Your personal belief is likely correct. Balancing a donking range is incredibly difficult for humans and doing so perfectly likely yields only a very small EV bonus over just always checking. For humans it makes a whole lot of sense to reduce the branching in a case like that whereas for computers it doesn't really matter.
Another good example is varying continuation betting sizes. A true GTO strategy would mix in a number of different sizings (and I'm sure the bots adapted to do this), but you only sacrifice a very tiny amount of EV by basically betting the same size every time. Doing the latter limits humans risk for making errors which is far more valuable than squeezing out .05bb/100 more by varying the sizes.
But it is now available with Google Maps! View some location in Satellite mode, and then click the "3d" button on lower right. And then you can view any place from various angles
It's a nice trick sure, using machine learning (I assume) to build 3d geometry from 2d satellite images, but it's nothing compared to the quality and fidelity of the images taken by low flying airplanes that Birds Eye in Bing actually used. Made house/apartment hunting a dream!
Looking at 3d google maps a bit more closely, it does seem they are capturing the sides of buildings that are not visible on the top down image. Still nowhere near the quality of Birds Eye, but I'd be interested in what other image sources they are using besides top down, and how they are captured.
It isn't machine learning, it's aerial photography shot at an angle with depth sensing.
For example, take an airplane and mount two cameras on it, one on each side, angled down at perhaps 45 degrees to capture ground imagery in each direction.
Add a LIDAR device next to each camera to capture a "point cloud" of the same area the camera is imaging.
Now you have photographic images with distance data for each pixel. You can use that to construct a 3D image that can be viewed from various angles.
(Disclosure: I work at an unrelated Alphabet company but have no personal knowledge of any of this, it's just my semi-educated guess.)
You probably don't even need the LIDAR. Since the airplane is moving, you can use the parallax between successive images to determine depth information. The technique is called "structure from motion"
I thought it had to be accomplished by satellite somehow. I looked at a very remote island in the southern Indian Ocean where I was stationed and the amount of detail in Bing Bird's eye view of the geography was astonishing. This was circa 2013. I would be very surprised if they flew a plane out there just for those islands, there are no flights or shipping routes passing by there.
Passing the Jepsen tests mean they'd say they're addressing the larger part of that market, rather than document stores specifically.
(I still think MongoDB, the company, isn't particularly great for the usual reasons re their past behaviour, I'm just imagining what they'd tell their investors)
Did you consider that perhaps projection of growth is exactly what you'd do in the event of an IPO? Or that Google trends isn't a sensible heuristic for a valuation?
I've down-voted you not because I disagree fundamentally (although I don't rate MongoDB) but because you are dismantling an argument badly. I hope that isn't too rude.
it is exactly what you'd do in the event of an IPO. I just don't understand how investing tons of money in human capital could be considered a "cash out" as the person I was replying to put it. If anything, it's the opposite.
Google Trends indicates how many new projects look for a database. Database companies typically make money with existing projects (subscription fees or occasionally new versions).
I agree that MongoDB is considered for many new projects but they will have very low market share for existing enterprise projects (which is where the money is).
I read about the first 50 replies or so and found myself agreeing with the 'meh' user, but after reading that blog post, it seems aredridel was on to something...
