Sun brief#44: Nvidia’s Brain for Robots

by kamblenayan826
September 15, 2025
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Nvidia Launches $3,499 ‘Robot Brain’ to Drive Robotics Growth
Stock Updates
Google Supercharges Virginia with $9B Data Center Expansion
AI Highlights of the Week
Nvidia Forecasts Slowing Growth After Two-Year AI Boom
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Nvidia Launches $3,499 ‘Robot Brain’ to Drive Robotics Growth

Nvidia Launches $3,499 Jetson AGX Thor Robotics Chip Developer Kit

Key Points:

Robot Brain” for Prototyping: The Jetson AGX Thor enables companies to design and test robots before moving to production. For bulk orders (1,000+ units), Nvidia will sell the Thor T5000 modules at a discounted $2,999 each.
Robotics Growth Market: CEO Jensen Huang has called robotics Nvidia’s biggest growth opportunity outside of AI, which has already tripled company sales in the past two years.
Industry Adoption: Companies such as Agility Robotics, Amazon, Meta, and Boston Dynamics are already using Nvidia’s Jetson chips. Nvidia also backs startups like Field AI to expand robotics applications.

Why It Matters:

With the Jetson AGX Thor, Nvidia extends its reach beyond data centers into robotics and autonomous machines, reinforcing its role as core infrastructure for the AI era.

Nvidia’s new ‘robot brain’ goes on sale for $3,499 as company targets robotics for growth

Key Points

Nvidia announced on Monday that its latest robotics chip module, the Jetson AGX Thor, is now on sale for $3,499 as a developer kit.
The company calls the chip a “robot brain.” The first kits ship next month, Nvidia said last week, and the chips will allow customers to create robots.
Nvidia CEO Jensen Huang has said robotics is the company’s largest growth opportunity outside of artificial intelligence.

Nvidia announced Monday that its latest robotics chip module, the Jetson AGX Thor, is now on sale for $3,499 as a developer kit.

The company calls the chip a “robot brain.” The first kits ship next month, Nvidia said last week, and the chips will allow customers to create robots.

After a company uses the developer kit to prototype their robot, Nvidia will sell Thor T5000 modules that can be installed in production-ready robots. If a company needs more than 1,000 Thor chips, Nvidia will charge $2,999 per module.

CEO Jensen Huang has said robotics is the company’s largest growth opportunity outside of artificial intelligence, which has led to Nvidia’s overall sales more than tripling in the past two years.

“We do not build robots, we do not build cars, but we enable the whole industry with our infrastructure computers and the associated software,” said Deepu Talla, Nvidia’s vice president of robotics and edge AI, on a call with reporters Friday.

The Jetson Thor chips are based on a Blackwell graphics processor, which is Nvidia’s current generation of technology used in its AI chips, as well as its chips for computer games.

Nvidia said that its Jetson Thor chips are 7.5 times faster than its previous generation. That allows them to run generative AI models, including large language models and visual models that can interpret the world around them, which is essential for humanoid robots, Nvidia said. The Jetson Thor chips are equipped with 128GB of memory, which is essential for big AI models.

Companies including Agility Robotics, Amazon, Meta and Boston Dynamics are using its Jetson chips, Nvidia said. Nvidia has also invested in robotics companies such as Field AI.

However, robotics remains a small business for Nvidia, accounting for about 1% of the company’s total revenue, despite the fact that it has launched several new robot chips since 2014. But it’s growing fast.

Nvidia recently combined its business units to group its automotive and robotics divisions into the same line item. That unit reported $567 million in quarterly sales in May, which represented a 72% increase on an annual basis.

The company said its Jetson Thor chips can be used for self-driving cars as well, especially from Chinese brands. Nvidia calls its car chips Drive AGX, and while they are similar to its robotics chips, they run an operating system called Drive OS that’s been tuned for automotive purposes.

WATCH: Nvidia’s China risks loom large ahead of earnings

Google Supercharges Virginia with $9B Data Center Expansion

Google to Invest Additional $9 Billion in Virginia Data Centres

Alphabet’s Google is investing an additional US$9 billion in Virginia through 2026 to expand cloud and AI infrastructure, marking a major step in the US data centre boom.

