time "spent" in the database depends on the speed of DB drivers too, which depends on the language. Our stuff is Java and average query is ~2ms round trip.
Python, Ruby and friends are bad for page speed metrics. REST response time of ~200ms vs ~10ms for our java backends
As with anything else, use your intuition, read between the lines, follow the incentives/money.
Based on the rating they give it does seem like a questionable source.
But if you want to go down that rabbit hole of who is or who isn't a questionable source based on some fact-checker you will eventually reach the question, how do we know that our fact-checker isn't biased? who funds the fact-checker, are there any political motivations over-ruling journalistic integrity, etc. And then eventually you arrive at a fact-checker that fact-checks other fact-checkers. And you can keep going down that rabbit hole forever or you can learn to use your intuition.
I will also say this:
Even a broken clock is right twice per day.
And in the same vein,
Even a questionable source can write an article based on facts every now and then.
Also they can get the Story from Fox News and Tucker Carlson, except the response will be the same. Unless the story comes from a publisher that aligns with their ideals, they won't trust it. Given the story is negative against someone they're throwing support for, they have 0 incentive to share the news. The media isn't about truth in story, it's about truth in political position.
I think this depends on the culture of the company. In sale&marketing-centric companies, it can be as you described. In engineering-centric companies, engineers sometimes create features and products that customers haven't asked for, and then it's up to sales&marketing to drive adoption, even if it is against customer protests, because the investment needs to be recouped.
I had had the exact same reaction. My career sometimes feels like a series of meetings in which I implore product managers to keep things simple and consistent instead of adding every bell and/or whistle imaginable.
And working less hours is also skewed by the rise of millions of gig jobs that don't have set hours.
The top 25% of the population is doing great by any measure. But when you discard the top 25%, the rest doesn't look so good. Income inequality in US is higher than almost every other industrialized nation. As high as it was in the 30's when massive social unrest gave rise to unions and worker protections.
When you factor in student loan debt and minimum wage being degraded by inflation and gig jobs, the bottom 50% are poorer than ever. As of this year, student loans have eclipsed credit card and auto loans as the second largest form of consumer debt behind mortgages
It might be a good thing for me at this point. Started out on a promising new project. Years later its been designed by committee into a sprawling unfocused mess. Maybe getting the boot would spur me to go back through the interview gauntlet
Unless the site uses certificate pinning its possible to do a downgrade attack that forces browser off of HTTPS. The extension HTTPS Everywhere is a stopgap against this
I'm going to be controversial here, and say that its possible that light colored skin is easier to identify from background, giving higher confidence to "is face" detection with lower false positives.
Brown is, next to green, the most common color in nature. Lighter color also has a greater contrast with the background when using camera flash or other subject lighting.
To be really blunt, I think white faces are easier to see. A common example in nature, white tailed deer. When tail is raised, their white fur is a clear danger signal because it stands out from the background. Like most mammals, the rest of their body is a shade of brown.
I don't think its racist to suggest that light skin, just like blue eyes, is a conspicuous highly visible signal suggesting a human face.
I find it hard to believe that such a large number of facial recognition models have an easier time identifying white people after years of publicity solely because of biased training data.
The ultimate example is probably blue eyes. Almost no other animal has blue eyes. Blue is extremely rare in nature. I want to see a study on facial recognition, blue eyes vs other colors. I bet money you will find that models excel at recognizing human faces with blue eyes above all other factors
I agree, I also think that it's possible everyone involved could have been working with diversity in mind and still were blind to this bug.
Imagine someone makes a diverse facial recognition model where the confidence for detecting black faces are usually 99.96% even in rough lighting and 99.99% for white faces. They may have an acceptance bar at 95% so it's well within tolerance.
Combine that with an auto-cropping algorithm that takes a image, does computer vision on it, and selects the object that has the highest confidence and fits within the crop window.
When tested on both, portraits of white people and black people, it would pass, but in the examples, it falls down.
I say all of this not to excuse Twitter -- I still think they need to rethink how their autocrop works and fix it, but I don't think people these days do any type of people recognition without thinking of diversity.
