Rodrigo Liang

Cerebras Systems, under the leadership of CEO Andrew Feldman, made a significant leap in AI performance with its breakthrough in fast inference. By achieving lightning-speed processing of the world’s largest AI models, the company unlocked new possibilities for real-time, complex applications like multi-agent collaboration and advanced reasoning. This rapid inference technology is set to transform industries, enabling real-time responses and dramatically enhancing the capabilities of emerging AI systems. Feldman emphasized that this progress opens doors to use cases, driving the future of AI beyond simple query-based tasks. Read more here: https://lnkd.in/g__sm6Be

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Unlock the full potential of your AI and ML projects with Simbeor SDK! Simbeor SDK is the industry-first signal integrity analysis automation kit https://lnkd.in/g-uZ4yDg Here are just some reasons to use Simbeor SDK for AI and ML: + Unique, fast, and accurate decompositional electromagnetic analysis of interconnects with multiple solvers + Universal API for C/C++, MATLAB, and Python + Tested in multiple ML projects + Easy to use with multiple example kits to start with + Scalable and cost-effective Ready to elevate your AI and ML projects? Learn more about Simbeor SDK today! https://lnkd.in/gRe3jwta  #simbeor #electromagnetics #signal_integrity #AI

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🌟 Exploring the Intersection of Business and Technology re AI! 🌟 Before my decade-long focus on AI, connecting technology and business in various domains has always been my passion; This is why I enjoyed this conversation with David Luan - No BS, No Twitter exaggerations, No clickbate - Just a super well informed, super smart David sharing his insights from years of hands-on experience: #Startegy, #Software, #Hardware, #Platforms, #ModelSpace and everything in between - LMK what you think of his projections. In This Episode: 1. The Biggest Lessons from OpenAI and Google Brain: What did OpenAI realize that no one else did that allowed them to steal the show with ChatGPT? Why did it take 6 years after the introduction of transformers for ChatGPT to be released? What are 1-2 of David’s biggest lessons from his time leading teams at OpenAI and Google Brain? 2. Foundation Models: The Hard Truths: Why does David strongly disagree that the performance of foundation models is at a stage of diminishing returns? Why does David believe there will only be 5-7 foundation model providers? What will separate those who win vs those who do not? Does David believe we are seeing the commoditization of foundation models? How and when will we solve core problems of both reasoning and memory for foundation models? 3. Bunding vs Unbundling: Why Chips Are Coming for Models: Why does David believe that Jensen and Nvidia have to move into the model layer to sustain their competitive advantage? Why does David believe that the largest model providers have to make their own chips to make their business model sustainable? What does David believe is the future of the chip and infrastructure layer? 4. The Application Layer: Why Everyone Will Have an Agent: What is the difference between traditional RPA vs agents? Why are agents a 1,000x larger business than RPA? In a world where everyone has an agent, what does the future of work look like? Why does David disagree with the notion of “selling the work” and not the tool? What is the business model for the next generation of application-layer AI companies? https://lnkd.in/dUpWWzvN

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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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Check out this technical conversation between Dr. Waku and Groq Compiler Engineer Gautam Rayaprolu. They cover how inference works on GPUs v LPUs, issues of reliability in large clusters, the Groq approach to building data centers, & more. https://hubs.la/Q02RqZR10

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☯️ Tensor networks and quantum computing just go together -- the duo takes on simulations of Hamiltonian dynamics. Plus, PsiQuantum is officially headed to Chicago's quantum kingdom. ⚆ PsiQuantum collaborates with Illinois to build the first US-based utility-scale 1 million qubit fault-tolerant quantum computer at the forthcoming Chicago quantum campus, supported by a $500M state budget ⚆ Atom Computing introduces a method to maintain 99% occupancy in a 1225-site neutral-atom array; advances large-scale neutral-atom quantum computers one more bit ⚆ Nullspace, Inc. releases Nullspace ES -- a specialized software for designing and analyzing large-scale ion traps; accelerates simulations and reduces prototyping costs ⚆ QuTech's development of somersaulting spin qubits simplifies control in large semiconductor qubit arrays; uses baseband signals and small magnetic fields for efficient qubit management ⚆ IBM announces an exclusive Quantum Developer Conference in November; will include hands-on experiences with the latest quantum tools and opportunities for networking with industry experts ⚆ Despite growing quantum courses, disparities in resources and access persist, necessitating targeted investments in smaller, rural, and minority-serving institutions to encourage equitable quantum education ⚆ IBM Quantum researchers propose a hybrid method combining quantum computing and tensor networks to accurately simulate larger systems and longer times in out-of-equilibrium phenomena with manageable computational costs ⚆ Don't miss a single qubit -- follow me & subscribe to the free newsletter for your daily quantum computing news & research insights. #quantumcomputing #quantumtechnology #innovation #quantumscience #quantumphysics

