Deepnight, founded by childhood friends Lucas Young and Thomas Li, is revolutionizing night vision technology with AI-powered software, offering a cost-effective alternative to traditional analog systems.
from Google to Night Vision: the Deepnight Story
Table of Contents
- 1. from Google to Night Vision: the Deepnight Story
- 2. The AI breakthrough: “Learning to See in the Dark”
- 3. Winning Over the Military with a Smartphone App
- 4. Investment and Future Applications
- 5. The Future is Radiant for AI-Powered Night Vision
- 6. What other industries or applications coudl benefit from Deepnight’s AI-powered night vision technology?
- 7. Revolutionizing Night Vision: An Interview with Deepnight CEO, Lucas Young
- 8. Archyde: What sparked the initial idea for Deepnight?
- 9. Archyde: How did you approach this challenge technically?
- 10. Archyde: How did you initially connect with the military, your first target market?
- 11. Archyde: Deepnight has secured significant investment. How does your business model work?
- 12. Archyde: Beyond military applications, where else can your technology be deployed?
- 13. Archyde: As AI technology advances, what exciting developments do you anticipate for deepnight and the industry?
- 14. Join the Conversation:
Lucas Young and Thomas li, former software engineers at Google, embarked on a mission to digitize night vision. Young, with a background in computational photography, and Li, specializing in AI and computer vision, identified a critical gap in the market: affordable, high-performance digital night vision.
traditional night vision goggles, using optical lenses and chemical processes, can cost between $13,000 and $30,000, primarily supplied by defense contractors like L3Harris and elbit America. Young recognized the potential to leverage advancements in AI and smartphone camera technology to create a superior, more accessible solution. The U.S. Army’s ongoing efforts to digitize night vision, exemplified by the $22 billion Integrated Visual Augmentation System (IVAS) project now led by Anduril, highlight the meaning of this technological shift.
The AI breakthrough: “Learning to See in the Dark”
Young was inspired by a 2018 scientific paper, Learning to See in the Dark, co-authored by Vladlen koltun, now at Apple. The paper explored using AI for low-light imaging. At the time,on-device AI chips lacked the processing power for real-time viewing at 90 frames per second (fps). However, in 2024, Young realized that advancements in AI accelerators running on system on Chips (SoCs) made it possible. This realization led Young and Li to found Deepnight and join the Y Combinator winter cohort.
Deepnight’s AI model enhances night vision using standard smartphone cameras.
Image Credits: Deepnight
Winning Over the Military with a Smartphone App
Deepnight’s initial target was the military.To gain traction, Young attended an industry event and distributed a white paper outlining his concept: “night vision as a software problem.” This approach resonated with an army colonel, leading to contact with the US army C5ISR Center.
To demonstrate their concept, the founders developed a night vision smartphone app and integrated it into a smartphone-holding VR set. This rudimentary prototype proved remarkably effective.
“The army awarded us a $100,000 contract in February 2024, one month into Y Combinator, based on the proof of concept in a smartphone demo and our whitepapers and presentation,” Young stated.
A subsequent demo in Washington D.C. further solidified their position, leading to additional contracts. Within a year of launching, Deepnight secured approximately $4.6 million in contracts from the federal government, including the U.S. Army and Air Force, and partnerships with companies like Sionyx and SRI International.
Investment and Future Applications
Deepnight’s innovative approach also attracted significant investment. the startup raised $5.5 million in a round led by Initialized Capital, with participation from angel investors including Kulveer Taggar, Brian Shin, and Matthew Bellamy. Notably, Vladlen Koltun, the author of the influential paper that inspired Deepnight, also invested.
Deepnight’s buisness model focuses on software solutions, partnering with hardware manufacturers to integrate their technology into various products. The implications extend far beyond military applications.
“Now we can make everything in the world see in the dark,because it’s just a software program.So that’s automotive, security, drones, maritime like boats, electronics, nav cameras,” Young explains. The reliance on inexpensive, off-the-shelf smartphone cameras further enhances the accessibility and scalability of their technology.
The Future is Radiant for AI-Powered Night Vision
deepnight’s success underscores the transformative potential of AI in revolutionizing traditional technologies. By focusing on software and leveraging readily available hardware, the company has democratized night vision, making it more affordable and accessible for a wide range of applications. As AI technology continues to advance, Deepnight is poised to lead the way in shaping the future of low-light imaging. Explore the possibilities of AI-enhanced night vision and contact Deepnight to learn more about their innovative solutions.
What other industries or applications coudl benefit from Deepnight’s AI-powered night vision technology?
Revolutionizing Night Vision: An Interview with Deepnight CEO, Lucas Young
In an exclusive interview with Archyde, Lucas Young, CEO adn co-founder of Deepnight, shares his insights on transforming night vision technology with AI-powered software.
Archyde: What sparked the initial idea for Deepnight?
Lucas Young: “Thomas Li and I identified a gap in the market. Conventional night vision technologies are expensive,mainly supplied by defense contractors,and rely on outdated methods. We saw an opportunity to leverage advancements in AI and smartphone camera technology to create a more accessible, superior solution.”
Archyde: How did you approach this challenge technically?
Lucas Young: “We drew inspiration from a 2018 scientific paper,’Learning to See in the Dark.’ In 2024, advancements in AI accelerators running on System-on-Chips (SoCs) made real-time processing possible at 90 frames per second. This allowed us to enhance night vision using standard smartphone cameras with our AI-powered software.”
Archyde: How did you initially connect with the military, your first target market?
Lucas Young: “We attended an industry event, distributed a white paper outlining our concept, and the approach resonated with an army colonel. This led to our first contract with the U.S. Army C5ISR Center. we demonstrated our concept using a night vision smartphone app integrated into a VR headset, proving our technology’s potential.”
Archyde: Deepnight has secured significant investment. How does your business model work?
Lucas Young: “Our business model focuses on software solutions. We partner with hardware manufacturers to integrate our technology into their products, making night vision accessible and scalable. This approach has attracted investors like Initialized Capital and angel investors, including Vladlen Koltun, co-author of the paper that inspired Deepnight.
Archyde: Beyond military applications, where else can your technology be deployed?
Lucas Young: “The implications extend far beyond the military. Deepnight’s technology can enhance night vision in automotive, security, drones, maritime, and more. It’s all about making everything in the world see in the dark through an accessible software program.”
Archyde: As AI technology advances, what exciting developments do you anticipate for deepnight and the industry?
lucas young: “AI’s transformative potential in revolutionizing traditional technologies is immense. at Deepnight,we’re constantly exploring new applications and enhancements to our software. The future of low-light imaging is radiant, and we’re thrilled to be at the forefront of this revolution.”
Join the Conversation:
With AI democratizing once niche technologies like night vision, what other areas do you see benefiting from similar shifts? Share your thoughts in the comments below.
