Doron Aronson

@SteveKerr @LewisHamilton tell @Simone_Biles "Never quit!" in discussing playing the waiting game as an athlete during #COVID19 #HPEDiscover

@amazon @awscloud #Pennsylvania

The tiny chips behind Amazon’s big AI investment semafor.com/article/03/14/… @ReedAlbergotti @semafor @amazon @awscloud #Amazon #NVIDIA

Amazing to hear @awscloud CEO Matt Garman on Decoder! His journey from AWS's first PM to CEO is truly inspiring. Love how we're staying focused on customer value while pushing tech boundaries. bit.ly/4hrEZcM @reckless

@reckless @awscloud @amazon #Amazon

Apple says it uses Amazon's custom AI chips - ⁦@CNBC⁩ ⁦@jordannovet⁩ ⁦@Apple⁩ ⁦@awscloud⁩ @Amazon #AI stocks.apple.com/AOc7aYTzeTUuzK…

Amazon steps up effort to build AI chips that can rival Nvidia ft.com/content/3d9b5c… via @ft @PatrickMoorhead @MActon93 @danielnewmanUV @awscloud @amazon #GenAI #AWS

Amazon's Secret Weapon in Chip Design is Amazon spectrum.ieee.org/amazon-ai @amazon @awscloud #AI #GenAI

AWS CEO ‘Bullish’ On Homemade Chip Future: ‘We Can Optimize Like Crazy’ crn.com/news/cloud/202… @awscloud #chips @NVIDIAAI

Big news – customers can now access Oracle Autonomous Database and Oracle Exadata Database Service in AWS, simplifying the deployment of enterprise workloads to the cloud while improving agility, flexibility, and security. #AWS #Oracle

AWS unveils Mithra to identify and mitigate malicious domains across its massive system techcrunch.com/2024/08/05/aws… via @techcrunch #SecurityInsights #Malware @awscloud @amazon @ron_miller #AWSGlobalCommunity

@awscloud @amazon #GenAI #chips

#LetsGoOilers📷

"Amazon started its (chipmaking) effort in 2015, acquiring startup Annapurna Labs", in "What’s next in chips" @odonnell_jm technologyreview.com/2024/05/13/109… @techreview #AI @awscloud @amazon

"When our customers are going somewhere new in a big way, we want to make sure we're supporting them. By dropping the cost of training these new (GenAI) models...we are making it possible for those customers (of all sizes)" Amazon SVP James Hamilton @TWSemicon @awscloud @amazon

@danielnewmanUV @KristinaParts @AWS @PatrickMoorhead It's a goodie for sure!

@DoronAronson @KristinaParts @AWS @PatrickMoorhead Whoa. You dug that up fast.

Big tech focuses on in-house chips in an attempt to reduce the reliance on Nvidia . I head to AWS in Texas to see how the competition stacks up: cnb.cx/3x5oEIH $NVDA $AMZN

@danielnewmanUV @KristinaParts Absolutely, it was great to see the @aws chips team in action in Austin today. I also enjoyed yours and @PatrickMoorhead's piece moorinsightsstrategy.com/the-six-five/a…. #AI

@KristinaParts We did that tour. Very interesting and scrappy team there in Texas. The trend to reduce reliance on NVidia isn’t unique to AWS. It is industry wide. Not because NVidia is bad, but rather because it is so good. The reliance is way too risky.

AWS Goes Deep on AI, Chip Power... and Cost Savings: thenewstack.io/aws-goes-deep-… via @thenewstack @awscloud

@awscloud @amazon #ArtificialIntelligence

@Pavan81 @ajassy Annapurna Labs is named after the Annapurna Massif mountain range in the Himalayas.

@ajassy Who came up with name Annapurna Labs? Does it signify anything?

Several years ago, when we started pursuing building our own chips, a lot of folks thought this was nuts. We heard a lot of the same refrains you often hear—why make this investment, why invest in a team and all the other fixed costs to develop your own chip when you can buy from other suppliers? And, while we knew we’d partner with those other companies for the foreseeable future, if your customers are telling you they’re thirsty for better price-performance, and you’re driven by what makes customers’ lives better and easier every day, you explore options to make it so. We realized pretty quickly that designing our own chips was going to be the best path to delivering this value for customers. We were lucky to find and join forces with the amazing Annapurna Labs team, who started with a chip (named Nitro) that offloaded security, networking, and some other virtualization functions from our servers so customers could use more of the server than they could before. Then, that team built a generalized CPU chip, Graviton, which has been very popular and impactful for customers, before embarking on building custom AI chips—Trainium (for training) and Inferentia (for inference)—which are also off to a strong start. Am very excited about our most recent chip releases at AWS re: Invent: Graviton4 and Trainium2. Graviton4 marks the fourth generation we’ve delivered in just five years (you can see the evolution from left to right in the image below), and it’s the most powerful and energy efficient multipurpose chip we have built to date. And with the surge of interest in generative AI, Trainium2 will help customers train their ML models faster, at a more advantaged price-performance. I’m really proud of the pace of innovation our teams are delivering on and what it is making possible for customers! aboutamazon.com/news/aws-reinv…