Is Nvidia Blackwell So Hot That Nobody Wants Hopper?

At this year’s GTC event in San Jose, Nvidia CEO Jensen Huang held over 25,000 people in the palm of his hand, captivated by his vision of AI and how it could transform the world we live in. Some folks in the audience couldn’t keep up and started fiddling with their phones.

The Rise of Blackwell

Jensen half-jokingly said nobody should buy a Hopper GPU now that Blackwell is in full production, playing the role of what he called the company’s "Chief Revenue Destruction Officer." He noted the frustration his sellers would feel upon hearing his advice. Investors did not appreciate his sarcasm either, and the stock is down 2.6% since GTC25 kicked off. However, according to Jensen, AI inference requires 100 times more computing now than a year ago, thanks mainly to the introduction of "reasoning" and agentic AI.

The New Token Boom

In fact, these trends, coupled with incredibly dense infrastructure and software revenue, are creating a new Token Boom that Jensen will harvest as a new revenue boom, in spite of the product churn.

Is Hopper Still Relevant?

While Blackwell is amazingly fast, with up to 40 times more tokens/second for inference, it also requires significant data center power and water cooling upgrades for the AI Factories Jensen is pushing. However, Hopper may be just fine for many AI developers for now. Nvidia has already shipped nearly three times the number of Blackwell GPUs compared to all Hopper chips in 2024. There is no doubt now that the $11B of Blackwell-based systems Nvidia shipped in Q4 is the start of a new demand cycle.

The Importance of Disclosure

Moving to an annual product cycle creates tension, but disclosing the roadmap is essential to prepare the supply chain and ecosystem for the next two years of innovation. No data center can power an 800 Kilowatt rack required for Rubin Ultra today, but they will need to power and cool the beast if they want to remain competitive when Nvidia starts shipping its future racks.

Nvidia Dynamo: Another Defensive Moat?

When the rest of the industry is trying to match (unsuccessfully) Nvidia GPU performance, Nvidia is optimizing the entire AI factory. The new Dynamo "AI Factory OS" and Co-packaged optical networking are two examples.

The Updated Nvidia Hardware Roadmap

Here’s the new Nvidia GPU lineup through 2028. The annual increase in computing power, memory, and networking should be awe-inspiring, but the audience at GTC seemed to have expected nothing less from the company that practically reinvented computing.

Co-Packaged Optical Photonic Scale-out

My colleague Jim McGregor of Tirias Research has already covered this innovation in Forbes, so I won’t belabor the point. The bottom line is that these co-packaged optics were not expected to be ready by any vendor for another couple years. Now Nvidia will ship CPO networking for scale-out to millions of GPUs later this year.

Conclusion

Nvidia is transitioning to its future place in the industry as THE foundational AI company. Jensen showed slides from many large enterprise clients that made this point; each had green icons with up to a dozen Nvidia Inference Micro-Services (NIMS) modules and hardware embedded in their AI stacks; once these green icons are in there, they won’t come out easily.

FAQs

Q: What is Nvidia’s plan for the future of AI?
A: Nvidia is transitioning to its future place in the industry as THE foundational AI company, with a focus on AI inference and scale-out.

Q: Will Hopper still be relevant?
A: While Blackwell is amazingly fast, with up to 40 times more tokens/second for inference, it also requires significant data center power and water cooling upgrades for the AI Factories Jensen is pushing. However, Hopper may be just fine for many AI developers for now.

Q: What is the new Token Boom?
A: The new Token Boom is a result of the trends, coupled with incredibly dense infrastructure and software revenue, creating a new revenue boom for Nvidia.

Disclosures

This article expresses the opinions of the author and is not to be taken as advice to purchase from or invest in the companies mentioned. My firm, Cambrian-AI Research, is fortunate to have many semiconductor firms as our clients, including Baya Systems, BrainChip, Cadence, Cerebras Systems, D-Matrix, Esperanto, Flex, Groq, IBM, Intel, Micron, NVIDIA, Qualcomm, Graphcore, SImA.ai, Synopsys, Tenstorrent, Ventana Microsystems, and scores of investors. I have no investment positions in any of the companies mentioned in this article. For more information, please visit our website at https://cambrian-AI.com.

Innovations in workforce productivity have been transforming the way we work, live, and interact with each other. As technology advances, we’re witnessing a significant shift in the concept of ‘work’. In this article, we’ll explore the impact of AI, automation, and robotics on the future of work and how it’s redefining the way we approach our daily tasks.

What is the Future of Work?

The future of work is about leveraging technology to increase productivity, efficiency, and accuracy. With the rise of AI, automation, and robotics, tasks that were previously time-consuming, labor-intensive, or prone to human error are being taken over by machines. This has opened up new opportunities for humans to focus on higher-value tasks that require creativity, empathy, and complex problem-solving skills.

Role of AI in the Future of Work

Artificial Intelligence (AI) is playing a crucial role in shaping the future of work. AI-powered tools are being used to automate repetitive, mundane, and high-volume tasks, freeing up human resources to focus on more strategic and creative work. For example, AI-powered chatbots are being used in customer service to provide 24/7 support, while AI-powered data analytics is helping businesses make data-driven decisions.

