In a groundbreaking move set to redefine the landscape of artificial intelligence (AI) computing, Cerebras Systems CEO Andrew Feldman showcased their latest innovation exclusively on “Taking Stock.” The third-generation wafer-scale engine (WSE-3), unveiled by Feldman, boasts a staggering 4 trillion transistors, making it the largest chip ever seen in the computer industry.

“This is the largest chip in the history of the computer industry,” exclaimed Feldman, presenting the chip to viewers. “Most chips are the size of a postage stamp, but as you can see, this is the size of a dinner plate. The advantage? It enables us to do AI work hundreds of times faster than any alternative product.”

Feldman emphasized the significance of larger chips in AI work, highlighting their ability to process more information and produce answers at unprecedented speeds. These chips are integrated into systems built by Cerebras, which are then interconnected into supercomputers, further amplifying their computational power.

Discussing significant partnerships in the healthcare sector, including collaborations with GlaxoSmithKline, AstraZeneca, and the Mayo Clinic, Feldman underscored the potential of AI to revolutionize healthcare delivery. “The healthcare industry accounts for more than 14% of GDP,” Feldman noted. “Our collaborations aim to accelerate drug research, design, and efficacy assessment, leveraging AI to improve patient outcomes.”

Looking ahead to 2024, Feldman identified AI’s increasingly pervasive role in society as a key trend. “AI is set to play a larger and larger role in our lives,” Feldman remarked, emphasizing the importance of developing faster, more energy-efficient AI computing solutions.

As Cerebras Systems continues to push the boundaries of AI computing, its latest innovation promises to unlock new possibilities across industries, from healthcare to finance and beyond. With the unveiling of their groundbreaking chip, Cerebras Systems, under the leadership of CEO Andrew Feldman, is poised to take charge of redefining the future of AI computing.