Key Points:

New and Expanded Facilities: Google will build a new data centre in Chesterfield County and expand existing campuses in Loudoun and Prince William counties.
Industry Trend: Other major tech companies, including Microsoft, Amazon, and Meta, are also investing heavily in AI-related infrastructure.
Energy & Partnerships: Dominion Energy will provide power, and Google is working with local partners to address energy capacity and efficiency.
Education Initiative: Google committed US$1 billion to provide Virginia-based college students free access to the Google AI Pro plan and AI training for one year.

Why It Matters:
The investment highlights the growing race to build AI infrastructure in the US, strengthens domestic tech capabilities, and supports education and local partnerships to meet energy and training demands.

A slew of major technology companies are rushing to build data centres in the US, citing a need to sustain the massive AI boom

The data centres in the US have largely been concentrated in northern Virginia, nicknamed “Data Center Alley”, since the initial cloud buildout in the early 2000s. PHOTO: BLOOMBERG

[NEW YORK] Alphabet’s Google is investing an additional US$9 billion in Virginia till 2026 to enhance cloud and artificial intelligence (AI) infrastructure across the state, marking the latest in a series of big tech investments in US data centres.

The money will go towards building a new data centre in Chesterfield County and expanding existing campuses in Loudoun and Prince William counties, the company said on Wednesday (Aug 27).

A slew of major technology companies are rushing to build data centres in the US, citing a need to sustain the massive AI boom. They are also showing that they are making investments domestically amid US President Donald Trump’s nationalist policies to propel the US to the forefront of the global AI race.

Reaching Across the Isles: UK-LLM Brings AI to UK Languages With NVIDIA Nemotron

Trained on the Isambard-AI supercomputer, a new model developed by University College London, NVIDIA and Bangor University taps NVIDIA Nemotron open-source techniques and datasets to enable AI reasoning for Welsh and other UK languages for public services including healthcare, education and legal resources.

September 13, 2025 by Kari Briski

Celtic languages — including Cornish, Irish, Scottish Gaelic and Welsh — are the U.K.’s oldest living languages. To empower their speakers, the UK-LLM sovereign AI initiative is building an AI model based on NVIDIA Nemotron that can reason in both English and Welsh, a language spoken by about 850,000 people in Wales today.

Enabling high-quality AI reasoning in Welsh will support the delivery of public services including healthcare, education and legal resources in the language.

“I want every corner of the U.K. to be able to harness the benefits of artificial intelligence. By enabling AI to reason in Welsh, we’re making sure that public services — from healthcare to education — are accessible to everyone, in the language they live by,” said U.K. Prime Minister Keir Starmer. “This is a powerful example of how the latest AI technology, trained on the U.K.’s most advanced AI supercomputer in Bristol, can serve the public good, protect cultural heritage and unlock opportunity across the country.”

The UK-LLM project, established in 2023 as BritLLM and led by University College London, has previously released two models for U.K. languages. Its new model for Welsh, developed in collaboration with Wales’ Bangor University and NVIDIA, aligns with Welsh government efforts to boost the active use of the language, with the goal of achieving a million speakers by 2050 — an initiative known as Cymraeg 2050.

U.K.-based AI cloud provider Nscale will make the new model available to developers through its application programming interface.

“The aim is to ensure that Welsh remains a living, breathing language that continues to develop with the times,” said Gruffudd Prys, senior terminologist and head of the Language Technologies Unit at Canolfan Bedwyr, the university’s center for Welsh language services, research and technology. “AI shows enormous potential to help with second-language acquisition of Welsh as well as for enabling native speakers to improve their language skills.”

This new model could also boost the accessibility of Welsh resources by enabling public institutions and businesses operating in Wales to translate content or provide bilingual chatbot services. This can help groups including healthcare providers, educators, broadcasters, retailers and restaurant owners ensure their written content is as readily available in Welsh as they are in English.

