Farzin Aghdasi, PhD MBA

Keeping your data close to the GPUs is essential, so we offer VAST Data as part of our #GPUasaService AI Platform. Let us help you #StepontheGaaS and move your #AI strategy forward. #Fast #Secure #Private Dominic Ken Michael Bill Traci

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1) making decisions based on #FirstPrinciples, 2) How Jensen Huang realized that #GPU holds the key to #AI and #AcceleratedComputing - schematic for #software, 3)question your own beliefs and assumptions

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Analog Behavioral Modeling involves creating models that mimic a desired external circuit behavior at a block level rather than simply reproducing individual transistor characteristics. One of the significant benefits of using models is that they reduce the simulation time. Read this blog to learn more about Verilog-A, the most used language by analog designers to describe analog circuit behavior, representing a high-level abstraction of a semiconductor device. https://ow.ly/yUNr50S5C2f

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AI workflows are driving demand for memory and storage to prepare data, train the model and create useful inference engines.  This is driving announcements of storage and memory products that support the various elements of these AI workflows.

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Here's a great GTC session that discusses advanced strategies for high-performance GPU programming with NVIDIA #CUDA. Stephen Jones explores parallel program design, #GPU optimization, and more to enhance application performance. 📺 NVIDIA On-Demand: https://nvda.ws/3TnmyfK

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As I delved into image processing using deep neural networks, I pondered the mechanism by which neural networks address the 2D spatial correlations inherent in images. Initially, the early layers of these networks appeared to map pixel intensities to individual neurons in the input layers, seemingly neglecting the 2D spatial relationships. This approach raised concerns about the effectiveness of traditional neural networks in capturing spatial dependencies. However, my understanding and concerns were alleviated upon discovering Convolutional Neural Networks (CNNs), which are specifically designed to account for and exploit these spatial correlations in images.

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📍 Reporting from Denver, Colorado, Graham Morehead discusses Intel's groundbreaking OCI Optical Compute Interconnect. 💡 Why it matters: Speed of Photons: Photons travel significantly faster than electrons, allowing for rapid data transfer. Silicon Photonics: Intel's innovation integrates photons directly into silicon, seamlessly connecting with current AI technologies. Massive Data Access: AI processes require immense data access, often leveraging distributed compute units. 📊 The ability to gather and process data efficiently is crucial, and photons are the fastest way to achieve this. 🔍 Discover why this advancement is pivotal for AI's future! 🚀 #AI #Intel #SiliconPhotonics #OpticalComputeInterconnect #FutureTech #GrahamMorehead #Pangeon #ThePangeon #GPT #AGI #OpenAI

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A significant advance that will help ease 3D design workflows https://lnkd.in/gk2bEr5W 3D mesh creation is a part of artistic work, architecture, mechanical engineering, and a lot more. A significant time goes into modeling. this new tool from NVIDIA will help reduce some of that

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One of the ways our engineers stay up to date on trends impacting the RF ecosystem is by experimenting with open-source RF modeling and analysis tools. Here, the team uses the Phyton Scipy.signal Toolbox to explore the theory behind poles and zeros and shares their findings. White Paper | RF Tools to Understand How Poles and Zeros Relate to Q Factor https://bit.ly/3xQQSrB

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Really interesting to see this: how Europe is moving up. It is interest to contrast this qualitative survey with the #siliconcatalyst analysys that UK is sixth in Europe in funding value fir silicon investment. And I will put in a plug for our #UKTIN Forward Capabilities paper on recommendations for UK Semiconductor sector: https://lnkd.in/eNNAsCAz

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A study in perspectives on AV safety: a Waymo robotaxi approaches an intersection in San Francisco. Some other driver is doing "really fast donuts" in the intersection, and has been doing so long enough that the robotaxi rider looks up because of the smell of burning rubber entering the cabin. Robotaxi enters the intersection, then stops. The other driver halts and narrowly misses hitting the robotaxi (by perhaps a foot). The rider: "I can trust the Waymo, but I can't trust this driver". States that the other driver was upset but the robotaxi rider "shrugged, and pointed to the invisible driver." What ya' gonna do? It's a Waymo. "Still going to use Waymo." Presumed Waymo response to regulators and media: The human driver doing donuts was irresponsible. If there had been a crash it would have been the other driver's fault. (If I got this wrong would be happy to be corrected by Waymo. They have not commented as far as I know.) A broader safety engineering response: This is not the first time a robotaxi has encountered another car doing donuts in an intersection. In fact, a Cruise robotaxi was hit in a similar situation in March 2023 (SGO 30412-4960). From the description it seems there was plenty of warning this was happening. Why did the robotaxi not stop well clear of the intersection as a prudent human driver would have? Is Waymo monitoring SGO data and learning from what has been reported by other companies? Has Waymo included "other car doing donuts" in its hazard log? Did Waymo decide to ignore mitigation of this hazard for some reason? Will that change now that this has happened to Waymo instead of just Cruise? I'm glad in this case there was no injury, but there certainly could have been but for chance from a rare circumstance that is already known to have caused a crash. Being saved by the “grace of the Gods” is not a safety argument. I hope these questions are being asked and resolved by Waymo. But we won't know until the next donut incident. Primary Source: https://lnkd.in/eFHEMVFX Article: https://lnkd.in/eFVpfjec

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https://lnkd.in/grt_6pVK Jim Keller on fire. 🔥 U.S. chip designer aims to bring down AI prices pushed up by Nvidia. #nvidia #artificialintelligence #llms #chatgpt #generativeai #gpu #servers #datacenter #cloud #ai #technology #innovation #business #Semiconductorindustry #electronics #semiconductor #supplychain credit: Nikkei Asia

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Got a chance to discuss TCG Key Per I/O capabilities and its possible use cases with confidential compute at the Confidential Compute Consoritium's TAC call yesterday. Please see the link below. The topic is covered from around 20 mins into the video and runs till about the 1-hour mark. https://lnkd.in/gvupy8iP

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As #AI scales across industries and use cases, understanding how to measure AI performance becomes key in developing solutions with sufficient head room. Like we say, "not all TOPs are created equal". At Qualcomm, we focus on running AI inferencing workloads on our super-efficient and powerful Neural Processing Units (NPUs). Highly recommend reading our latest article on how to measure AI workloads, performance and the right place to run them.  https://lnkd.in/gzV33PCa

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I'll see you there! #AI Driving Fabs of the Future...People, Technology, Infrastructure "There has never been a more exciting time in the history of #semiconductor manufacturing. Following the supply chain disruption of the early 2020s, teams rushing to expand operations and add capacity are looking to maximize operating leverage amidst a challenging market backdrop. With dozens of new fully automated 300mm fabs set to open their doors in the next two years, here are the burning questions: -- What does it mean for the existing 200mm legacy fabs?  -- What challenges will we face in 2024? -- How can we solve them together?" SEMI Semiconductor Digest Cadence Design Systems Analog Devices Design News Lin Tso, CMM Samer Bahou https://lnkd.in/gHhJKrEE

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