Nvidia pushes AI adoption among enterprises

Nvidia launched a series of GPUs and AI projects to push the AI and robotic evolution, providing the enterprises new opportunities to access the technology in cost efficient way.

Chipmaker giant Nvidia recently announced Project GR00T, or Generalist Robot 00 Technology, as a versatile model for humanoid robots to advance robotics and AI development.

It also introduced Jetson Thor during the GPU Technology Conference. Based on the NVIDIA Thor system-on-a-chip (SoC), the new computing platform is designed to handle complex tasks and interact safely and naturally with both people and machines.

Nvidia has taken giant strides in terms of expanding its AI-enabled product portfolio as it previously also launched a cloud service called NVIDIA Quantum Cloud. The US-based chipmaker is collaborating with several players in the industry to help enterprises deploy new AI applications quickly and cost-effectively. 

Jensen Huang, founder and CEO of Nvidia at the GTC, commented on how building foundation models for general humanoid robots is one of the most exciting problems to solve in AI today. He also added that enabling technologies are coming together to lead robotics worldwide to take giant leaps towards artificial general robotics. 

Nvidia’s recently launched generative AI microservices are being used or are to be used by several companies for various innovative applications across different industries. Leading application, data, and cybersecurity platform providers such as Adobe, Cadence, CrowdStrike, Getty Images, SAP, ServiceNow, and Shutterstock are among the first to utilize the new NVIDIA generative AI microservices offered in NVIDIA AI Enterprise 5.0.

In a press release, Huang emphasized the potential of transforming the vast data reservoirs held by established enterprise platforms into generative AI copilots. “Created with our partner ecosystem, these containerized AI microservices are the building blocks for enterprises in every industry to become AI companies,” he added.

What is GR00T 

According to Nvidia, GR00T is a general-purpose foundation model trained in NVIDIA GPU-accelerated simulation. The simulation helps robots learn from a small number of human demonstrations through imitation learning and from the NVIDIA Isaac Lab robotics platform through reinforcement learning.

According to Jensen Huang, this initiative tackles one of the most thrilling AI challenges, developing models for general humanoid robots. Robots equipped with GR00T will understand human language and imitate actions, allowing them to learn and interact with the world efficiently. Huang demonstrated these robots during his presentation at GTC.

Arrival of Blackwell

Nvidia also launched a new generation of AI graphics processors named Blackwell. The chip is called GB200 and, according to the company, will be shipped later this year. The announcement comes after the recent partnership between Nvidia and Yotta Digital Services. Yotta received the current generation of 4000 Hopper chips, H100, marking it as the first arrival of the GPUs. 

According to a Bloomberg report, Blackwell chips, made up of 208 billion transistors, will be the basis of new computers and other products deployed by the world’s largest data center operators. This roster includes Amazon.com Inc., Microsoft Corp., Alphabet Inc.’s Google, and Oracle Corp. 

As per Nvidia, Blackwell-based processors, like the GB200, offer a massive performance upgrade for AI companies, with 20 petaflops in AI performance compared to 4 petaflops for the H100. The additional processing power will enable AI companies to train more extensive and intricate models, reports CNBC.

NIM Inference Microservices

NVIDIA’s NIM microservices offer ready-to-use containers powered by their advanced AI software. These containers, which include Triton Inference Server and TensorRT-LLM, help developers deploy AI models much faster, reducing the time it takes from weeks to just minutes.

These microservices provide easy-to-use tools for developers to create AI applications in areas like language understanding, speech recognition, and drug discovery. Developers can use their own data securely stored in their systems to build these applications. These applications can grow or shrink as needed, giving flexibility and speed when running AI on NVIDIA-powered computers.

Companies like NVIDIA, A121, Adept, Cohere, Getty Images, and Shutterstock, as well as other open models from companies like Google, Hugging Face, Meta, Microsoft, Mistral AI, and Stability AI, are using these microservices as they support their models and are the fastest and most efficient way to deploy AI models in production.

ServiceNow, a business software company, recently announced that it is using NIM microservices to develop and deploy new AI applications quickly and cost-effectively.

Nvidia’s India collaborations

Nvidia is also contributing to the broader adoption of AI technologies across various sectors in India by partnering with Indian companies and conglomerates, leveraging NVIDIA’s GenAI software to drive innovation and enhance their offerings. 

Infosys plans to set up an NVIDIA Centre of Excellence to train and certify 50,000 of its employees on NVIDIA AI technology, aiming to provide generative AI expertise to its global customer network. Wipro also announced a collaboration with NVIDIA to help healthcare companies accelerate the adoption of generative AI through AI-driven strategies, products, and services. 

Reliance Industries Limited and Tata Group are partnering with NVIDIA to build an AI computing infrastructure and platforms based on NVIDIA technology, including the NVIDIA GH200 Grace Hopper Superchip and NVIDIA DGX Cloud. 

These partnerships indicate a strong momentum towards adopting AI technologies among Indian enterprises, aiming not only to transform their own operations and service offerings but also to contribute significantly to the broader adoption of AI technologies across various sectors in India.

The soaring sales

Nvidia became the first chipmaker to achieve a market capitalization exceeding $ 2 trillion, trailing only Microsoft and Apple Inc. overall. The announcement of new chips and AI commuting platform was eagerly anticipated, which in return propelled Nvidia’s stock by 79% this year as of Monday’s close, according to Bloomberg.

Consequently, the investors were not easily impressed by the presentation’s details, which led to a decline in the company’s shares by as much as 3.9% in New York on Tuesday. 

However, CFRA analysts, after the announcements, increased their price target for the stock from $600 to $700. They emphasized that “NVDA will drive the upcoming Industrial AI revolution as robotics become more prevalent, leading to the emergence of AI-powered factories and large virtual warehouses utilizing the omniverse/digital twins.”

In conclusion, Nvidia’s recent announcements signify breakthrough advancements in AI and robotics fields. Despite some skepticism, Nvidia, with its innovative technological advancements, remains a key player in the AI revolution with continued market capitalization and growth projections.

Image Source: NVIDIA

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