meson2k

Good luck guessing that address. Our own unikernel, IncludeOS, randomizes addresses at each build, so even with access to source code you still don’t know the memory layout.

"There is one mortal sin in computer security (or by the way, in any kind of security) that is feeling safe. It’s just a variation of pride to be true, but it’s very deadly. Blindly trusting a protection technology is an extreme error."

Read up on DEP. Randomizing function addresses at each build is useless when it comes to attack mitigation. You need to randomize addresses at each execution.

Nokia sued Qualcomm back in the day when they were the biggest mobile manufacturer. http://www.nytimes.com/2008/07/24/technology/24qualcomm.html Look where they are now...

Apple needs to win with technology and innovation, not lawyers

The emitted code is highly name mangled - one of the reasons why you encapsulate the C code in "extern C" https://en.wikipedia.org/wiki/Name_mangling

or when memory constraints prevent you from using libstdc++

The size increase by using these techniques would be far smaller than linking in libstdc++. libc is much smaller than libstdc++, especially when you need to support dynamic code and do a whole-archive on your libraries in the executable.

Qualcomm MDM9625 is the powerhouse behind VoLTE and connectivity. This isn't the latest MDM from Qualcomm though...

This is what their website says: " Dear MtGox Customers,

In light of recent news reports and the potential repercussions on MtGox's operations and the market, a decision was taken to close all transactions for the time being in order to protect the site and our users. We will be closely monitoring the situation and will react accordingly.

Best regards, MtGox Team"

MSM6280 is 7 years old. The author has no clue how advanced these RTOS have become now and the kind of effort that goes into security at a system level e.g. xpu, smmu etc.

Dunster, any clue if Quantopian supports option trading?

Good try. Some observations: - The sharp ratio is very bad. Focus on improving. Instead of looking for spectacular gains, focus on solid growth. - Looking at the daily tick backtest, at many points, the alpha is so negative that the losses your algo occurs would make you delinquent. Again, focusing on better sharp ratio should help here. (RETURNS -72.64%) - Practical consideration: You look at every stock in data for each tick and its historical prices. This could work perfectly well at a low frequency trades e.g. daily, but not at per-second tick because computing time > transaction time i.e. you would be acting on stale inference. - Transaction costs?

PS: Pet peeve. Gradient descent is a heuristic at best and not true machine learning :)

A zero-area polygon. A zero-volume hedron. etc. etc.

"i" undeclared