Generative AI: Scaling Laws Post DeepSeek
The Future of AI Infrastructure
The recent stock market collapse, triggered by the sudden fervor for the Chinese artificial intelligence (AI) breakthrough DeepSeek AI, and its apparently much cheaper computing approach, might lead one to believe that companies are dramatically reducing their spending on chips and systems for AI. However, a recent generative AI conference in New York, hosted by the Bloomberg Intelligence unit of Bloomberg, left a different impression: the hunger to expand the use of generative AI is so great that spending is set to continue to drive enormous investment.
The Demand for AI Infrastructure
The conference, titled "Generative AI: Scaling Laws Post DeepSeek," featured constant references to how demand will drive greater spending. "We had ten panels today, and not a single person on those panels said we have more capacity than we need," said Mandeep Singh, a senior technology analyst with Bloomberg Intelligence, and an organizer of the event. "And no one was talking about a bubble" in infrastructure, added Singh. "The most important question right now in front of everybody is the AI infrastructure build. Yeah. Where are we in that cycle?"
The Impact of DeepSeek AI
The hope raised by DeepSeek AI is that a lot of work can be done with less expense. "DeepSeek shook a lot of people," said Anurag Rana, Singh’s colleague at Bloomberg Intelligence, and the senior IT services and software analyst. "If you are not needing that many GPUs to run models, then why do we need $500 billion for the Stargate project," he observed, referring to a planned US AI project run by Japan’s SoftBank Group, OpenAI, and database giant Oracle. Everyone in the industry hopes that AI costs will come down rapidly just like the cost of cloud computing dropped.
The Need for Custom AI Models
Panelists agreed that while "foundation" or "frontier" large language models will continue to be developed, individual enterprises may use hundreds or even thousands of AI models. "We use a family of models," said Shawn Edwards, Bloomberg’s chief technologist, in an interview with David Dwyer, the head of Bloomberg Intelligence. "There is no such thing as a best model." These models might be trained on a company’s proprietary data via fine-tuning, the act of re-training a neural network after its initial "pre-training" on generic data.
The Rise of AI Agents
The proliferation of AI models is increasing the processing demand, many speakers suggested. "You won’t cram a whole process into one agent, you’ll break it up into parts," said Ray Smith, Microsoft’s head of Copilot Studio agents and automation. Through a single interface, predicted Smith, such as Copilot, "we will interact with hundreds of agents — they are just apps in the new world" of programming.
The Need for Cost Reduction
The trend to get AI "agents" to more people in an organization is further demanding a cost reduction, said James McNiven, the head of product management for microprocessor maker ARM Holdings, in a chat with Bloomberg’s Hyde. "How do we provide access on more and more devices," he posed. "We are seeing models at a PhD-level" of task capability, he said.
The Future of AI Computing
Despite the ambitious scenarios, one condition could upend all the use cases and investment plans: the economy. "The other big thing we are focused on is the non-AI tech spending," said Rana. "When we look at the likes of IBM, Accenture, Microsoft, and all the others, when we just put aside AI for a second, that is something that is going to be a struggle going into this earnings season."
Conclusion
The future of AI infrastructure is looking bright, with demand driving greater spending and investment. However, the economy remains a wild card, and the impact of potential economic uncertainty and recession on AI spending remains to be seen.
Frequently Asked Questions
Q: What is DeepSeek AI?
A: DeepSeek AI is a Chinese artificial intelligence (AI) breakthrough that has sparked a sudden fervor for cheaper computing approaches.
Q: What is the impact of DeepSeek AI on AI infrastructure spending?
A: The hope raised by DeepSeek AI is that a lot of work can be done with less expense, potentially driving greater spending on AI infrastructure.
Q: What is the need for custom AI models?
A: The need for custom AI models arises from the fact that individual enterprises may use hundreds or even thousands of AI models, which cannot be met by a single "best" model.
Q: What is the rise of AI agents?
A: The rise of AI agents is driven by the need to break down complex processes into smaller parts, making it easier to deploy and manage AI models.
Q: What is the need for cost reduction in AI?
A: The need for cost reduction in AI is driven by the trend to get AI "agents" to more people in an organization, as well as the proliferation of AI models, which is increasing processing demand.
