With the renewed partnership between NVIDIA and Google Cloud, alongside Iris Energy's strategic investment, NVIDIA experienced a remarkable 19% increase in its stock value.

During their Tuesday announcement, NVIDIA and Google Cloud detailed their partnership's expansion, focusing on new AI infrastructure and software aimed at large-scale generative AI models and enhancing data science workflows.

In a discussion at Google Cloud Next, Thomas Kurian, CEO of Google Cloud, and Jensen Huang, CEO of NVIDIA, spoke about how Google employs NVIDIA's H100 and A100 GPUs for its internal research and projects like DeepMind.

Huang emphasized the significant joint efforts that have led to NVIDIA's GPUs being used for acceleration in various applications. PaxML framework The Jax-based machine learning framework developed by Google is specifically designed to facilitate training for large models, complete with features for experimentation and parallel processing.

According to NVIDIA’s blog post In a recent publication, Google shared that they've been using PaxML along with NVIDIA GPUs for their internal model development, which includes projects from DeepMind. The two companies announced that PaxML is now available on the NVIDIA NGC container registry, giving AI developers access to NVIDIA® H100 and A100 Tensor Core GPUs.

"Google Cloud has always been at the forefront of AI innovation, constantly working to enhance our customer experience,\" Kurian commented. \"Many of Google's services leverage NVIDIA GPUs, and our clients are increasingly looking for NVIDIA's accelerated computing to efficiently develop generative AI models.\"

Furthermore, Google plans to integrate NVIDIA’s GPUs within its Dataproc service, aimed at helping data scientists optimize their Apache Spark workloads. serverless Spark NVIDIA's stock reached an all-time high, closing more than 19% up on Tuesday, topping out above $487, which brings the market capitalization to around $1.2 trillion.

The boost in NVIDIA's stock price was further propelled by Iris Energy's purchase announcement of 248 NVIDIA H100 GPUs for about $10 million.

This GPU acquisition is aimed at generating AI technology, marking this as a significant opportunity for the company.

While Bitcoin mining remains central to Iris Energy’s operations, they acknowledge that generative AI presents new avenues for expansion. revealed The company's high-efficiency cooling systems and their seasoned management team suggest they are well-equipped to capitalize on these trends.

Moreover, Iris Energy pointed out that these GPUs may enable them to tap into adjacent markets that focus on generative AI.

"We see immense potential in leveraging our next-gen data centers for generative AI, especially given the current shortages in rack space and computing power,\" stated Daniel Roberts, Co-Founder and Co-CEO of Iris Energy. \"We believe the demand for sustainable computing is here to stay, and we are uniquely situated to benefit from the growth in the broader sector, whether it relates to ASICs for Bitcoin mining or GPUs for generative AI and beyond.\"

• Dense computing in its data centers
• Could it be that Tesla is gearing up to compete with NVIDIA?
• 100% renewable energy
• 760MW of available power capacity2
• On Tuesday, Tesla unveiled an ambitious plan to roll out a significant AI computing cluster featuring $300 million worth of NVIDIA H100 GPUs, totaling 10,000 units, aimed at enhancing the training capabilities of its Full Self Driving (FSD) initiative.

These latest H100 GPUs are set to improve both the speed and quality of FSD training.

"We may possess the most extensive real-world video training datasets globally, with a hot tier cache capacity exceeding 200PB—exponentially more than what's used for large language models,\" mentioned Tim Zaman, Tesla’s AI Infrastructure & AI Platform Engineering Manager.

The demand for NVIDIA GPUs currently outstrips available supply. In light of this, Tesla has committed over $1 billion toward developing its own supercomputer, dubbed Dojo, to enhance the company's computing power.

Dojo's architecture employs a highly optimized custom chip design developed in-house. If successful at scale, Tesla's chips could become competitive with NVIDIA's offerings.

According to Sawyer Merritt Moreover, Tesla is planning to allocate more than $2 billion for AI training initiatives this year and an additional $2 billion in 2024.

Following this news, Tesla's stock rose by over 7% on Tuesday, marking its most significant single-day increase since March and a three-week high. declared Elon Musk has long hinted at his ambitions in AI, dating back to prior to the formation of his new venture, hinted at in July. Musk was a co-founder of OpenAI but stepped down from its board in 2018.

However, it’s widely known that the demand The company recently revealed a staggering 101% year-over-year revenue growth, accompanied by an impressive 854% rise in earnings per diluted share.

This revenue surge is largely driven by the rising demand for NVIDIA's H100 AI infrastructure, particularly from major cloud service providers and developers in the generative AI landscape, as evidenced in Tuesday’s announcements.

Oppenheimer analyst Rick Schafer added Analysts from Oppenheimer, Goldman Sachs, BofA, and several others have expressed optimistic projections, raising their price targets to $800 and $745 for NVIDIA, respectively.

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Cindy is a passionate journalist at Metaverse Post, focusing on various topics tied to web3, NFTs, the metaverse, and AI. She has conducted insightful interviews with over 30 C-level executives, sharing their valuable perspectives with the readership. Originally hailing from Singapore, Cindy now resides in Tbilisi, Georgia, holding a Bachelor’s degree in Communications & Media Studies from the University of South Australia and boasts a decade of experience in journalism and writing. xAI She actively engages with press releases, news updates, and interview prospects.

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