Tag: Quadric

The hum of servers used to be the sound of AI. Now, it’s the quiet whir of a chip, nestled inside a device. At least, that’s the bet Quadric is making. The company, aiming to help companies and governments build programmable on-device AI chips, is riding the wave of a significant shift in the artificial intelligence landscape. The move away from cloud-based AI to on-device inference is gaining momentum, and Quadric seems well-positioned to capitalize.

Earlier this week, during a call with investors, a Quadric spokesperson highlighted their focus on fast-changing models. This means the ability to run updated AI algorithms locally, without constantly pinging the cloud. It’s a critical advantage in fields like edge computing, robotics, and even national security, where latency and data privacy are paramount.

The technical challenges are significant. On-device AI demands powerful, yet energy-efficient, processing. Traditional GPUs, designed for the cloud, often fall short. Quadric’s approach involves developing specialized chips. These chips are designed to handle the complex computations needed for AI models right on the device. This is a bit of a departure from the conventional wisdom of recent years.

“The market is definitely moving in this direction,” said John Thompson, a senior analyst at Forrester, in a recent interview. “We’re seeing increased demand for low-latency, secure AI solutions, and on-device inference is a key enabler.” The analyst also noted a shift in procurement priorities in key markets, especially in light of export controls and domestic supply chain policies.

Consider the details: Quadric’s roadmap includes the M100 and M300 chips, with projected releases in 2026 and 2027, respectively. The company is targeting a performance increase of up to 5x compared to existing solutions, as per internal projections. But the true test will be the real world, and how well these chips can handle the dynamic demands of AI models.

Meanwhile, the supply chain remains a critical factor. The availability of advanced manufacturing processes, particularly those offered by TSMC, could be a bottleneck. The U.S. export rules and domestic procurement policies also play a significant role. It’s a complex equation, where innovation meets the realities of global politics and manufacturing capacity.

Still, the shift towards on-device AI is clear. Quadric is among the companies poised to benefit. It’s a space that’s going to be interesting to watch as the year progresses.

The hum of servers, usually a constant drone, seemed to quiet slightly, or maybe that’s how the supply shock reads from here. Inside Quadric’s engineering lab, the team was running thermal tests on the new M300 chip, slated for release in early 2027, according to their roadmap. The goal: to enable AI processing directly on devices, bypassing the need for constant cloud connectivity.

It’s a strategic pivot, as the industry begins to recognize the limitations of cloud-dependent AI. Quadric, founded with the aim of helping companies and governments, sees the potential in programmable on-device AI chips. They’re designed to run fast-changing models locally. This means quicker response times and enhanced data privacy, key selling points in an increasingly security-conscious world.

“We’re seeing a significant shift,” said analyst Maria Chen from Forrester, during a recent industry briefing. “The demand for on-device inference is surging, and companies like Quadric are well-positioned to capitalize. We project the market to reach $15 billion by 2028.” That’s a bold number, considering the sector was still nascent just a few years ago. But the need is there: think of self-driving cars needing instant reactions, or edge devices in remote locations with limited bandwidth.

The technical challenges are significant. Building these chips requires advanced manufacturing, and the global supply chain, still recovering from recent disruptions, adds another layer of complexity. Export controls also play a major role. Quadric, like many in the industry, has to navigate the complex web of US and international regulations. The company is likely looking at options for domestic procurement policies in China, which could influence their strategy.

Earlier today, the team was reviewing the performance metrics for the M100, which is already in use. The focus now is on the M300, which promises a substantial performance leap. The engineers were huddled around monitors, analyzing the data. The atmosphere was focused, the air thick with anticipation. The M300 is expected to offer a 4x performance increase over the M100, according to internal projections.

The shift to on-device AI is more than a technological evolution; it’s a strategic move. It gives companies and governments greater control over their data and operations. Quadric is, in a way, at the forefront of this transformation. Their success will depend on their ability to deliver on their promises, navigate the complex regulatory landscape, and, of course, stay ahead of the competition.