Status
Available
Last Round Valuation
$50 Billion
Share Price
$50.00
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Lightmatter is delivering a new paradigm in semiconductor chip architecture and the next transition for large-scale computing. The company has developed photonic processors that are faster, more efficient and cooler than any conventional processors in existence today and is answering the call for increased compute speed, low energy density, and reduced chip heating. Lightmatter is set to enable the continued rapid growth of artificial intelligence computing while minimizing its well-known and growing impact on the environment.
Artificial intelligence (AI) is prevalent in daily life, powering products ranging from online advertising to intelligent personal assistants. The AI models behind these products are “trained” using large datasets: a process that requires a lot of time and energy with existing computer processors. As AI algorithms continue to develop, current technologies will struggle to keep up with the increasing demand for computing power. Faster and more energy efficient computers will be essential. This is where Lightmatter comes in.
Lightmatter’s products essentially do two things: make computing faster and more energy-efficient — requirements critical to supporting the generative AI boom.
Lightmatter's chips execute certain complex calculations crucial to machine learning with remarkable speed—literally in a flash. Unlike traditional chips that employ charge, logic gates, and transistors to store and manipulate data, Lightmatter's chips utilize photonic circuits. These circuits carry out calculations by altering the path of light. While this concept has been around for some time, it's only recently that scaling it for practical and highly valuable purposes has been achieved.
Through patented technology developed at MIT, Lightmatter has created a silicon chip that uses light signals, rather than electrical signals, for processing. This chip was used to demonstrate a new form of AI processing that promises orders of magnitude performance improvements over what’s feasible using existing technologies.
“For decades, electronic computers have been at the foundation of the computational progress that has ultimately enabled the AI revolution, but AI algorithms have a voracious appetite for computational power,” said Nick Harris, CEO of Lightmatter. “AI is really in its infancy, and to move forward, new enabling technologies are required. At Lightmatter, we are augmenting electronic computers with photonics to power a fundamentally new kind of computer that is efficient enough to propel the next generation of AI.”
Lightmatter’s suite of products consists of Envise, Idiom, and Passage, providing a full stack of hardware and software solutions to realize the benefits of photonic compute and interconnect technologies.
Envise is the world’s first general-purpose photonic artificial intelligence (AI) accelerator. Inference, which is synonymous with the deployment of AI models, represents the fastest-growing, largest energy footprint endeavor in the AI computing space. Envise enables ultra-high performance inference on the world’s most advanced AI models (GPT-3, Megatron) as well as staple neural networks (BERT-Large, DLRM, ResNet-50).
Idiom interfaces with standard deep learning frameworks and model exchange formats, while providing the transformations and tools required by deep learning model authors and deployers.
To enable customers to extract maximum performance from Envise, Lightmatter added a software stack: Idiom. Idiom compiles and executes neural network models on Envise and offers tools for debug, profiling and model optimization. Idiom also enables automatic blade detection — enabling rapid deployment of large AI models across entire server racks.
Passage is a new, wafer-scale programmable photonic interconnect through which computer chips communicate at unprecedented speed. Passage, an 8-inch by 8-inch computer chip, integrates transistors and photonics (including lasers, modulators, and photodetectors). Heterogeneous computer chips are integrated with the platform using standard chip-on-wafer packaging technology.
Lightmatter believes Passage will enable a world where configurable-topology supercomputing systems are built on a single platform that takes advantage of the benefits of optics, without the packaging cost and complexity, enabling a 100Tbps chip-to-chip interconnect.
Lightmatter claims its technology delivers a performance that is 5 times faster than an Nvidia A100 unit when running large transformer models like BERT, all while consuming merely 15% of the energy. This proposition is particularly enticing for AI behemoths like Google and Amazon, who are always in pursuit of higher computing power while grappling with hefty energy bills. The blend of enhanced performance and reduced energy costs makes Lightmatter's platform an overwhelmingly attractive option for these industry giants.
According to TechCrunch, Lightmatter’s products are in beta testing, and mass production is planned for 2024, presumably, at which point Lightmatter will have enough feedback and maturity to deploy in data centers.
Lightmatter’s product helps companies reduce their data center energy consumption costs by around 80% when training and running machine-learning models, compared with providers like Nvidia, AMD and Intel, whose chips move data over electrical wires. Lightmatter is also aiming to get companies such as Nvidia, AMD, and Intel to license its technology for use in their own chips.
In July 2024, Nvidia's Vice President Simona Jankowski is becoming chief financial officer at Lightmatter, bringing her extensive experience in investor relations and strategic finance. Jankowski said that she hadn’t been looking to departnNvidian, one of the world’s most valuable companies, until Lightmatter came along. “It’s just about the only opportunity that I would have left Nvidia for,” she said in an interview.
In July 2024, according to CEO Nick Harris, Lightmatter has “incredible market traction” and its products will soon make an appearance in some of the world’s largest data centers. It’s close to having enough money coming in to be self-sustaining but will take advantage of available capital to prioritize growth.
In October 2024, Lighmatter announced it had raised $400 million in a Series D financing, led by new investor T. Rowe Price and existing investors such as GV (Google Ventures). nThe funding will support the rollout of a device called Passage, which allows various types of computer chips to share data optically. While CEO Nick Harris declined to name specific customers, he has previously mentioned that Lightmatter's clients include some of the largest chipmakers and cloud service providers.
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Key Investors
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Size of Market
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Market Position
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Industry
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Primary Vertical
Artificial Intelligence
Employees
500
Mosaic Score
840
Money
760
Momentum
850
Management
760
Market
960
What is a Mosaic Score?
| Name | Work History | Title | Status |
|---|---|---|---|
| John Smith | Aenean, quam eu, diam dignissim | Chief Executive Officer | Current |
| John Smith | Aenean, quam eu, diam dignissim | Chief Executive Officer | Current |
| John Smith | Aenean, quam eu, diam dignissim | Chief Executive Officer | Current |
| John Smith | Aenean, quam eu, diam dignissim | Chief Executive Officer | Current |
Last Round
Sept. 2019, Series B1
Valuation Post-Money
$400.2M
Amount Raised
$2.5M
Total Funds Raised
$75.2M
Implied Valuation
$84M
| Date | Round | Amount | Valuation | Investors |
|---|---|---|---|---|
| MM/DD/YYYY | Growth Equity | $1M | $2.8B | Name goes here |
| MM/DD/YYYY | Growth Equity | $1M | $2.8B | Name goes here |
| MM/DD/YYYY | Growth Equity | $1M | $2.8B | Name goes here |
| MM/DD/YYYY | Growth Equity | $1M | $2.8B | Name goes here |
| Company | Valued | Revenue |
|---|---|---|
|
Coinbase San Francisco, CA |
$2.8B | $1.3B |
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Coinbase San Francisco, CA |
$2.8B | $1.3B |
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Coinbase San Francisco, CA |
$2.8B | $1.3B |
