- What was the idea behind it?
- Why did it die?
- What did you learn?
A sensor attached to a barbell that uses a gyroscope and accelerometer to analyze your form. I built a prototype using a Raspberry Pi and BerryIMU and it was cool to visualize the data. It was mainly just to learn more about the Raspberry Pi.
An app to map the precise location of routers inside a building. I was learning about writing Android apps and mapping and this was a fun project. By accessing the list of nearby wifi networks and their strength, I could triangulate the location of the router and plot it on the map (visualized as a square that got smaller and smaller as you collected more data).
A to-do list that was triggered by location. After learning about lat/lon and mapping from the previous project I thought it would be cool to geofence tasks. For example, I need to get milk so I put that on the list and when I get within a certain distance of any grocery store, I get a notification. Or if my task is to get cash, I get a notification when I get near to an atm. I used the Foursquare API for the location searching and did some calculation based on speed of travel to give more or less advance notice.
I have dozens of these little projects I've done in the name of learning and eventually parts of them made it into larger projects.
I had well-defined business applications in mind. (I had already deprioritized over ten ideas after discussing with various people including potential customers, and chose to focus on the NLP ones.)
I was ahead of the times in vision, and right in technical direction (deep neural networks plus more). But I was not confident and not comfortable in raising money. Some friends were willing to give seed funding, after seeing a startup in a domain I had deprioritized emerge with a successful exit. I did not accept the offer.
There was one person helping me as a technical co-founder. I needed a business person to join as a co-founder, however, no one I wanted from my circles was willing to take the plunge.
A friend casually connected me to a VC. I did not even know that the person I was going to meet was a VC. I reviewed the applications with him. He liked the proposals and said he could get me customers the moment the product is ready. I did not even discuss raising money.
Behind the scenes, I was facing a significant personal challenge.
I underestimated the amount of time needed for training data preparation. More time was going on that instead of algorithm development.
Starting in 2014, a former colleague offered me a contract job in computer vision (even though I had no prior experience in computer vision), which I took to support the startup. That not only consumed me fully, but was very interesting and challenging in its own right. The NLP startup work ended up on the backseat. My computer vision work was briefly covered by an independent blog writer here: https://www.technologyreview.com/2017/03/29/243161/qualcomm-...
I was left with a feeling that had I raised money and thereby gone more strongly towards the startup work, I could have been at the forefront of modern AI with deep neural networks.
To summarize, I failed because of the personal challenge which is in fact continuing till date and has severely demotivated me, and because of my reluctance to risk someone else's money.
Aside: Having learnt computer vision afresh on this contract job, I later implemented simplified versions of several classical computer vision algorithms in Microsoft Excel, using a series of one-liner formulas: https://news.ycombinator.com/item?id=22357374
In 1993, after reading George Gilder's call to waste transistors[1], I came up with the insane idea of just making a fabric of 4x4 bit lookup tables, with each table taking a bit from each neighbor, and generating a bit to send as well. It was the minimum configuration that I thought would be suitable for general purpose computation.
There turn out to be several advantages that help balance out the colossal waste of power and transistors that may eventually make it worth pursuing. The latest is that the structure is so simple there isn't anywhere to hide code that doesn't belong in the chip, so it might be useful to national security types.
[1] - https://www.wired.com/1993/04/gilder-4/
Why did it die? I didn't believe enough to pursue getting the thing made.
What did I learn? Ideas are cheap, implemented ideas are gold.
https://bestresources.co -> a place for people to share their personal resources.
Web is crowdy. So, i built this for people to share their resources (that they used while learning).
- https://github.com/jhadjar/uniflex: enables a subscriber of a telco company to send airtime to a subscriber of another telco company, which telco companies don't allow directly. I learned to research: the code worked for me using Gammu and 3G dongles of multiple telco operators, however, a "normal" SIM cannot send airtime to an "airtime merchant SIM", which would have been needed to make it work in the real world. I could have had this information in one conversation with airtime shop owners.
- https://jhadjar.wordpress.com/2016/04/09/leoculus-automotive... and https://github.com/jhadjar/Leoculus: Leoculus is an interface (project) to display analog video from a Rear View Camera on car monitors that only accept digital video (Peugeot S.A., Tesla Motors, etc.). I learned to make time and invest on things I wanted to actually do and to build for people I like to interact with. I originally started thinking about it because a friend at the time had an after-market accessory install, but I don't particularly like that vibe/space.
- One project for a friend who worked in the finance department at a telco company who used Excel to compute some things, look-up vendors/accounts, fill-out cheques, etc. I built the thing and it worked. I asked my friend then how much his company would pay for it, and his manager, although loving the product and wanting to get it told him they will not pay for it, but it would be really great if they could get it. I learned to say "fuck off".
- One project for a friend of a friend who worked at an organization of 60,000+ people who had a FileMaker thing to manage careers and the thing showed its limit. I started researching the thing to help. The data is sensitive. There was a quick and dirty prototype. I learned from my earlier projects and asked how much they would pay for it and he said nothing. Leveraging the skills I learned on my telco project, I said "fuck off".
- Another project for someone doing dental prostethics who needed to sell a product but who was ignored by wholesalers. I asked him questions at 2AM in a forest on all these products, got me some samples, had spectrography done, noticed they're quite the same, and researched the topic (polymerization and stuff). I stopped it right there because the margins are really low and I leveraged what I learned on not working in a space that I don't like.