High Bit

In this episode, Brett Gibson talks with Lucas Young, cofounder and CEO of Deepnight about how they’re building AI-powered night vision that helps the military, law enforcement, and first responders see in near-total darkness. Deepnight combines AI with commodity digital sensors — the same kind used in smartphones — to replace expensive analog night-vision hardware that costs over $30,000 per unit and hasn’t kept pace with modern imaging technology.

Lucas explains how night vision has worked since World War II, why analog image intensifiers hit a ceiling, how smartphone photography paved the way for this breakthrough, and what it takes to bring military-grade low-light imaging into the field.

Chapters

(00:00) Why Night Vision Is Still Mostly Analog

(00:39) Deepnight’s Breakthrough: AI That Sees in the Dark

(01:44) How Their AI Reconstructs *Real* Scenes

(03:58) Lucas’s Path: Google Pixel → YC Founder

(05:26) Why Modern Cameras Rely on Software

(09:12) The Rise of AI-Enhanced Photography

(11:45) The Insight: AI Could Beat $30K Night-Vision Goggles

(13:03) How Traditional Night-Vision Tubes Work

(14:10) Starting Deepnight Without Knowing If It Would Work

(15:11) Early Prototypes: Offline → Real-Time Night Vision

(16:15) The Physics Challenge: Seeing in Moonless Starlight

(19:12) Running This on Smartphone-Class Chips

(22:27) Building a Custom Neural Network for Night Vision

(28:43) Can Cheap $50 Sensors Match Military Gear?

(48:06) What’s Next: Real Soldiers Using AI Night Vision

Subscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.

Brett Gibson sits down with cofounders Max Prilutskiy (CEO) and Veronica Prilutskaya (CPO) of Lingo.dev to talk about making every product multilingual—so teams “just keep shipping” and don’t have to worry about localization and translations at scale. Lingo.dev helps product teams develop multilingual user interfaces, uses LLMs to produce perfect translations, and automates localization end to end.

Chapters:

(00:00) The Future of Coding and “Vibe Coding”

(00:50) What Lingo.dev Does

(01:24) Built at a Hackathon

(04:59) From Google Translate to LLMs - for more context

(06:20) “Perfect Translation” - objective AI precision + subjective brand tone + cultural nuance

(11:13) Automating Translations with Pull Requests

(13:41) The New Compiler - making apps multilingual without refactoring

(17:42) How “Vibe Coding” Changed Software Development

(19:10) Write Once, Click Save, See It in Any Language

(37:29) AI Impact: “The Future of Coding” in Practice

Subscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.

Follow Lingo.dev, Max and Veronica on X for more:

https://x.com/lingodotdev

https://x.com/MaxPrilutskiy

https://x.com/vrcprl

Orbital Operations is building high-thrust, cryogenic spacecraft designed to move freely in orbit—reshaping how we think about mobility, defense, and logistics in space.

Cofounder & CEO Benjamin Schleuniger joins Initialized Managing Partner Brett Gibson on High Bit to talk about the next generation of spacecraft that will move, refuel, and think for themselves:

• Why satellites need to move — the rise of in-space mobility
• How cryogenic propulsion unlocks long-duration missions
• The refrigeration-cycle tech enabling propellant storage in orbit
• Military and logistics use cases driving demand
• Refueling with water to extend mission life
• The third age of space mobility and what it enables
• How AI and autonomy will power future spacecraft

Chapters

(00:00) Intro

(01:10) What Orbital Operations is building and why it matters

(01:26) Ben’s path: NASA → SpaceX → Relativity

(02:17) Why satellites need to move now

(04:30) Basics of propulsion and why mobility is limited in space

(05:55) Satellites vs rockets: propellant tradeoffs

(08:30) Choosing cryogenic propellants and rethinking storage

(10:15) The refrigeration-cycle system that makes it possible

(17:00) Thermal management and engineering challenges in orbit

(22:30) Military and logistics use cases for in-space mobility

(25:40) Refueling with water and the future of orbital logistics

(27:50) Engineering vs. business challenges of building in space

(30:50) Scaling missions and the path to commercial viability

(33:30) The third age of space mobility and what comes next

(35:20) AI tools in aerospace and autonomy in orbit

Subscribe to High Bit for more conversations with technical founders building what’s next, hosted by Brett Gibson of Initialized Capital.

