I'm thankful for all the extremely improbable things that had to happen for me to have the experience I'm having.
I am thankful
- To have been born to loving, educated parents
-To live in a time and place with economic and social liberty
- To have a loving and growing group of friends and family around the world who live interesting and inspiring lives
-To live in a time where so many of us can travel at the speed of sound and communicate at the speed of light
-To be able to ask any question, purchase any common object, or want to see any loved one face-to-face, and have my wish fulfilled by a vast global network of machines that do our bidding
-For the millions of seekers, of wise men and women, who created wonders from the energy of the sun and the materials of the Earth, and showed us the way through the darkness
-That after 1000 trillion creatures and eons of failed attempts, one particular hairless ape on one particular wet rock evolved a 3 pound mass of flesh into the most sophisticated computational apparatus in the universe
- That it feels like anything at all to be thinking meat.
This is a heap of nonsense. Not only does this summarily dismiss the enormous challenges in digital signal processing required for removing arbitrary background audio, it exposes some confusion associated with the ideas of correlated random variables, inner products, and affine transformations.
This has the smell of a comment written by someone with limited real-world experience. Simply writing down the list of problems you would have to solve to build Shazam would take an entire afternoon.
Yes, deep neural networks have proven remarkably useful for machine perception, but you would still need to collect a colossal amount of audio data, fingerprint all of it, build a low-latency processing infrastructure for making inferences, and convince a hundred million people to install your software to feed you copious real-world training data that you can use to improve model performance.
One reason is that the amount of training data is many many orders of magnitude smaller.
FWIW it seems the structure you're talking about exploiting is at a morphological and syntactic level, which modern language models tend to effectively handle. Semantics are a much harder problem.
High modularity refers to when a system's components can be cleanly separated and recombined.
If I were to guess, I'd say that amelius is saying that it becomes increasingly common as companies grow for them to expand into functions that were originally outside their core function. Framed this way, "selling stuff online" may have once set an effective upper bound on what Amazon does, but now they appear to be expanding into "moving stuff from place to place."
You may have meant s/tenant/tenet. I'm only pointing it out because the typo is an extant word that may be interpreted to mean something proximate (but not identical) to what I think you actually meant.
The point of this post is to call attention to the fact that while Objective C is actually a 30-year-old language that is the foundation of the entire Apple development ecosystem, some journalist misunderstood Objective C to be something that Microsoft had produced, and his or her mistake propagated wildly across the internet.
The main breakdown products of aspartame are aspartic acid and phenylalanine. You may have been born with a genetic mutation that makes it possible for you to taste phenylalanine, which tastes bad.
The main correlate is the impact of faculty output. This also is not necessarily correlated with the quality of the education students receive. But then, department rankings shouldn't necessarily reflect the quality of the education either.
If what surprised you was Figure 1 in the paper [1], note that it depicts only CS departments. The CS department at UW is widely considered among the best in the United States. Not that this is definitive, but it's ranked 6 in the US News and World report [2].
I don't think it is a mistake. I think the author is trying to make the case that startups end up having round-number valuations. I don't think he is making the case that the number of startups decreases exponentially as a function of valuation, which is what would be implied by the points (900M, Many), (1000M, 22), (1100M, 6).
Yes; in order to qualify as a skeuomorph it doesn't need to _not_ serve a purpose, it just needs to retain design cues that were essential to the function of the original but not to the function of the copy. The iOS camera could very well do its job of taking pictures without making a shutter sound. The shutter sound is an auditory cue for the user, but not a side effect of the camera's function.
As another example, consider the iOS notes app[1] before the iOS6 design transition. The app looked like a legal pad---complete with a leather binding across the top and remnants of pages torn off. These were essential functional characteristics of the original object, but were retained in the copy only to provide visual cues to the user that remind her that the app she is using is just like a notepad.
