t GTC 2026, Nvidia committed to unlocking new levels of compute for the industry's leading innovators. At the same time, another narrative about bottom-up innovation was unfolding in other corners of GTC.

On a quiet veranda at the San Jose Convention Center, The Deep View spoke to Illia Polosukhin, co-founder of Near, about "user-owned AI," where the technology is decentralized, all your data is kept separate from the models, and agents are treated as a secure, separate OS.

While Near doesn't have the marketing muscle of OpenAI, Anthropic, and other leading players in the AI ecosystem, it's counting on the kind of bottom-up, word-of-mouth momentum that turned OpenClaw into a viral hit, aiming to spread the mantra about a safer and more empowered alternative to the way most people are experiencing today's AI.

Meanwhile, Nvidia CEO Jensen Huang emphasized that more compute means more intelligence, more intelligence means more value, and more value means more revenue. Huang told a full capacity audience at the San Jose Civic on Wednesday that “intelligence is directly correlated to the amount of compute that you have.”

Amid the veritable firehose of announcements at the conference, Nvidia posed an entirely new scaling law to continue pushing the narrative of more: Agentic scaling.

• Following pretraining scaling, post-training scaling and test-time scaling, this new scaling law involves AI not just talking to humans, but to other AIs, vastly increasing demand for low-latency, large-context inference.
• These multi-agent systems, Nvidia claims, will unlock multi-trillion parameter models, turning daylong requests into hours. To do so, however, these systems need to get a lot faster, with Nvidia emphasizing the need to deliver tokens 15 times faster and with 10-times larger models.

“The best open [models] are trillion-parameter models, and … if you look at the proprietary models, they’re more than a trillion parameters,” Kari Briski, VP of generative AI software at Nvidia, told The Deep View. “Now, the fourth scaling law is not just about one reasoning model. It’s about a swarm of agents with subagents. Agents talking to agents.”

Polosukhin is also all-in on agents, including the claw revolution. Near has IronClaw, which offers a more secure version of OpenClaw, similar to NanoClaw and Nvidia's NemoClaw. The company also launched a secure agent marketplace designed to run agents that can offload work and earn money, all within its decentralized, security-first platform.

Our Deeper View

It was impressive to see Nvidia racing ahead with all of its vast resources to help scale the exponential growth of the AI ecosystem. Of course, the companies that can most benefit from these upgrades are the ones with the most resources to purchase compute — Google, Microsoft, OpenAI, Anthropic, etc. — and that risks further centralizing the AI industry around a few leading players. Contrast that with the decentralized vision of Near's Polosukhin, a Google researcher who pioneered the transformer that launched the generative AI revolution. Polosukhin speaks emphatically about the risks of centralizing too much power and the importance of having an alternative. Though Nvidia spent the week preaching about the importance of open models and the bottom-up OpenClaw revolution, tacitly acknowledging the need for a balanced AI ecosystem, the inevitable winners of the exponential scaling of compute will be the ones that can pay for it.