20240318 – NVidia GTC 2024 Spring Edition

NVIDIA GTC is one of my favorite events whose 2024 spring version just got underway today.
Jensen Huang had his keynote address today and the theme was Digital Twinning combined with Generative AI to enable industrial automation. The NVIDIA founder and CEO demonstrated in his GTC keynote how developers can use digital twins to develop, test and refine their large-scale, real-time AIs entirely in simulation before rolling them out in industrial infrastructure, saving significant time and cost.

Key takeaways where NVidia’s accelerated computing platform is driving the next wave in AI, digital twins, cloud technologies and sustainable computing.

  • The Blackwell Chip that has AWS, Google, Oracle and Microsoft gearing up for it.
  • The future is Generative, moving from retrieval to ultimately have inference engines to analyze and make sense real time.
  • AI Security: A trusted environment that encrypts data at rest, in transit and while being computed.
  • AI Factory to generate intelligence for the next industrial revolution.
  • Manufacture digitally first: utilize digital twin to build the AI factory using Omniverse to reduce time and build a perfect assembly plant in one take.
  • AI Foundry, NeMo Retriever, Chat with PDF: LLM in a box to aggregate knowledge in a Vector Database and enable it to be available to the enterprise to extract their “goldmines” and convert them to copilots.
  • Physical AI would need 3 computers: Watcher and Context creator, Onmiverse Compute engine and a Robotic Engine to do.

Attention is all you need (aka The Transformer Architecture), and Conversation, Reasoning and Communication is all you want! Welcome to the world of Generative AI.

Unveiled at the 2024 Spring GTC event, NVIDIA‘s Blackwell superchip and LATTE3D are compelling additions to its portfolio and will certainly be the tools for this next industrial revolution we are embarking on – one that is governed by tools running AI in every aspect of our society.

Grant Michel: As we continue to explore the possibilities of AI, it’s exciting to think about the potential when it’s combined with our own reasoning and logical abilities. The result? An unprecedented level of efficiency and productivity. In fact, I have a theory that communication and English logic classes in schools will become increasingly popular as we seek to optimize our creative output. Let’s embrace the power of technology and education to unlock our full potential. Link: https://www.creativebloq.com/news/nvidia-latte3d-text-to-3d-generative-ai

As aptly put by Grant Michel from Würth Additive Group with whom we are partnering on engineering our products and solutions, tomorrow’s world will be governed by:
1. prompt engineering using LLMs to enable conversations
2. simulation, computation and analytics to enable reasoning, and
3. inference to enable communication.

For this reason, we at Numorpho Cybernetic Systems (NUMO) are building our process engineering platform, Mantra M5 to have a mix architecture consisting of GPUs, CPUS and TPUs/NPUs to enable the 3 constructs of converse, compute and infer to seamlessly pull-push information to enable data engineering the future.

As Grant puts it “…. communication and logic classes in schools will become increasingly popular as we seek to optimize our creative output. Let’s embrace the power of technology and education to unlock our full potential.”

At Numorpho Cybernetic Systems (NUMO), we are fully committed to utilizing Nvidia’s Omniverse, Metropolis, it DGX platform, OpenUSD object languate (along with ChatUSD) and its bits, bytes and AI underpinnings to depict our World Model to enable simulation, emulation, interaction and calibration of physical entities using digital twins.

We are part of their Inception program and plan to utilize it for enablement of process engineering in our Mantra M5 platform to enable the activities of make, manage, move, market and maintain. It would include parametric modeling, generative design, smart manufacturing and actionable intelligence utilizing conversation (prompt engineering), computation and inference engines to convert meaning to motion.

NUMO_GenAI_ProcessFlow

The Physical AI system defined by Jensen matches with our Lacanian triad: Symbolic, Imaginary and Real to converse, simulate and enable real world scenarios that defines the core framework of Mantra M5 using #gpus #cpus #npus and #tpus.

NUMO_Lacan_ProcessEngineering

Summarizing the industrial revolution, Jenson mentioned that how it all started was “water comes in” and “electricity comes out”. In the new industrial revolution AI factories are the

NITIN UCHIL – Founder, CEO & Technical Evangelist
nitin.uchil@numorpho.com

REFERENCES:

Accelerating Automotive Workflows With Large Language Models [S62804]

, Director, Artificial Intelligence, Ford Motor Co.

Large language models (LLM) are revolutionizing the way we interact with information, making it easy to pinpoint information from a large source of data, such as vehicle owner’s manuals or manufacturing machinery manuals. However, ensuring these agents operate accurately, or without hallucinating, presents a variety of challenges. To date,the best solutions use LLMs through the retrieval augmented generation (RAG) architecture, with solutions benefiting from fine-tuning LLMs for performance, scalability, and domain knowledge. This session will demonstrate and discuss such LLM solutions for vehicle engineering, connected vehicle analytics, manufacturing, legal, vehicle service and repair, customer support, and employee support.
Driving Enterprise Transformation: CIO Insights on Harnessing Generative AI’s Potential [S62779]

, Vice President, Enterprise AI and Automation, NVIDIA

, VP – Engineering, LinkedIn

, Senior Vice President, Chief Information Officer, NVIDIA

, Chief Information Officer, SentinelOne

, Chief Digital Information Officer, ServiceNow

Generative AI is leading a transformative era for enterprises, with vast potential to enhance employee experiences, improve productivity, strengthen security, and drive operational efficiencies. Our esteemed panel of chief information officers will explore how they harness Generative AI in their organizations. AI’s promises are accompanied by organizational and technical challenges. CIOs grapple with structuring AI and transformation programs, acquiring essential skills, and establishing guardrails for data governance, security, hallucinations, and toxicity in Generative AI deployments. They also consider build-versus-buy options and analyze cost-benefit and total-cost-of-ownership dynamics of Generative AI solutions. Moderated by NVIDIA’s vice president of enterprise AI and automation, this session provides practical insights and best practices from CIOs at the forefront of enterprise transformation through Generative AI. Join us to explore the future of AI in the enterprise.
  • Driving Innovation: Generative AI and Industrial Digitalization in the Automotive Industry [S62380]

    , Co-Founder and CEO, Wayve

    , Vice President, Automotive Enterprise, NVIDIA

    , Founder and CEO, Waabi

    , Chief Data & AI Officer, JLR (Jaguar Land Rover)

    Join senior leadership from renowned automotive companies, including Jaguar Land Rover, Waabi, and Wayve as they discuss their experiences in incorporating Generative AI and industrial digitalization across their organizations. This session, moderated by NVIDIA, provides an exploration into the transformative power of cutting-edge technologies that are reshaping the automotive landscape. Discover how these industry leaders are revolutionizing everything from vehicle design and manufacturing to autonomous driving and customer experiences, and gain valuable insights to navigate the fast-evolving automotive landscape.
    Soundbytes
    Cybernetic human machine world that we all live in Chrissie JLR, AI automation and improve our data, deep level of personalization (working with Accenture). Going beyond modern luxury.
    Raquel – scale, deploy, capital efficient. Safety critical system interpretability, simulation, Trucking (Waabi), unit economics. Robo taxis use case is iffy. Driver shortage for long haul trucking. Combine imitation with reinforced learning. Simulation is key.
    Norm – unsupervised, self-supervised learning, synthetic learning – inference and safety, explainability

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