Artificial intelligence is not just a program or chatbot; it represents "a new industry on the scale of electrification." The development of this technology will create numerous jobs for electricians, welders, and builders. This view was expressed by Nvidia CEO Jensen Huang.

"These are skilled, well-paying jobs, and there is a shortage of them. You don’t need a computer science degree to participate in this transformation," he wrote.

This statement comes amid growing market concerns about AI's impact on employment. Since the beginning of 2026, the tech sector has faced falling stock prices, mass layoffs at fintech company Block, and alarming statements from Anthropic's leadership about potential job replacements by neural networks.

Huang's essay was a response to these concerns. He cited an example from radiology: while AI assists in analyzing images, the demand for doctors continues to rise. According to him, increased productivity opens new opportunities that drive further economic growth.

"This is not a paradox," emphasized the Nvidia CEO.

The 'Five-Layer Cake'

Huang also outlined the concept of the "five-layer cake" of AI architecture. At its base is energy, followed by chips, physical infrastructure, models, and applications.

He stated that the AI industry has transformed into a large-scale industrial production. This sector requires trillions in investments, a vast number of specialists, and a fundamental shift in the nature of computing itself.

Traditional software operates by searching for and executing pre-existing instructions. In contrast, neural networks generate responses anew each time, "reasoning" in real-time based on the context provided.

Since "intelligence" is produced "here and now," the entire computing stack must be built from scratch. AI cannot function effectively on old data centers; it requires specialized infrastructure, starting from the very bottom level—energy.

"Real-time generated intelligence requires real-time produced energy. Energy is the primary principle of AI infrastructure and a limiting factor on how much intelligence the system can produce," explained Huang.

This paradigm extends far beyond Nvidia's supply chains. If energy becomes the primary resource, any disruption in its generation (for example, due to conflict in the Middle East) becomes a direct obstacle to scaling new technologies.

Huang acknowledged that building specialized infrastructure is still in its early stages. Hundreds of billions of dollars have already been invested in the industry, but trillions more are needed. Specialized "AI factories" are being built at unprecedented rates worldwide.

He also mentioned open-source models. DeepSeek-R1 is an example of how access to powerful neural networks accelerates adoption and increases demand for training, infrastructure, chips, and energy. Open source is not a threat to Nvidia's business; rather, it fuels it, Huang concluded.

Platform for AI Agents

According to sources from WIRED, the chipmaker is negotiating partnerships with Salesforce, Cisco, Google, and Adobe. The goal is to launch an open platform for AI agents under the working title NemoClaw.

This product will allow companies to integrate autonomous assistants into their workflows. Access to the platform will not be tied to Nvidia hardware—it can be used independently of the underlying equipment.

As of this writing, no official agreements have been made. Nvidia did not respond to the publication's request for comment.

The company's interest in agents coincides with the rising popularity of open AI tools that run locally on devices and perform tasks with minimal human involvement. A notable example is the OpenClaw project (also known as Clawdbot and Moltbot), which generated significant buzz in China in March this year.

Recall that at the end of 2025, Nvidia doubled its net profit due to record demand for AI chips.