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Sagence AI: Analog Chips for More Efficient AI
Startup aims to reduce energy consumption of AI models with new in-memory architecture
Isabella V19 November 2024

 

 

 

Sagence AI is developing analog chips to address the rising energy costs of AI, creating an alternative to traditional GPUs. With its in-memory approach and a focus on power efficiency, the startup aims to reduce power demand by improving data speed and density. However, challenges related to manufacturing and competing with giants such as Nvidia could hinder its path.

Key points:

  • Sagence AI develops in-memory analog chips to optimize AI.
  • Analog chips are more efficient than GPUs but present programming and accuracy challenges.
  • The startup has already attracted significant investment and aims to launch its chips in 2025.
  • Growing energy demands for AI may necessitate the adoption of more sustainable solutions.

In the ever-changing semiconductor landscape, a new player is looking to challenge the status quo. Sagence AI, a startup founded by Vishal Sarin, is focusing on a technology that could rewrite the rules of computing power in AI: analog chips. These devices, which differ substantially from the traditional graphics processing units (GPUs) that currently dominate the AI market, could dramatically reduce power consumption and improve performance, challenging one of the major limitations of modern GPUs.

Today, GPUs, designed to handle huge workloads in data centers, are notoriously power-hungry. According to Goldman Sachs estimates, the growing demand for AI could lead to a 160 percent increase in power consumption by 2030. This energy impact is one reason why many experts, including Sarin, believe the current GPU development model is not sustainable in the long run. His vision is clear: to create a solution that, while maintaining high performance, minimizes the energy impact, thus solving one of the major problems in the AI industry.

Sarin, with long experience in circuit design, founded Sagence AI (formerly known as Analog Inference) with the goal of developing analog chips that can run AI models more efficiently. Unlike digital chips, which operate with binary values (0 and 1), analog chips use a continuous range of values to represent data, a feature that offers significant advantages in density and computational speed. In fact, these chips are designed to operate directly “in-memory,” which means they do not have to continuously transfer data between memory and processor, a process that in GPUs can cause bottlenecks and slowdowns. In an age when performance needs to be ever higher, this solution could make all the difference.

Despite the advantages, analog technology also presents some difficulties. Indeed, analog chips are more complex to fabricate with the precision required for modern applications, and programming these devices is less straightforward than digital approaches. However, Sarin believes that analog chips should not completely replace GPUs, but integrate them, for example, in application scenarios that require high performance and low power consumption, such as in servers or mobile devices.

Sagence has already attracted significant funding, including from such illustrious names as Vinod Khosla and TDK Ventures, raising $58 million since 2018. The startup plans to bring its chips to market in 2025, a key step in establishing itself as a competitive player in an industry already dominated by giants such as Nvidia, whose GPU ecosystem is closely tied to most of the existing AI infrastructure. The challenges are many: not only is large-scale analog chip production expensive, but competition is fierce, and convincing customers to migrate from an established system could prove challenging. In this context, Sagence will have to concretely demonstrate that its chips are more efficient than current solutions, both in terms of power consumption and performance, to gain a share of the market.

The timing may be favorable, however. Although 2023 has not been a bright year for semiconductor startups, funding in this sector has increased, a sign of renewed investor interest. Sagence, with its innovative proposition and a steadily growing team, has the potential to seize this opportunity and enter the market with a product that could be critical to the future of AI.

Chip manufacturing, in any case, remains an expensive and complex challenge, made even more difficult by geopolitical tensions and protectionist policies that are changing the global semiconductor landscape.

It will be interesting to see how Sagence navigates these choppy waters and whether it can demonstrate that its analog approach can truly make a difference, even in a market dominated by highly established digital solutions.