Follow Orbital Operations and Benjamin Schleuniger on X for more:

@OrbitalOps_

@BenSchleuniger

“Robots are the only way my business survives, but it’s not viable for me.”

Formic founder and CEO Saman Farid joins Brett Gibson, managing partner at Initialized to unpack why that mindset keeps factories from adopting automation and how Formic closes the gap.

They cover: de-risking with financing, productizing complete robot work cells, and running fleets with teleoperation, intelligent error recovery, and careful staging to hit factory-grade uptime.

You’ll hear why palletizing is the ideal first beachhead, how the team cut deployment costs roughly in half, and why they say no to one-off requests until they can be productized.

Saman also shares how the company resists “fun” engineering in favor of scale, injects controlled chaos into his company, uses daily 8 a.m. meetings for problem solving, and bridges the culture gap between the manufacturing and software industries.

Subscribe for more builder-level deep dives from High Bit.

Follow Formic and Saman for more:

Formic: https://x.com/goformic

Saman: https://x.com/samanfarid

Content

(00:00) “It’s not viable for me”—closing the adoption gap

(00:44) What Formic does & where robots work today

(02:24) Engineer → VC → founder: why start Formic

(04:38) Adoption vs flashy demos. Solve one task well

(05:47) De-risking with financing; manual first, then automate

(08:23) The playbook: scope, build modules, deploy, operate1

(10:36) Work cells, not just arms

(13:38) 99.9% uptime15:01 Why palletizing was the first beachhead

(16:49) Cutting costs per deployment

(18:08) Saying “no” & expanding scope the right way

(21:15) Resisting “fun” engineering to serve more factories

(22:07) Injecting chaos into your company

(23:34) Daily 8am to crack hard problems

(25:40) Culture clash: manufacturing × software

(27:24) Evaluating new robots, regional rollouts

(31:24) Where AI helps across the org

(37:11) What’s next: more robots, more tasks, more factories

Daksh Gupta, co-founder and CEO of Greptile, joins Brett Gibson on High Bit and explains why human code review is essentially "security theater" and how Greptile uses AI to catch bugs by understanding entire codebases.

He dives into why code generation and code review must stay separate, the surprising challenge of teaching AI what's a nitpick versus a severe issue, and how intelligence becoming "abundant and nearly free" is reshaping software practices. Plus: why some companies will be left behind if they don't adopt AI tools, what happens when human "taste" becomes the final bottleneck, and whether code legibility will matter in an AI-dominated future.

Follow Greptile and Dkash for more:

@greptileai

@dakshgup

Chapters

(00:00) About Greptile, the evolution to specialized bug detection

(03:00) Humans are bad at code review. Why AI works

(06:00) Intelligence becoming abundant

(07:20) Sneaky disruption - what people are looking for vs what they need

(10:50) Code gen and verification are different problems

(14:00) Code gen and code review should be separate

(17:15) Getting LLMs to understand code

(24:15) Claude 4's tool-using capabilities changed their approach

(25:00) Architecture: from flowcharts to agent tools

(27:30) What’s hard about code review - what’s a nitpcik vs. a severe issue

(31:00) What was the “High Bit”

(35:06) Whether code legibility will matter in an AI world

(37:25) Why Terraform and infrastructure code is particularly difficult

(43:25) Re-architecting systems to be AI-friendly vs. adapting AI to messy reality

(45:55) Human "taste" as the final bottleneck

(47:14) Rick Rubin level taste in software

(47:55) Human appetite for change - kitchen exhausts for stoves

(50:50) Working with companies that use AI to generate code

AyJay Lasater, cofounder and CTO of Albedo, joins Brett Gibson on High Bit to talk about the challenge of building satellites for one of the toughest places to operate in space: very low Earth orbit (VLEO).