Beyond Welsh, the UK-LLM team aims to apply the same methodology used for its new model to develop AI models for other languages spoken across the U.K. such as Cornish, Irish, Scots and Scottish Gaelic — as well as work with international collaborators to build models for languages from Africa and Southeast Asia.

“This collaboration with NVIDIA and Bangor University enabled us to create new training data and train a new model in record time, accelerating our goal to build the best-ever language model for Welsh,” said Pontus Stenetorp, professor of natural language processing and deputy director for the Centre of Artificial Intelligence at University College London. “Our aim is to take the insights gained from the Welsh model and apply them to other minority languages, in the U.K. and across the globe.”

Tapping Sovereign AI Infrastructure for Model Development

The new model for Welsh is based on NVIDIA Nemotron, a family of open-source models that features open weights, datasets and recipes. The UK-LLM development team has tapped the 49-billion-parameter Llama Nemotron Super model and 9-billion-parameter Nemotron Nano model, post-training them on Welsh-language data.

Compared with languages like English or Spanish, there’s less available source data in Welsh for AI training. So to create a sufficiently large Welsh training dataset, the team used NVIDIA NIM microservices for gpt-oss-120b and DeepSeek-R1 to translate NVIDIA Nemotron open datasets with over 30 million entries from English to Welsh.

They used a GPU cluster through the NVIDIA DGX Cloud Lepton platform and are harnessing hundreds of NVIDIA GH200 Grace Hopper Superchips on Isambard-AI — the U.K.’s most powerful supercomputer, backed by £225 million in government investment and based at University of Bristol — to accelerate their translation and training workloads.

This new dataset supplements existing Welsh data from the team’s previous efforts.

Capturing Linguistic Nuances With Careful Evaluation

Bangor University, located in Gwynedd — the county with the highest percentage of Welsh speakers — is supporting the new model’s development with linguistic and cultural expertise.

Welsh translation of: “The aim is to ensure that Welsh remains a living, breathing language that continues to develop with the times.” — Gruffudd Prys, Bangor University

Prys, from the university’s Welsh-language center, brings to the collaboration about two decades of experience with language technology for Welsh. He and his team are helping to verify the accuracy of machine-translated training data and manually translated evaluation data, as well as assess how the model handles nuances of Welsh that AI typically struggles with — such as the way consonants at the beginning of Welsh words change based on neighboring words.

The model, as well as the Welsh training and evaluation datasets, are expected to be made available for enterprise and public sector use, supporting additional research, model training and application development.

“It’s one thing to have this AI capability exist in Welsh, but it’s another to make it open and accessible for everyone,” Prys said. “That subtle distinction can be the difference between this technology being used or not being used.”

Deploy Sovereign AI Models With NVIDIA Nemotron, NIM Microservices

The framework used to develop UK-LLM’s model for Welsh can serve as a foundation for multilingual AI development around the world.

Benchmark-topping Nemotron models, data and recipes are publicly available for developers to build reasoning models tailored to virtually any language, domain and workflow. Packaged as NVIDIA NIM microservices, Nemotron models are optimized for cost-effective compute and run anywhere, from laptop to cloud.

Europe’s enterprises will be able to run open, sovereign models on the Perplexity AI-powered search engine.

Huang Renxun said at the opening ceremony of the 2025 China International Supply Chain Promotion Expo in July this year that the next wave of AI will be Robotics, “which have the ability to reason and execute, and can understand the physical world.” GGII predicts that China’s humanoid Robotics market will reach nearly 38 billion yuan by 2030, the compound growth rate will exceed 61% in 2024-2030, and sales of humanoid Robotics in China will grow from around 0.004 million units to 0.2712 million units.

According to the Financial Federation’s theme library, among the relevant listed companies:

Obi Zhongguang has now integrated various products into the NVIDIA Isaac Sim Robotics simulation development platform. When platform users carry out Robotics simulation testing and development with the company’s integrated products, they can easily call the company’s 3D camera data through the platform to quickly create a 3D vision solution.

CLP Port is currently cooperating in robotics and related Industry, mainly based on NVIDIA’s Jetson products. Application scenarios including low-speed unmanned vehicles and robotic arms have been implemented one after another.

Spexo