Impact of Automation on the Future of Work

Automation is another significant force driving change in the future of work. Automation is enabling businesses to streamline processes, reduce costs, and improve efficiency. For instance, automated production lines are increasing productivity in manufacturing, while automated customer service platforms are reducing response times and improving customer satisfaction.

Emergence of Robotics in the Future of Work

Robotics is also redefining the future of work. Robots are being used in various industries, from manufacturing to healthcare, to perform tasks that require precision, speed, and accuracy. For example, robots are being used in surgery to perform complex procedures, while robots are being used in logistics to improve supply chain efficiency.

What Does the Future of Work Mean for Humans?

The future of work is not just about machines replacing humans, but also about humans working alongside machines to achieve greater productivity, innovation, and success. As humans, we have the capacity to think creatively, empathize with others, and make complex decisions. The future of work is about harnessing these human skills to create a better world for all.

Conclusion

In conclusion, the future of work is about embracing new technologies to increase productivity, efficiency, and accuracy. AI, automation, and robotics are transforming the way we work, live, and interact with each other. As we move forward, it’s essential to recognize the benefits and challenges of these technologies and how they can be used to create a better world for all.

FAQs

Q: What are the benefits of AI, automation, and robotics in the future of work?

A: The benefits include increased productivity, efficiency, and accuracy, as well as the ability to focus on higher-value tasks that require creativity, empathy, and complex problem-solving skills.

Q: What are the challenges of AI, automation, and robotics in the future of work?

A: The challenges include the risk of job displacement, the need for continuous upskilling and reskilling, and the potential for unintended consequences if not implemented responsibly.

Q: How can humans work alongside machines in the future of work?

A: Humans can work alongside machines by focusing on tasks that require creativity, empathy, and complex problem-solving skills, while machines take over tasks that require precision, speed, and accuracy.

Q: What are the implications of AI, automation, and robotics on the future of work for different industries?

A: The implications vary by industry, but overall, AI, automation, and robotics are transforming industries such as manufacturing, logistics, healthcare, and customer service.

Q: What can be done to prepare for the future of work?

A: To prepare for the future of work, individuals and organizations must invest in continuous learning, upskilling, and reskilling, as well as develop the skills and competencies required for the future landscape.

So, What Is Manus?

Manus is currently an invite-only research preview, immediately casting doubt on developer Monica’s claim that it’s the first AI agent. OpenAI’s similar Operator agent model is also a research preview but is at least available to customers – if only for those paying for the $200-per-month ChatGPT Pro tier.

But a developer video has been released showing it performing real-world tasks like screening resumes, researching housing and analyzing stocks.

How Does It Work?

Its name, derived from the Latin “Mens et Manus” (“mind and hand”), reflects its structure: LLM algorithms as the mind and deterministic algorithms as the hand. Unlike ChatGPT, which only generates responses, Manus can execute actions—integrating with services, processing data, and performing operations like a traditional computer program.

Is This AGI?

No, it doesn’t qualify as AGI – as the developers themselves state in their video, it’s a “glimpse” of AGI – artificial general intelligence.

AGI is best thought of as an eventual goal of developing AI that can learn to carry out just about any task, much like a human can. It uses the tools it’s given or, if it doesn’t have anything suitable, can work out how to find the tools it needs, or even design and use new tools.

Geopolitical Implications

In recent years, we have seen AI become a geopolitical battleground, primarily between the U.S. and China.

The leadership of both nations has made it clear they recognize its enormous potential to shape the future due to its impact on everything from medical research to the economy to warfare.

Everyday Agents

So, the race is on to create what I feel will become the equivalent of the computer operating system for the AI era. Essentially, agentic AI that enables anyone to do things with machines that previously would have taken expert-level knowledge and skills.

Conclusion

Manus AI represents a significant leap from chatbots to autonomous agents capable of executing real-world tasks with minimal human oversight. Its capabilities and potential applications are vast, and its development is likely to have a significant impact on the future of AI and its applications.

FAQs

Q: What is Manus AI?
A: Manus is an invite-only research preview that can perform real-world tasks like screening resumes, researching housing, and analyzing stocks.

Q: How does Manus work?
A: Manus uses LLM algorithms as the mind and deterministic algorithms as the hand to integrate with services, process data, and perform operations like a traditional computer program.

Q: Is Manus AGI?
A: No, Manus is not AGI, but rather a glimpse of AGI. AGI is best thought of as an eventual goal of developing AI that can learn to carry out just about any task, much like a human can.

Q: What are the geopolitical implications of Manus?
A: The development of Manus and other AI agents could potentially lead to a shift in the balance of power between nations, with China and the U.S. being the primary players in the AI race.

Q: What is the future of AI?
A: The future of AI is likely to be shaped by the development of agentic AI, which will enable humans to work with machines in ways that were previously impossible, leading to significant advancements in fields such as medicine, education, and the economy.