Tìm Co-founder ở VN

Tiếp bài “Chia sẻ kiến thức startup” kì trước.

Đã học gần hết 2 năm ở USC, thời gian trôi thật nhanh. Mấy đưa bạn cùng lứa vào trường đã đi làm ở Google, Microsoft cả rồi, còn mình ở lại trường làm thuê cho giáo thêm 3+ năm nữa, đôi lúc thấy nhạt. Mình muốn bắt đầu làm một cái gì đó cho riêng mình, start-up. (ở VN trước, ở Mỹ thì cần thêm ít chất xám nữa).

Ý tưởng cũ: “xây dựng mobile app và website để thu thập dữ liệu về local business – cơ bản là giống Yelp.com”. Làm về mảng quán ăn – nhà hàng trước. Nếu thành công có thể mở rộng cho shopping. Mình nghĩ app này có nhu cầu người dùng cao mà chưa ai làm đến đầu đến đũa? Mô hình này là lấy tiền từ quảng cáo từ local business hoặc brand ads. Ngược lại mình đem lại cho họ thêm lợi nhuận bằng nhiều khách hơn.

Không giống như Facebook, Google…, phần mềm nước ngoài khó chen chân vào cái thị trường local business vì đơn giản là tính local và physical của restaurant hay shopping. Lại thêm quán cóc vỉa hè nhiều ^^. Tóm lại là ít rủi ro hơn làm social network apps, Viber-like apps.

Trong note ”Chia sẻ kiến thức startup”, startup cần phát triển 3 yếu tố cùng lúc, People, Customer và Funding. Về con người, đầu tiên, mình cần tìm một co-founder mà complement với mình. Cụ thể, mình có king nghiệm xây dựng back-end, nên muốn tìm một người có kinh nghiệm về GUI (web, mobile app). Tất nhiên trong start-up, mặc định cần self-motivation để drive công việc ở VN, có cùng chí hướng, đam mê startup và khá coding. Mình vẫn đang phải làm PhD nên sẽ làm part-time và remote. Giai đoạn đầu, ngoài ideas, mình sẽ đóng góp về system design, xây dựng backend và tìm kiếm funding.

Bài toán là làm sao xây dựng user base và data cập nhật về local business. Mình có một số idea xuất phát từ research đang làm về location-based, muốn thảo luận với ai quan tâm. Những strategy để build user base và restaurant data cần thảo luận chi tiết.

Về funding, ở giai đoạn incubator, mình có thể bỏ ra $1000-1500 mỗi tháng để nhóm hoạt động. Sau khi có vision rõ ràng là đi kiếm funding, có beta version thì mang đi quảng bá.

Ai quan tâm hoặc biết ai có thể quan tâm thì contact/refer cho mình nhé.

Thanks much!


e-mail: ubriela@gmail.com



Spatial Crowdsourcing and Applications

Spatial crowdsourcing is a new mobile platform which extends crowdsourcing beyond the digital domain and link it to tasks in the physical world. One of my favorite examples to explain spatial crowdsourcing is a real story in Beijing, China. A young Chinese girl, named Ling Yifan, initiated a love campaign to make granpa’s last days delightful moments (he was diagnosed with limph cancer). She created a campaign on the Internet, “Taking Grandpa Around the World”. Consequently, she received 20,000+ replies with photos of her grandfather’s portrait at many beautiful places around the world, such as Switzerland, Italy, Germany, San Francisco. As a result, her grandfather lived his last days with joys and fun, watching beautiful pictures. Let come back to this example later.

So what is spatial crowdsourcing? let break the term into three parts 1) outsourcing 2) crowd and 3) spatial.

First of all, outsourcing is the contract out of an internal business process to a third-party organization (wiki). For example, Apple ships the task of making iphone cases to China due to cheaper labors or Japanese software companies outsource parts of their softwares development to Vietnam for the same reason. More examples can be found in the book “The World is Flat”.

Second, why crowd? There is a whole research area in crowd-related topics, such as group think, crowdfunding, crowdsourcing. Most of those research were based on the claim that a group of people is more intelligent than individuals because of the diversity of ideas. This probably a reason why we have group meetings, group discussions, etc, to collect intelligence from people or generally the crowd. A book named “The Wisdom of Crowds” discusses this. From my understanding, the concept of crowdsourcing is essentially taking the idea of crowd to the outsourcing business. In 2006, Jeff Howe first tossed the term crowdsourcing in Wired Magazine. He defined crowdsourcing as a process of outsourcing is the act of a company taking a function performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. There are various examples of crowdsourcing examples. Mturk.com and Odesk.com are of the biggest crowdsourcing Internet marketplaces. The idea of these crowdsourcing platforms is to utilize human computation to perform tasks that computers are currently have not been able to solve effectively yet, such as labeling pictures. Other examples could be threadless.com, which is a company outsourcing the tasks of designing t-shirt to the crowd (they made money out of it) or innocentive.com, whose idea is to outsource the task of solving scientific problems to the crowd.

Finally, how does the spatial aspect play a role in crowdsourcing? To make it simple, spatial means a location with latitude and longitude. With spatial crowdsourcing, the users need to physically present at the task location in order to perform the task. That is, the users not only interact with each others on the Internet but also on the physical world. A main reason makes crowdsourcing a successful business model is the popularity and convenience of Internet; gathering workforce from the crowd becomes easy than ever. However, with spatial crowdsourcing, physically travel to a location is an impediment to the practicality and applications of spatial crowdsourcing. People are not likely to drive 30 miles to do some simple tasks. It just does not work. To make spatial crowdsourcing applications work, the tasks shouldn’t take much time from the users. One way to make this happen is to allow users to solve tasks while traveling. So the potential users of spatial crowdsourcing are the ones who travel a lot. An example spatial crowdsourcing is Waze.com, which is a free GPS navigation app on iphone/android with spatial-crowdsourced features. The users (drivers) can report traffic jam, accident or police so that the other users who are driving ahead this road be aware of those incidents in advance. Another feature is to report the prices of gas stations (in U.S you can save a few bucks by going to a cheap gas station). Note that the users can do these tasks without much effort. Other successful examples include but not limited to Uber – taxi ride-sharing app, TaskRabbit, GigWalk – crowdsourcing household tasks or recently Google shopping express.

The question is why suddenly spatial crowdsourcing become popular?

The reason is that smartphones are now so popular and there are many sensors within them. Also, the network quality is getting higher, like 4G LTE. Those three enable us to develop SC applications listed in the Figure below.


Examples of Spatial Crowdsourcing Applications

Recently, we developed an app named iRain [1] that utilizes spatial crowdsourcing technology to enable human workers to report precipitation condition, particularly rain level/no-rain observation to improve real-time global satellite precipitation estimation. Basically, researchers can specify a set of locations they want rain information, our system crowdsource the tasks (i.e., a set of locations) to nearby users using push notifications. When notified users get the tasks, they just need to report, let say “heavy rain”. All the reports from users are then usable for the researchers.

[1] Hien To, Liyue Fan, Luan Tran, and Cyrus Shahabi, Real-Time Task Assignment in Hyperlocal Spatial Crowdsourcing under Budget Constraints, In Proceeding of IEEE International Conference on Pervasive Computing and Communications (PerCom 2016), Sydney, Australia, March 14-18, 2016