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It's finally here 🎉 We’re excited to kick off our series of technical analyses, in which we're exploring the performance implications of NVIDIA's H200 GPU for the use case of LLM, VLM, and DiT inference and training. In the first installment, we measure the multi-node inference overhead and explore the benefits of FP8 quantization. 🛠️ Hardware: NVIDIA H200 The H200 shows great promise, particularly for extremely large Transformers models, as it allows to handle BFLOAT16 without multi-node inference, removing any inter-node communication overhead. 🐋 Model: DeepSeek V3 We chose DeepSeek V3 as our case study model due to its SOTA model capabilities and high demanding GPU resources for model serving in production and research environments. 🚀 Serving framework: SGLang Although we plan to benchmark other inference systems such as vLLM and TensorRT-LLM, we landed on SGLang due to its performance-oriented design and easy-to-modify Python code base. This first blog in the series is a part of our ongoing co-research with SGLang, for which we provided GPU infrastructure and engineering hours. Read it in full and see the results: https://lnkd.in/ePt_b3gm

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Dive into the latest advancements in AI with cross-modal integration, where cutting-edge architectures like encoder-decoder models, GANs, and transformers enable seamless data processing across text, images, audio, and more. Discover how these technologies are unlocking new possibilities across many industries. Learn more about how these advanced systems are shaping the future of AI: https://lnkd.in/ddwVigyS

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Ahead of COMPUTEX 2024... NVIDIA founder and CEO Jensen Huang delivered a keynote address tonight with a focus on what's next for the AI ecosystem and what to expect from the NVIDIA pipeline. His two-hour long speech, including demo, was presented in front of a packed audience at the National Taiwan University auditorium. Jensen's address was live-streamed on YouTube and broadcast on TVBS HD, the leading local cable TV channel. The event upstages tomorrow's COMPUTEX opening keynote by Lisa Su, the CEO of AMD, and speeches by Pat Gelsinger, Intel CEO, Cristiano Amon, CEO of Qualcomm, among other tech luminaries. #nvidia #ai #products #demos #hardware #software

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Mivium's Game-Changing Gallium Nitride Tech Seeks to Outperform Silicon, Reducing Toxicity and Enhancing Efficiency for Data Centers and AI Applications http://s4g.biz/14nov24 tl;dr: Eric Tsai’s Mivium focuses on gallium nitride (GaN) to replace silicon, improving efficiency and sustainability. GaN's fast-switching properties make devices smaller, more powerful, and less energy-intensive. Mivium’s unique, clean GaN production process avoids the toxic materials typical in semiconductors. Nevada’s tech-friendly policies support Mivium’s plans to establish a new “gallium valley” in Reno. By crowdfunding, Eric brings everyday investors into Mivium’s journey, making early-stage investing accessible. https://lnkd.in/e2nunP4g #ImpactCrowdfunding #DiverseFounders #SocialEntrepreneurs #CommunityCapital #ImpactInvestors #RIC #InvestmentCrowdfunding #SuperCrowd #gallium

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🚀 Join IoT expert Umesh Lokhande for our latest Engineering Hour! Learn how Arm Cortex-M microcontrollers' nested vector interrupt controller (NVIC) simplifies hardware interrupt implementation. 📈 Umesh will explore the interrupt lifecycle, priority levels, and reentrancy interrupts, plus demonstrate managing two external interrupts on an STM32 MCU. Don't miss out on this deep dive into advanced design techniques! 📅 Date: Sunday, August 4th  🕒 Time: 15:00 GMT 👉 Join here: https://lnkd.in/gfGjh_U4 #IoT #Engineering #ArmCortexM #STM32 #EmbeddedSystems #TechTalk #Interrupts #NVIC #Microcontrollers #TechEducation

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🎥 Missed our webinar with HEAVY.AI and Vultr? ➡️ https://nvda.ws/3OJsFrP Watch it on-demand today and gain insights on how these two companies are utilizing the #NVIDIAGraceHopper Superchip, from accelerating enterprise #AI workloads for their customers to unlocking energy savings in the #datacenter.

