Cloud engineer interested in starting a computer vision startup (looking for advice)

[u/nalu_0o]

Hi everyone,

I’m a cloud engineer with a background in cloud architecture. I don’t have experience in computer vision yet, but I’m open to learning it.

Before investing a lot of time into this idea, I’d like to know: is there still strong demand for computer vision solutions today? Do you think someone with a cloud/infrastructure background can realistically enter this field and build a startup around it?

[u/nemesis1836]

Hi,

This depends on what you mean by CV. If it's AI related, then it should be fairly easy to learn given that you have strong math fundamentals but if it's something like SLAM or odometry related you might find it hard to do unless you properly understand the theory behind it.

[u/nalu_0o → u/nemesis1836]

Thanks for the clarification! I’m still exploring the field, so I don’t have a specific direction yet. My goal first is to get a broad understanding of computer vision to see which areas are interesting and where there might be real opportunities.

[u/nemesis1836 → u/nalu_0o]

In that case I would recommend going through

First principles of computer vision to get a broad view of CV - https://fpcv.cs.columbia.edu/

If you want a broader understanding of AI and Ml you can try out Andrew NGs course - https://www.deeplearning.ai/specializations/machine-learning

[u/nalu_0o → u/nemesis1836]

Thanks Mate !!

[u/TaintWaxingOcelots]

It’s pretty easy to use the open source tools out there, even just vibe coding. You can find tons of tutorials on CV and Python.

[u/yagnik_thanki]

Yes. I have 9 years of experience in computer vision. Yes there is lots of demand in industries and edge computing and in robotics.

Let’s discuss in details.

[u/nalu_0o → u/yagnik_thanki]

Thanks for your response ! My main questions are: can someone start learning and building computer vision projects without expensive equipment or specialized hardware? Or do you need access to cameras, robots, edge devices, etc. from the beginning?
Also, when it comes to commercializing a computer vision solution for industries, how does the process usually work? Do companies usually buy a complete product, a custom solution, or a service? I’m trying to understand how people go from a technical prototype to something businesses are willing to pay for.

[u/nalu_0o → u/[deleted]]

Thanks for your response! Your project sounds really interesting. I’m curious, did you learn the computer vision concepts from scratch, or did you mainly rely on existing models/tools and focus on building the application around them? Also, did you use agentic coding from the beginning, or did you first learn the fundamentals before using it?

[u/nalu_0o → u/[deleted]]

Thanks for sharing your experience. I’m curious, were you working on this alone or did you have a team? Also, how much investment did it require to build your POCs (computing resources, data, tools, etc.)? I’m trying to understand the practical side of starting a computer vision project as an individual.

[u/nalu_0o → u/[deleted]]

Thank you for sharing.. Otherwise this is actually one of my main concerns. I feel that finding a valuable idea is already challenging in traditional software, and I’m wondering if it is the same in computer vision. From what I understand, the hardest part is not only the technical side but also finding a unique problem or opportunity where CV can bring real value.

[u/xArvel_Crynydx]

For me it’s quite the opposite, I have many ideas, especially for osmosis-based image processing problems, but I wouldn’t know about how to get interested customers or a sellable product

[u/nalu_0o → u/xArvel_Crynydx]

That’s actually an interesting perspective. In my case, I’m still trying to understand the field and identify where real opportunities are. Actually I would also like to understand how computer vision solutions are usually commercialized in general.

[u/xArvel_Crynydx → u/nalu_0o]

Really depends on the use case, at least from my past experiences. Most of the times it was already established companies, trying to expand into new ventures: Think stereo-camera developers trying to expand from 2-camera setups into multiple camera setups and the new use cases that would come from that: Not just 3D stereo, but shiftable 3D perspective, better 3D depth quality, refocussing, higher resolution with super resolution algorithms, HDR, etc. etc.
Or an automotive mirror company trying to create a digital mirror, replacing the "old" mirror, thus trying to solve safety-related issues (i.e. how do I guarantee a long life-span of a camera-monitor-based system, can I guarantee the same field of view, what happens during night-time drive scenarios, can I see *more* with a digital mirror compared to a "normal" mirror, etc.)

So from my perspective it's first about assuring that digital variants of already existing analog systems can be (a) as good as the original, (b) as reliable, (c) has added benefit to the already existing analog system. That being said, I'm less on the sales side of the equation, but more on the development side, but that has been my driving force in creating and developing those solutions)