Harnessing photonics to lead the next wave of advancements in AI computation.
“Semiconductors are arguably humanity’s greatest achievement to date,” says Jimmy Goodrich, vice president of global policy at the Semiconductor Industry Association. Over the last half century, what has fueled the digital semiconductors’ pervasiveness in society is described by Moore’s Law, built on the observation that the number of transistors on a microchip doubles every two years, and the cost per transistor is halved.
AI, at the cusp of its own revolutionary impact to humanity, is driving an unprecedented demand for computation right at the time that the physics of digital semiconductors is failing to continue to support year over year speed ups that follow Moore’s law. Transistor scaling has hit its limits and AI accelerator companies are struggling to keep pace with demands, particularly in “edge” applications that require greater power and cost efficiency. Domain-specific architectures targeted to AI workloads can make up for some of the slowdown in transistor advances but that approach also has its limits.
Inorganic Intelligence is breaking the digital semiconductor mold by integrating photonics into accelerators for AI workloads, thereby enabling step-change advancements in AI computation. Harnessing light to perform data-parallel calculations is many orders-of-magnitude faster, more power efficient, and lower cost than in traditional semiconductors. Photonic computing redefines what is possible in the field of artificial intelligence.
Photonics has been primed for use in computation through decades of advances of in-silicon photonics design and fabrication driven by the world of network communication. Dave Lazovsky, Inorganic Intelligence CEO, has a deep understanding of the state-of-the art photonics devices and semiconductor technology. Through his research during his time at Khosla Ventures, he connected with Professor Nikos Pleros of Aristotle University of Thessaloniki to establish the design of the company’s proprietary photonic neural network (PNN). Devices in Dr Pleros’ team’s novel architecture and the technologies and processes used for the integration of the PNN are proven in volume production devices used in other applications.
Inorganic Intelligence’s founders understand that there are three pillars for a successful AI architecture. It must:
- Solve real customer problems
- Be designed for reliability, manufacturability, and low-cost from the start
- Have a robust developer and deployer ecosystem that integrates seamlessly with customers’ existing flows
Inorganic Intelligence has assembled a technical leadership team to deliver on each of these requirements.
Inorganic Intelligence CTO Phil Winterbottom brings a unique combination of technical depth across all disciplines required to architect a photonics-based accelerator. Winterbottom’s experience and expertise span photonics, AI / machine learning hardware and software, as well as ASIC system architectures. Following his 10+ year tenure at Bell Labs, he led the technical teams at two startups, Entrisphere (acquired by Ericsson) and Gainspeed (acquired by Nokia.) He was most recently VP of Engineering at an optical AI computing startup.
Preet Virk, the company’s COO, brings deep technical expertise and experience managing engineering teams in the semiconductor and data communications sectors. He previously served as SVP at MACOM and Mindspeed Technologies where he drove the initial adoption of electro-optical solutions enabling 100G transceiver deployment data centers. He also co-packaged DSP solutions with photonics for the first 100G single lambda transceivers for data centers.
Michelle Tomasko leads Inorganic Intelligence’s software effort, relying on her 20 years of technical leadership experience in the silicon industry as the former the VP of Engineering at Groq and having worked for other leading technology companies including NVIDIA, Google Consumer HW, and Transmeta. At NVIDIA, she drove all aspects of software for the leading GPU architectures. Tomasko delivered Google’s first machine learning/image processing accelerator system on a chip, the Pixel Visual Core for the Pixel 2 phone.
Uniting the team is Dave Lazovsky, who previously managed over $1B in semiconductor manufacturing equipment business at Applied Materials before founding his first startup, Intermolecular and leading it through its IPO.
As Lazovsky and his team note, humanity has only scratched the surface of AI’s potential. The digital domain has opened the door for AI but is not able to continue to deliver the same level of performance gains that has put the computational power of supercomputers of yesterday into the smartphones of today. Photonics promises to be the technology to usher in the next era of rapid growth; Inorganic Intelligence has the know-how and the team to take the industry there.