASDAQ:NVDA) market stronghold in AI training and inference. CNBC reports AWS will soon launch a Graviton4 update boasting 600 Gbps of network bandwidth, courtesy of its Annapurna Labs design, with availability expected by month's end. Later this year, AWS plans to roll out Trainium3, promising 50% better energy efficiency versus Trainium2, which underpins Anthropic's Claude Opus 4 model. While Nvidia's Blackwell GPU retains a rawperformance lead, Trainium2 already offers superior cost-performance ratios, according to AWS Senior Director Gadi Hutt. Developers eyeing Trainium will need to retool workloads away from Nvidia's CUDA ecosystem and validate modelaccuracy parity on AWS's frameworks. Nvidia has dominated AI compute thanks to unmatched throughput and the ubiquity of CUDA in developer toolchains. By delivering strong price-performance and energy gains via Graviton4 and Trainium3, AWS aims to lure hyperscalers and cost-sensitive enterprises that run massive inference fleets or large-scale training jobs. If AWS can minimize migration friction and prove equivalent accuracy, it could open the door for a meaningful shift in AI infrastructure spend. The real test will come when Graviton4 benchmarks are published and Trainium3 previews hit developer hands. Watch for cloudnative AI workloads running on non-CUDA stacks and for enterprise case studies highlighting total cost-of-ownership savings. Those signals will reveal whether AWS can genuinely erode Nvidia's GPU hegemony. This article first appeared on GuruFocus. Error in retrieving data Sign in to access your portfolio Error in retrieving data
CNBC
4 days ago
- Business
- CNBC
AWS' custom chip strategy is showing results, and cutting into Nvidia's AI dominance
Amazon Web Services is set to announce an update to its Graviton4 chip that includes 600 gigabytes per second of network bandwidth, what the company calls the highest offering in the public cloud. Ali Saidi, a distinguished engineer at AWS, likened the speed to a machine reading 100 music CDs a second. Graviton4, a central processing unit, or CPU, is one of many chip products that come from Amazon's Annapurna Labs in Austin, Texas. The chip is a win for the company's custom strategy and putting it up against traditional semiconductor players like Intel and AMD. But the real battle is with Nvidia in the artificial intelligence infrastructure space. At AWS's re:Invent 2024 conference last December, the company announced Project Rainier – an AI supercomputer built for startup Anthropic. AWS has put $8 billion into backing Anthropic. AWS Senior Director for Customer and Project Engineering Gadi Hutt said Amazon is looking to reduce AI training costs and provide an alternative to Nvidia's expensive graphics processing units, or GPUs. Anthropic's Claude Opus 4 AI model is trained on Trainium2 GPUs, according to AWS, and Project Rainier is powered by over half a million of the chips – an order that would have traditionally gone to Nvidia. Hutt said that while Nvidia's Blackwell is a higher-performing chip than Trainium2, the AWS chip offers better cost performance. "Trainium3 is coming up this year, and it's doubling the performance of Trainium2, and it's going to save energy by an additional 50%," he said. The demand for these chips is already outpacing supply, according to Rami Sinno, director of engineering at AWS' Annapurna Labs. "Our supply is very, very large, but every single service that we build has a customer attached to it," he said. With Graviton4's upgrade on the horizon and Project Rainier's Trainium chips, Amazon is demonstrating its broader ambition to control the entire AI infrastructure stack, from networking to training to inference. And as more major AI models like Claude 4 prove they can train successfully on non-Nvidia hardware, the question isn't whether AWS can compete with the chip giant — it's how much market share it can take. The release schedule for the Graviton4 update will be provided by the end of June, according to an AWS spokesperson.
