Learnings from founding a Computer Vision Startup: Chapter 1 & 2: Why a startup?
3 likes1,230 views
1. The document discusses the learnings from founding a computer vision startup. It emphasizes that the original business idea is less important than executing on that idea. It recommends doing basic homework on competition and timing, and finding a core founding team with complementary skills to build a prototype. 2. "Copying" other ideas is acceptable, but copying existing products may be risky depending on local restrictions, user dynamics, and whether there are key advantages like a huge technological lead. The document shares how the author's startups in computer vision were founded, including building on early object recognition work and having working systems for face reconstruction and search.
Learnings from founding a Computer Vision Startup: Chapter 1 & 2: Why a startup?
- 1. 1. Why a startup
- 2. Make a dent in Learnings from founding a Computer Vision Startup the universe Build something that someone else thinks is important
- 3. Learnings from founding a Computer Vision Startup Be your own boss Take control and responsibility for your living
- 4. Learnings from founding a Computer Vision Startup Get a hands-on MBA
- 5. 2. The Business idea
- 6. Learnings from founding a Computer Vision Startup The original idea is an almost negligible part of a business Ideas are cheap, execution is hard! “I had the idea for eBay. If only I had acted on it, I’d be a billionaire!” -ReWork Flickr:IvanClow
- 7. so you had the idea ... ... what now?
- 8. Learnings from founding a Computer Vision Startup 1) Do basic homework on competition www.crunchbase.com
- 9. Learnings from founding a Computer Vision Startup 2) Find a core founders team ... To build a prototype With complementary skills (more on team later)
- 10. Learnings from founding a Computer Vision Startup 3) Check timing Timing is crucial External factors (market, competition, ...) A lot more crucial than you would think! http://en.wikipedia.org/wiki/Outliers_(book)
- 11. and just get started
- 12. Learnings from founding a Computer Vision Startup In the beginning Maybe don’t quit your job right away, spend lunch, evenings, weekends with the project Being grad student is ideal, especially if project related to your work
- 13. on copying ideas
- 14. Learnings from founding a Computer Vision Startup Should you copy ideas? http://techcrunch.com/2007/05/14/web-2-in-germany-copy-paste-innovation-or-more/
- 15. Learnings from founding a Computer Vision Startup “Copying” ideas is ok copying products may be risky Flickr:lazzarello
- 16. Learnings from founding a Computer Vision Startup When copying products may work Local restrictions to product (banking, accounting, commerce) Local user group (language!) Timing Huge technological advantage User dynamics (Twitter vs. Jaiku, “nightclubs”) Or some other key advantage...
- 17. How we did it
- 18. Learnings from founding a Computer Vision Startup How we did it: idea for kooaba I was a bit interested in QR codes originally (2004) Let try some students object recognition on mobile phones (2005) Founded company with Herbert Bay in 2006
- 19. Learnings from founding a Computer Vision Startup How we did it: idea for Polar Rose Had some 3D face reconstruction results, wanted to see if that could do face recognition Started company by myself, built working system First browser plugin & search idea born (chosen among many options at the time)
- 20. Q&A
- 21. Learnings from founding a Computer Vision Startup Resources Crunchbase www.crunchbase.com Outliers (on timing as success factor) http://en.wikipedia.org/wiki/Outliers_(book)