Opinion
From Nvidia’s vision to Google’s nuclear reactors: The elephant in the room of Israeli AI
"The Israeli government and local industry must understand: AI is not just code; it is infrastructure," writes Marina Risher of AudioCodes.
In recent weeks, the Israeli tech sector has been in a festive mood. The completion of the backup infrastructure and secure zones for Project Nimbus, led by Google and AWS, was rightly perceived as a significant milestone for Israeli data sovereignty. At the same time, Jensen Huang, CEO of NVIDIA, continues to preach the vision of "Sovereign AI" from every possible stage, the concept that every nation must possess independent AI infrastructure, from chips to data, to secure its economic and security future.
However, between the ribbon-cutting ceremonies in Israel and Huang’s global vision, a white elephant is hiding in the room that few are talking about: Physics. Or to be more precise, Energy.
While we in Israel celebrate the migration to the cloud, U.S. tech giants already realize that existing infrastructure won't suffice. These are not just estimates; actions speak louder than words. Google, Microsoft, and Amazon have recently signed massive deals to purchase nuclear energy to feed their power-hungry server farms. They understand that the traditional power grid will simply collapse under the exponential demand of GenAI. And this brings us to the Israeli paradox.
An Energy Island in a Compute Revolution
Israel is an energy island. We do not have cross-border power grids to lean on during peak loads, and civilian nuclear reactors are not a viable option in the foreseeable future. We must answer the growing demands with what we have.
The forecasts are challenging. According to data from Mordor Intelligence, power consumption by data centers in Israel is expected to jump by approximately 7% annually through 2030. The growth in demand for heavy computing is outpacing the rate of national infrastructure deployment.
This means that if we continue to run toward the default solution of moving everything to the cloud, we may find ourselves facing a dead end: either the grid won't have the capacity, or, the more likely scenario, energy and computing prices will skyrocket to levels that make AI usage unviable for many organizations.
The problem is not just national; it is strictly business. CEOs and IT managers who jumped on the GenAI bandwagon with enthusiasm are now beginning to experience what is known as "bill shock."
Large Language Models (LLMs) are energy and resource gluttons. As an organization implements more automation, bots, and data processing, costs rise. Cloud centralization, which once seemed like a magic solution for efficiency, is turning into a cost trap in the new reality of AI. So how do we solve the equation? How do we maintain data sovereignty, adopt advanced AI, and remain profitable without crashing the power grid? The answer requires an architectural shift.
The future of enterprise AI in Israel lies not only in the massive server farms of Project Nimbus but in a smart integration between the cloud and Edge Computing:
1. Returning Power to the Edge: Not every query needs to travel to a remote server and back. Organizations must adopt a hybrid architecture in which some processing is performed locally, on-premises, or on edge devices. This is particularly critical in real-time-sensitive applications, such as Voice AI, a field where every fraction of a second of latency determines service quality. Local processing not only improves performance and maintains privacy but also reduces energy consumption and bandwidth costs.
2. A Diet for Models: The era of one size fits all is over. You don't need a cannon (a massive model like GPT-4) to kill a fly (a simple organizational task). The future belongs to Domain-Specific Models and advanced compression techniques. These models are smaller, more precise for the organization's needs, and consume a fraction of the energy.
True Sovereignty is also Sustainability
The Israeli government and local industry must understand: AI is not just code; it is infrastructure. To realize the vision of Sovereign AI and ensure competitiveness, we cannot rely solely on building more and more central data centers. We need to build a smart ecosystem that leverages cloud advantages but also knows how to work at the edge.
Those who are wise enough to build a hybrid infrastructure today, combining a sovereign cloud with strong edge capabilities and efficient models, will not only save costs but also ensure their organization can continue to run, even when the power or budget of their competitors starts to run out.
The author is the Senior Product Manager for Secure Regulatory Solutions at AudioCodes.