He shares how the idea took shape, the importance of avoiding fear-based calls, why they decided to bring key systems in-house, and the physics-driven design choices that shaped their approach.

Along the way, AyJay walks through the mirror mishap that could have delayed them a year, the supply-chain chess it took to recover in just two weeks, and what it means to take on a mission where there’s no playbook to follow.

Follow Albedo on X for more:

@Albedo

Chapters

(00:00) Knowing Everything – Why total system knowledge is the only way to do something that’s never been done

(00:59) Albedo’s Mission – Getting drone-quality imaging from space

(04:21) The Spark – From Lockheed to startup. How a single tweet ignited the VLEO idea

(09:29) Inside VLEO – Why it’s one of space’s toughest environments

(14:46) Breaking Down the Impossible – Applying first principles to the hardest orbit

(18:17) Ditching the Bullet – Rethinking design from physics up

(21:09) Make vs. Buy – The decision to take control in-house

(28:55) No Fear – Avoiding fear-based calls when stakes are high

(35:37) The Mirror Crisis – Saving a year’s work in two weeks

(47:11) 4D Supply Chain Chess – Creative problem-solving under pressure

(50:38) The Fun and Stress of Knowing It All – Why no detail can be left to chance

(51:32) What’s Next – Albedo’s path to VLEO and its first 10 centimeter images

Amir Elaguizy, cofounder and CEO of Poker Skill, joins Brett Gibson on High Bit for a look inside the mind of someone who’s been all in on AI long before it was everywhere. He explains what’s possible when you’re not just using AI tools, but constantly learning, testing, and pushing them to their limits, and he shares how he’s used AI to build his startups.

Follow Amir and Poker Skill for more:

@amirpc

@PlayPokerSkill

Chapters:

(00:00) Introduction

(01:36) Amir's background and passion for AI

(06:00) How the landscape is changing

(17:00) How Amir uses AI day-to-day

(30:33) Why AI isn’t a “do my job for me” button

(34:44) Transforming a company into a lean, AI-driven machine

(39:09) Amir’s newest venture: Poker Skill

(46:47) Picking the right tools

(51:38) Closing Remarks

Brett Gibson hosts Sol’s Ben Chelf and John Boiles on the "High Bit" podcast to discuss their groundbreaking work on the Sol Reader, the world’s first wearable e-reader. They dive into the unique engineering challenges of integrating e-ink technology into a head-mounted format, the intricate development process of creating their own e-ink driver, and the importance of optimizing for user comfort and the reading experience.

Chapters:

00:00 - Introduction

02:16 - The Birth of Sol Reader: From Idea to Prototype
05:19 - Comparing Sol Reader to Other Wearable Technologies
09:59 - Technical Challenges and Innovations in E-Ink Displays
20:30 - Manufacturing and Quality Control Processes
23:12 - Software Development and Optimization
33:40 - Future Plans

Vince Chu, cofounder of HomeVision, joins the "High Bit" podcast to discuss how his team is automating real estate valuations at scale. From overcoming technical challenges to scaling AI-powered underwriting, Vince explains how HomeVision is changing the game for both lenders and appraisers.

Our managing partner, Brett Gibson, spoke with Playground AI founder Suhail Doshi about advancements in AI-driven image generation and their new Playground v3 image foundation model. Suhail shared Playground’s mission to make graphic design more accessible, enabling users to create items such as T-shirts, logos, social media posts, and even memes. They discussed the gap between language and image models, as well as the underinvestment in AI for images.

Check out the new Playground here: https://playground.com/design

Playground’s white paper introducing their image foundation model Playground v3 here: https://arxiv.org/abs/2409.10695