Pat Gelsinger-backed startup PicoJool raises $27.5M to boost bandwidth for AI clusters - SiliconANGLE
Pat Gelsinger-backed startup PicoJool raises $27.5M to boost bandwidth for AI clusters - SiliconANGLE
摘要: UPDATED 08:00 EDT / SEPTEMBER 24 2026
Pat Gelsinger-backed startup PicoJool raises $27.5M to boost bandwidth for AI clusters
Mike Wheatle
正文
UPDATED 08:00 EDT / SEPTEMBER 24 2026
Pat Gelsinger-backed startup PicoJool raises $27.5M to boost bandwidth for AI clusters
Mike Wheatley
A startup called
PicoJool
that’s backed by former Intel Corp. Chief Executive Pat Gelsinger says it’s ready to help ease the strain on artificial intelligence data centers after raising $27.5 million in early-stage funding today.
The Series A round was led by Socratic Partners and saw participation from Hudson River Trading. It brings the company’s total amount raised to $39.5 million. It follows an earlier $12 million
seed funding round
last November that was led by Gelsinger’s venture capital firm Playground Global.
PicoJool is trying to pioneer a technology called
Vertical Cavity Surface Emitting Laser
or VCSEL, which is a kind of semiconductor laser diode. It enables data to be sent via light signals through optical cables rather than traditional wire, enabling much faster data center communications. The startup, which has developed a number of optical chips and modules based on the technology, says they can drastically improve the performance and energy efficiency of large AI chip clusters.
There’s a growing appetite among data center operators for this kind of rapid and efficient connectivity. The more powerful AI models become, the bigger the clusters of graphics processing units and other accelerators are needed to run them. These days, the world’s largest enterprises operate clusters containing hundreds, sometimes even thousands of AI processors, which are constantly sending data packets back and forth to one another so they can work in unison to power AI workloads.
As a result, data centers are dealing with a tsunami of data, and it’s putting enormous strain on the traditional copper wire interconnects used to link all of those chips together. They simply cannot keep up with the bandwidth demands of the largest AI clusters, and they consume vast amounts of energy too, driving up the cost of runni