How many training samples we observe over life time ?

In this post, I like to compute what number of visual instances we observes over time, with the assumption that we visually perceive life as a constant video with a certain fps rate.

Let's dive into the computation. Relying on [1],  average person can see the world with 45 fps on average. It goes to extremes for such people like fighter pilots which is 225fps with the adrenaline kicked in.  I took the average life time 71 years [3] equals to $2239056000$ (2 .24 billion) secs and we are awake almost $2/3$ of  it which makes $1492704000$ (1.49 billion) secs .  Then we assume that on average there are $86*10^9$ neurons in our brain [2]. This is our model size.

Eventually and roughly, that means without any further investigation, we have a model with 86 billion parameters which learns from  $1492704000 * 45 = 67171680000$  almost 67 billion images.

Of course this is not a convenient way to come with this numbers but fun comes by ignorance 🙂

[1] http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2826883/figure/F2/

[2] http://www.ncbi.nlm.nih.gov/pubmed/19226510

[3] http://www.who.int/gho/mortality_burden_disease/life_tables/situation_trends/en/

Why I chose industry over academy

In general, if I need to choose something over some other thing I enlist the positive and negative facts about options and have a basic summation to find out the correct one.

Here I itemize my subjective pros and cons list. Maybe you might find it skewed or ridiculous but these are based on my 3 years of hard core academic effort and 2 years in industry (sum of my partial efforts). I think they present at least some of the obstacles you would see in the both worlds.

Pros--

1. Academic life is the best in terms of freedom at work. You choose your study topic, at least to some extent, you team-up and follow the boundaries of human knowledge so as to extend it a bit. This is a very respectful and curious search. For sure, it is better than having a boss choosing your way to go. However , even this freedom is limited as in  the below comic 🙂
2. Dresscode. Yes, academy is not so certain to define a particular dresscode for you, in most cases. You are free to put on your comfortable shorts and flip-flops and go to your office to work. However, it should be pointed out that present industry also realized the idiocy of strict dresscodes and it provides better conditions for the employees as well. Yet, business is still not comparable with the academy.
3. Travel around the world with conferences, summer-schools, meetings, internships at low-cost. Meet people around the globe and feel the international sense.
4. Respectful job. It urges the sense of respect as you say you are an academic and  people usually assume you are more intelligent than the most, thanks to great scientist ancestors.
5. Set your schedule. Schedule of an academic is more flexible and you have a bit of freedom to define your work time.
6. Teaching. It is really great to envision young people with your knowledge and experience. Even-more, it is a vital role in a society since you are able to shape the future with the young people you touch.
7. Elegant social circle. Being an academic chains you with a social circle of people with a similar education level and supposedly similar level of cultivation. That of course does not mean that the industry consists of the ignorant but living in corporate life is more susceptible to facing unfortunate minds.

Large data really helps for Object Detection ?

I stumbled upon a interesting BMVC 2012 paper (Do We Need More Training Data or Better Models for Object Detection? -- Zhu, Xiangxin, Vondrick, Carl, Ramanan, Deva, Fowlkes, Charless). It is claming something contrary to current notion of big data theory that advocates benefit of large data-sets so as to learn better models with increasing training data size. Nevertheless, the paper states that large training data is not that much helpful for learning better models, indeed more data is maleficent without careful tuning of your system !! Continue reading Large data really helps for Object Detection ?

All kind of data is useful for companies since they are able to understand and direct their customers as much as data is acquired. The main purpose of the business is that. Understand  customers so that you can make them happy, keep them alive in the company border. The only communication then is the data provided by all those people. They hire data analysis people and try to uncover some unknowns.

fact#29

In 30 minutes, the average body gives off enough heat (combined) to bring a half gallon of water to boil.

facts#28

The lungs contain over 300,000 million capillaries (tiny blood vessels). If they were laid end to end, they would stretch 2400km (1500 miles).