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rfurlan

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Machine learning expert, quant, software engineer, Singularity University alum, serial autodidact, science lover, militant atheist & soon-to-be-robot. Blog: www.bitcortex.com

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Something most people don't know about HoloLens: the holograms stay where you put them indefinitely. So if you put a browser window on a wall in your bedroom and come back after a week, it will be exactly where you left it.

Yes, the holograms are literally objects made of light so at low brightness they are transparent, but if you crank up they will appear solid but you still won't confuse it for a real object because they are so bright.

I haven't watched a whole movie on it yet, but it wouldn't be a problem, the device is reasonably comfortable so you can wear it for hours

Yes it does work outside if the space has enough objects around so it can generate a model of the location. When model generation fails, it falls back to a "limited mode" where holograms follow you around instead of staying where you put them.

Oddly enough, the tracking system does not work in the dark, so you need some light to use it.

HoloLens user here, based on this video alone, the experience appears to be equivalent, although holograms appear to be a bit more stable on HoloLens, which also has no trouble tracking fast head movements

The problem isn't when you get banned, it is the fact that Google refuses to clearly communicate the reasons when there is real money at stake.

Google: "you delivered 30k worth of ads but I don't owe you anything because you broke the rules. I will not tell you which rules you broke or the URLs of the offending pages though, you will have to trust me"

Here is what is currently known about Glass:

- Transparent microdisplay, front-facing camera, touch-sensitive controls, audio I/O, internals "equivalent to a Galaxy Nexus", IMU, WiFi

Apple page on ergonomics? How ironic considering that most of their input devices are more like torture devices. Beautiful for sure but suitable for human use.

You are correct, their QC is more of a hardware solver for a very specific problem than a general purpose computer. On scaling, I was a D-Wave a few weeks ago, they seem to be prepared to scale-up the chip aggressively in 2012.

That is not how it works Viscanti, gate-based QCs are still toys and it remains to be proved if they will become useful anytime soon. On the other hand D-Wave's adiabatic chip is very promising but it requires you to fit a "square peg in a round hole" - expressing problems into a format their hardware can handle is tricky.

To clarify: you express your problem as an Ising model, load the model into the D-Wave One QC and it will solve it for you. The interesting thing is that solving Ising models is a NP-hard problem.

D-Wave's current chip has only 128 qubits and it is somewhat limited. As they scale it up (and they are prepared to do so) you will be able to use their computer to solve larger and larger models that could not be solved with standard silicon in a reasonable amount of time.

D-Wave's computer is basically a hardware solver for Ising/QUBO models. It is not programable in the traditional sense and you need to find a way to express the problem you want to solve in a way that maps well over the hardware.

Don't use MongoDB 15 years ago

I just recently published an article describing my experience migrating from SQL Server to MongoDB, you can read it here: http://news.ycombinator.com/item?id=3203601

I agree with the author that MongoDB is green, maybe not quite ready for prime time yet. All things considered, I realize we took a risk by switching and while I am quite happy with MongoDB, I do worry that at some point we will experience a failure condition we might not be able to recover from.

I just recently published an article describing my experience migrating from SQL Server to MongoDB, you can read it here: http://www.wireclub.com/development/TqnkQwQ8CxUYTVT90/read

I tried my best to describe both what we gained and what we lost after the transition. At the end of the day, MongoDB (and other NoSQL solutions) are different tools for different jobs. Obviously it takes investment to master a new tool and we almost aborted the migration in two different occasions simply because we didn't know enough about maximizing MongoDB performance. Now that the dust has settled and with all things considered, I am glad we didn't.

Books I would recommend for beginners:

Evidence Based Technical Analysis: http://www.amazon.com/Evidence-Based-Technical-Analysis-Scie...

Pairs Trading: http://www.amazon.com/Pairs-Trading-Quantitative-Methods-Ana...

Quantitative Trading: http://www.amazon.com/Quantitative-Trading-Build-Algorithmic...

An Introduction to High Frequency Finance: http://www.amazon.com/Introduction-High-Frequency-Finance-Ra...

Trading and Exchanges: Market Microstructure for Practitioners: http://www.amazon.com/Trading-Exchanges-Market-Microstructur...

I also wrote a couple of very introductory articles, sadly I never got past part #2: http://www.bitcortex.com/2008/12/28/pragmatic-automated-trad... http://www.bitcortex.com/2009/01/04/pragmatic-automated-trad...

I am could mentor 1-2 HN readers that are serious about getting into quant trading. Just let me know you are interested :)

You are basically choosing your competitors over your investors if you stick to your position. I would rather protect the interests of the people who have taken a risk to help me realize my vision than nurture a future competitor.