365 karma · joined March 15, 2016
x: @nselmi
hnchat:Tvj9hHlcviEKPVWG2YIh
Not saying it's useful but you saying "only way to read SQLite is SQLite" is hyperbole.
@safaitic
Did you overcome that and learn from the mistakes? No offence, but to be honest you saying "I could have been SalesForce" makes it seem like you're still working on the arrogance part.
It would have been more adequate if, say, the drone could last a day. Which would roughly be a 10x improvement.
I would bet in less than 10 years you'll have camera only fully autonomous systems.
Cyber space is a high leverage domain which rules out the possibility of a shortage in resources from the opponent. It is also a recent evolving space which makes it more difficult to assess the opponents capabilities, reach and sophistication.
By its nature this operation seems to be part of a bigger destabilisation strategy, maybe a stress test to validate different tactics.
I would be really worried once the ads become well written which would increase the complexity of the situation since quality measures can be manipulated.
In other words once they can fake "fake news", things might get really weird.
That's where the right-left model breaks. This is not an extreme right wing thing, it's statist authoritarianism. Can be embraced by both sides, extreme or not.
For example:
The easiest and most abundant thing to learn on the web is unsurprisingly web development.
An ML engineer can use ML to optimize the data structures that he uses for his models.
I could not say the same about fields like biology or physics.
Another illuminating sentence from the paper was this:
>This leads to an interesting observation: a model which predicts the position given a key inside a sorted array effectively approximates the cumulative distribution function (CDF). We can model the CDF of the data to predict the position as: p = F(Key) ∗ N
Maybe it's just my very limited knowledge as an undergrad but I'm feeling that this can be the start of something big. Another idea that just came to me after is how much of this ML is applicable to the domain of cryptography. In my security class it seemed like much of the famous hash functions for example were somehow "found" in vast space of potential schemes.