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Blackwell 26,596 times more powerful than our 8 Intel MOSIPS? At Computex 2024, Jensen Huang unveiled the roadmap for Blackwell, promising a future of accelerated computing architectures that redefine our expectations. These advancements are set to elevate AI capabilities to unprecedented levels. Our A7Technology MOSIPS system, powered by 8 Intel NUC computers, delivers 752 GFLOPS, with each system offering 94 GFLOPS. This impressive setup, however, pales in comparison to the capabilities of the new Blackwell B200 GPU. The B200 not only doubles the transistor count of the current H100 but also delivers an astounding 20 petaflops of AI performance from a single GPU, compared to the H100's 4 petaflops. The B200's 192GB of HBM3e memory and 8 TB/s bandwidth are equally impressive, showcasing how scaling is driving AI capabilities to new heights. This leap in performance is a significant phase shift, surpassing the limits of Moore's law and pushing the boundaries of what we thought possible with CPU architectures. To put this in perspective, a single Blackwell B200 GPU's 20 petaflops make it approximately 26,596 times more powerful than our current system's 752 GFLOPS, which uses eight of the latest Intel CPUs. These breakthroughs in parallel architectures are not just incremental improvements; they represent a monumental leap in AI capability and power, setting the stage for the next era of technological advancement.

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Insightful conversation on Scaling Performance in AI Systems with Ed Sperling of Semiconductor Engineering and Andy Nightingale of Arteris. Check it out here: https://hubs.ly/Q02Y_6KN0 #semiconductor #innovation #SystemOnChip #NetworkOnChip #Arteris

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Join us on Thursday, Oct 17, for our webinar on "Supercharging AI Platforms with Anyscale" 🚀 ⚡ Discover how Anyscale can optimize AI platforms with key capabilities including: 🔵Advanced Instance Management: Launch clusters in <60s, Scale to 1000s of nodes, and rely on Anyscale's intelligent instance selection that searches across on-demand and spot instances to reduce costs. 🔵Global Compute Management: Efficiently manage resources across cloud, on-prem, and Kubernetes. 🔵Preventing AI Sprawl: Anyscale's Governance Suite provides fine grained control to set quotas, monitor usage, and the observability teams need to optimize AI workloads. Don’t miss it—sign up today: https://lnkd.in/gFpWMB3C

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Join industry leaders at #PTC25 for a dynamic discussion on "𝙎𝙘𝙖𝙡𝙞𝙣𝙜 𝙂𝙋𝙐 𝙄𝙣𝙛𝙧𝙖𝙨𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚 – 𝙃𝙤𝙬 𝙩𝙤 𝙎𝙥𝙚𝙚𝙙 𝙐𝙥 𝙒𝙞𝙩𝙝𝙤𝙪𝙩 𝙇𝙤𝙨𝙞𝙣𝙜 𝙊𝙪𝙧 𝘾𝙤𝙤𝙡?" As AI demand and high-performance computing accelerate, the challenges of scaling GPU infrastructure are top of mind. This expert panel will dive into strategies to boost performance, keep systems cool, and address supply chain disruptions. 🌍💡 Don't miss out on insights from key leaders in the field: Bjorn Brynjulfsson , CEO of Borealis Data Center Jaime Leverton, CEO of Jaime Leverton Ventures & Advisory Gil Santaliz, CEO of NJFX Chris Sharp, CTO of Digital Realty Michael Elias, Senior Equity Research Analyst at TD Cowen Don't Miss Out! 📅 January 20, 2025 🕑2:00 PM – 2:45 PM 📍MPCC, South Pacific 2 _______________ #AI #GPU #DigitalInfrastructure #PTC25 #APAC #IT #DigitalInfrastructure #CriticalInfrastructure #DataCenters #Subsea #Cooling #DC #AC #LiquidCooled #Inference #EdgeAI #

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YES! Thanks, Dean Takahashi, VentureBeat, for covering NVIDIA's Inference Microservices (NIMs), including those powered by partners such as Domino Data Lab. Excited to innovate jointly with NVIDIA on an #AI form factor that makes it even easier to deploy, manage, and scale models built in #DominoDataLab on #NVIDIA's infrastructure Here's the article: https://gag.gl/fxt56p #GenerativeAI #GenAI #ResponsibleAI #datascience #MachineLearning #ml #mlops #Innovation #EnterpriseAI #AIatscale

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▶️ NVIDIA’s Ian Finder and Supermicro’s Patrick Chiu joined WEKA Chief Product Officer Nilesh Patel on SiliconANGLE & theCUBE at #SC24 to unpack the our industry-first joint solution for the NVIDIA Grace CPU Superchip and discuss the opportunities it presents. Check out the full interview and write-up of the conversation: https://weka.ly/3ZkhNXM

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