HN user
I was recently swindled by a custom framing store (and by that I mean they delivered their advertised service at highway robbery prices).
If I ever frame anything again, I will look into Level Frame.
It's a pretty solid resume, but I've seen a dozen better ones that don't belong to billionaires... Unless...
Sorry, gotta update my LinkedIn.
After having a little patience to digest the stuffy academic language I realized something:
This is one of the craziest articles I have ever read.
It is like the premise of a sci-fi novel where future states slowly creep along by dredging and filling in land. But it's actually really happening at a scale beyond novelties like Dubai and non-contentious (at least internationally) expansions like Battery Park City.
The fact that sand-smuggling is a thing...
In my mind, the next big step will be the machine perception, specifically full scene understanding in vision.
Computer vision has advanced very rapidly recently in sub-tasks like object recognition, scene segmentation, 3d-modeling from videos, and others.
Now people are trying to put these elements together, along with text-based metadata and logic for physical interpretation of images (e.g. the coffee cup is on the table which is on the ground and abuts the wall; physical interpretations of spatial information).
Soon enough we'll be to the point where a drone can identify and track most objects in its line of sight and know their physical relationships to each other. This opens up tremendous possibilities in robotics.
"You won't believe what the data about Buzzfeed clickbait reveals!"
How can someone be a "secret" genius if they are one of the most famous mathematicians of the 20th century and received the field's highest honor?
I do not think that word means what you think it means.
Even if his criticisms of coveillance are correct, I still think the world is headed that way.
Simply put, you can't put the genie back in the bottle. We passed a similar threshold with industrialization, and the consequent removal of autonomy for workers on several levels (is the 1800's factory of exacting time cards and constant repetitive movements that far behind the warehouse the author describes?). It was a tumultuous transition (strikes, revolution, communism, etc.) but we made it through. The transformation in state and corporate power that tools like surveillance bring will be similar, but just like in the industrial revolution we can't turn back the clock and have to instead ride out whatever happens.
I use and enjoy the services that uber offers. That said, it uses dubious loopholes to evade the (misguided, anti-competitive) regulations taxi companies operate under.
Letting uber evade the bad regulations instead of fixing them is a poor solution (same with tesla and dealerships).
I feel like I get this advice all the time. "Invest in Indexes" is ridiculously popular advice. I've also been exposed to portfolio theory in lots of academic literature.
It's not obscure within finance or without.
Needs better transit for that to happen.
I'm calling his work on LeNet in 1998 pioneering. I'm not trying to disparage his current work.
Lecun's work on LeNet was pioneering, and basically set the template for deep learning. However, it's not as simple as him being "right all along"; incremental advances in neural net architectures, a lot of developments in stochastic gradient methods, and orders-of-magnitude improvements in hardware and data availability have been what made deep learning as powerful as it is today.
The main point is that skeptics in the 2000's were basically right about neural nets being of limited use, but other technologies advanced and broke down the barriers.
Lecun's original convolutional nets in 1998 were run on the then-gigantic dataset of 60,000 images. Consider that a company like Facebook can provide billions of images with some form of tagging, and you see the different world we live in.
It was fought over states' right to maintain the constitutionality of slavery.
Where is the design?
You mean like https://angulardart.org/
The true value proposition of deep learning is not to avoid hand-coded features, but to make better use of scale in data and computational resources.
More specifically, adding SIFT or edge detection to your raw pixel input will almost always strictly improve a deep model's performance (though they might be redundant) at a not-particularly-large computational cost.
It wouldn't solve the adversarial example problem though, except to the extent that it makes calculating gradients harder.
VCs deal in illiquid, information-asymmetric markets where prices are directly negotiated, capital is locked up for an extended period, and deals are large enough that investment is forced to be "lumpy".
If you could somehow invest in a startup "index", it would be great, but there really is no such thing (especially not for the VCs).
I guarantee the amount of time spent on traveling salesman problems at Uber is a miniscule fraction of all development time.
I know someone who intereviewed at Vicarious and came away unimpressed. That said, any company with an investment by a guy who can make his company buy it out is a good one to invest in.
If Larry Page, Sergey Brin and Eric Schmidt announced tomorrow that they would do everything in their power to prevent GOOG from EVER paying dividends, buying back stock, or selling to another company, then that would be catastrophic for the share price, correct? This is a step beyond simply being disinterested in dividends and buybacks in the near term, but you seem to be confusing the two.
Anyone who purchased shares at that point would be doing so because of one of the following 1) They believe that Page, Brin and Schmidt will change their minds 2) They believe that control will be wrested away from Page, Brin and Schmidt by more buyback/dividend friendly management 3) They believe that other people will still buy for reasons 1,2, or 3. This is classic Keynes Beauty Contest investing.
GOOG could still grow its revenues, but if it is guaranteed to never pay a dividend or buy back stock (Berkshire Hathaway doesn't pay dividends but Buffett has said he would definitely pursue share buybacks under certain conditions) or sell its assets, then there is no way to get cash out of GOOG except by trading with other beauty contest investors. The only thing left to anchor GOOG stock value to Google the company is the possibility of bankruptcy.
So yetanotherphd is 100% correct. It's not impossible for people to trade as if there's no connection between a company's future dividends/buybacks/asset sales and its stock price. But that's how you end up buying tulip bulbs for their weight in gold.