I find it hard to see why they're using computer vision for cropping at all. Years ago there was a post on Reddit which showed how Reddit crops images for thumbnails; as far as I remember, it was to do with colour density, not facial recognition, and written with a simple image library in Python. With some images, you could predict what the thumbnail would contain. Perhaps that also had a racial bias, but at least it wouldn't be contributing to a long list of sociological criticisms of machine learning.
To blue eyes again, you could make a facial recognition system that just looked for 2 blue iris shapes and probably score 90%+ accuracy on most datasets (of exclusively blue eyed people and non-human objects) because blue is so rare in animal eyes, and so rare in nature. With such a strong face signal it may be impossible to match accuracy for non-blue-eyes humans without purposely making match quality for blue eyes worse.
We may be seeing a similar but weaker bias for darker skin. Light skin is fairly rare among mammals. The only solution to eliminating recognition accuracy bias may be to nerf accuracy for people with light skin. There have been many reports of facial recognition erroneously classifying dark skinned humans as animals. If part of model accuracy classifies lighter skin animal = more likely human, its going to be very hard to remove that bias because its empirically true. If the classifier is unsure if a shape is a human or animal face, but its very lightly colored, it may make the model statistically more accurate to report higher confidence that a lighter colored face is more likely to be human.
this may be more of a "most animals are brown" than a "brown people look more like animals" problem with the models. A possible path to fixing the bias is to crop all faces detected, disregarding model confidence of whether the face is human
> Tech companies have made clear that they don’t like the idea of blocking apps without a more organized policy process, and have suggested that they see this as a First Amendment issue, said Adam Segal, a cybersecurity expert at the Council on Foreign Relations.
Yet they're both perfectly fine with blocking apps for arbitrary reasons citing "app store policy".
Lets be blunt here, whether you agree with the Tiktok issue or not, for Apple and Google this is purely a money issue. They are probably afraid this will increase support for third party app stores among the masses
> Yet they're both perfectly fine with blocking apps for arbitrary reasons citing "app store policy".
Phrased less disingenuously: Private companies are fine making decisions based on their own internal policies, as opposed to blocking certain apps based on nebulous requests/pseudo-demands from the government.
That doesn't quite capture it. I want to buy an app for my phone and a vendor wants to sell it to me. But because my phone is a walled garden, Apple and Google who are third parties to the transaction can step in and prevent it.
The Department of Commerce is saying that the Uniform Commercial Code is also a bit of a walled garden, and we can step in and prevent it.
There are many, many things that are totally legal for private companies to do but the government is implicitly or explicitly prohibited from doing. Freedom of speech (not saying this is an example of that) is probably the prime example.
A company can bar you from saying just about anything. You can be fired for wearing a tie your boss doesn't like (this never happens, but it's legal in 49 states). The government has very narrow parameters in which is can limit speech, or more accurately, punish you for given speech.
I believe they're afraid this will increase the strength of the argument that app stores can be regulated for national causes, which is bad news for their control of their own ecosystem (to a first approximation: government involvement always increases cost). It's also, sort of, bad news for, like, Americans... If a foreign company makes a parody game critical of US politics, can the government use this precedent to get it yanked from app stores?
It's called the free market. Private businesses can make decisions as they see best, and the barrier for government overriding that is extremely high. In America at least, this is traditionally viewed as a good thing.
We also generally believe that making things "purely a money issue" is how to incentivize people to do their best work.
There are countries in the world where it's widely accepted that the government is closely involved in business decisions and does what it thinks is best for the country, and they ask people to be motivated the goals of the country, as determined by the ruling party, not their own profit motive. TikTok is familiar with one of those, in fact.
Exactly, I have no idea why you're being downvoted.
Private companies are supposed to able to follow whatever legal policies they want to in order to compete and make as much money as possible.
In a democracy, the executive branch of the government is not supposed to be able to do whatever it wants arbitrarily. That's why the legal principle of "due process" exists -- it has to follow established rules that don't single out individual people or organizations for arbitrary reasons.
The two issues (banning apps, banning companies) could not be more different in terms of the principles involved.
Python, Ruby and friends are bad for page speed metrics. REST response time of ~200ms vs ~10ms for our java backends