These are good calculations. I think many people would like to go to a significantly larger field of view than 40 degrees. 40 degrees horizontally is not that much: the human visual field is over 200 degrees.
OLED-on-glass-substrate is allowing TVs to get lighter making them more installable. OLED-on-plastic-substrate TVs could be shipped rolled up. They may not be that far away (<10 years).
The older copy of the US site at https://web.archive.org/web/20180206011840/https://www.42.us...
is very clear:
"I AM NOT BETWEEN THE AGES OF 18 AND 30. CAN I COME TO 42?
No. While we do not have anything against those who are over 30 years old, when opening a new location, we have decided to concentrate our where they can be the most efficient and where we have a great deal of experience."
On the current site this is changed to:
"You can apply to 42 if you’re older than 45, but please know that most students here are younger and that Intensive Basic Training is tiring."
Hardly encouraging.
The french site http://www.42.fr/ says "ouverte à tous et accessible aux 18-30 ans" (18-30 only)
Draw your own conclusions about age discrimination here. You are free to apply...
"Email is a wonderful thing for people whose role in life is to be on top of things. But not for me; my role is to be on the bottom of things. What I do takes long hours of studying and uninterruptible concentration."
This article might be one of the best intros:
Space-Time Approach to Non-Relativistic Quantum Mechanics
R. P. Feynman
Rev. Mod. Phys. 20, 367 – Published 1 April 1948
Following Gladwell's 10000 hour rule, I would say you could probably call yourself a data science after 1000+ hours experience working with datasets successfully. As far as the math goes you should be able to do regression analysis, you don't need to know tons of stats but you do need to know stats and probability essentials (first few classes at a good school) deeply. I like this Wikipedia entry on "mathematical maturity": http://en.wikipedia.org/wiki/Mathematical_maturity; apart from writing proofs, it is very relevant.
I haven't seen any lab demonstrations of multi Mbit devices. Until we see that this is years away from production in my experience as a device physics researcher. All storage technologies so far have taken 10 years plus to have large market share and I don't see this as an exception.
Flock math department here. Robots are software-limited, and Flock has more overlap with robotics on the software side than people might think. At Bump we have been writing software to exchange bits of stuff between computers that 50% of the population has attached to their bodies. Flock is actively making decisions for the human based on situational awareness. The machine learning and statistical techniques we are using are the same ones that are being using in robotics for e.g. situational awareness and path/task planning.
If anyone out there is interested in being a developer in my group and is handy with algorithms and fast data stores e.g. Redis, ideally in production, email me.
If anyone wants to do some very interesting contract work in machine learning (SVMs) for a YC company, please mail me. [edit: email address now in my profile oops]
Yes, you need to be careful about overlap (transparency can help), but without a scatterplot, I would not see the sharp edges, or have my attention drawn to the outliers.
Density plots imply a model: By creating bins, square or hex, you are adding a layer of interpretation on top of the 2D data, which can be bad. Also the bins of this article have sharp edges (high frequency content) and add artificial structure. I think smooth density plots, not covered by this article, are superior.
Even though I can program an Arduino just fine, this is so low-friction that it will encourage me do short projects and experiments I otherwise might not.
40 inch flat panels used to cost $40000 in higher volumes (production quantity) than LIDARs are shipping now. Now these panels cost ~$500 (and are better).
Bump has one engineer in Tokyo and we may expand, probably on front-end mobile (iOS or Android). Our lead product the Bump app is the 5th most popular app of all time in Japan.
Want to work on a product that is used and loved by millions?
Bump Technologies is the developer of the Bump app available on iOS and Android. Bump allows users to exchange contact info, photos, and more, simply by fist bumping phones together. We now have more than 75mm downloads and are growing quickly. Objective C, Cocoa, Java, Scala, Python, Diesel, Redis, Riak, and Haskell are just some of the languages/technologies we use.
* Android developers
* iOS developers
* Backend (python) developers
Internships in Android, iOS, backend, data analytics, product, and design.
At Bump, we offer a fun, collaborative working environment. You will be challenged to come up with creative solutions to interesting problems and own your own project. The designs you make and the code you develop will be used by our tens of millions of active users. We have been working on some new products and features that we are planning to launch in 2012, so it is a really exciting time to join our team. Check out our tech blog and intern blog on our website to read about some of the cool things we are working on.
For more information and to apply online, visit our website http://bu.mp/jobs.
