Chips, data centers, and power enable AI, but customers buy the value it delivers. @Salesforce Chair & CEO @Benioff on bringing hundreds of thousands of Salesforce customers and a million Slack customers from point A to point B without leaving their past investments behind, with @danielnewmanUV and @PatrickMoorhead. $CRM

Chips/Memory CEO age: $AMD - Lisa Su - 56 yrs old $SKHY - Kwak Noh-jung - 60 yrs old $NVDA - Jensen Huang - 63 yrs old $INTC - Lip-Bu Tan - 66 yrs old $MU - Sanjay Mehrotra - 68 yrs old $TSM - Che-Chia Wei - 73 yrs old $AVGO - Hock Tan - 75 yrs old Didn't realize Lisa is that much younger than the crowd. AMD has a bright future ahead...

Chips, AI, Startups and More 🚀📡🥂 During @VentureAtlanta , Falcomm is opening its doors to the people building what comes next: chip designers, AI engineers, founders, investors and anyone curious about the hardware that powers modern communications. This year, the new #DeepTechTrack# brings space tech, defense tech, frontier tech, robotics, and quantum computing into the conference lineup, and there will be plenty to talk about once the sessions wrap. Expect good food, good drinks and the kind of conversations that start with "so what are you working on?" and end with a follow-up on the calendar. 📅 Wednesday, October 14 ⏲️ 6:00 to 9:00 PM 📍 Location shared upon registration approval 🔗 Reserve your spot: Space is limited. Know someone who should be in the room? Tag them below and have them register too. #Semiconductors# #DeepTech# #AI# #Startups# #DefenseTech# #AtlantaTech# #VentureAtlanta#

Chips bounced. Intel stood out. Now the market turns back to the bigger question: how long can AI momentum hold against higher rates and rising power costs? 👀 Read more:

Chips, memory, interconnects, storage, robotics. Compute hardware infrastructure is undergoing the largest transformation in 30 years. Whatever innovation challenges lie ahead, computer science will be central to the solution. And we've raised $1.1B to help that along.

Chips are the foundation of every AI experience. That's why understanding the hardware behind the software has never mattered more. When you ask a chatbot a question or generate an image, there's a physical chip somewhere doing the heavy lifting. For most of computing history, that was a CPU—the "brain" of a computer—great for general tasks needed to run software and operating systems. AI is more complex: for workloads called training and inference, AI needs to perform trillions of calculations in parallel. That's where AI accelerators come in. Purpose-built accelerators can deliver significantly better performance and efficiency than general-purpose chips. @awscloud Trainium chips are an example—purpose-built for AI training and inference. New chips for a new era. ⬇️