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Search - "stock photo"
at a previous job at a shit company ran by bible-thumpers, i was rebuilding the company website for my a-hole boss. I asked him where I should get images from- if there was a stock photo site he preferred or what.
"Just pull them off Google. That's what I do."
Later when I was combing through the site, I saw he'd added images that CLEARLY STATE another COMPANY'S NAME in the image themselves. Nothing like promoting another company on your OWN company website, huh?
(And no, their company name is not ActiveMobi.)
They're still there, 3+ years later. Dumb ass.2
Absolutely hate these "moving up", "stairs of success", "we are so diverse!" stock photos all over the internet.
You feel like you are being subtle, fuck no. Unless your target audience is stupid as as fuck, this photos looks dumb and over the top. And what is up with this "diversity" all over the place? don't get me wrong, I am all for diversity. But learn how to apply it properly.
"Looks like we need a picture of a student. Oh no, we need to be diverse. Add 15 kids of 15 different ethincity in the same picture to make sure we looks diverse. Phew!"
And the animations. Holy fucking shite. Why is it that a cheap website immediatly means that your website needs to have 100 different animation in the front page.
Seriously, picture rolling from here and there. Text coming out of nowhere.Everything being squeezed and rotated. God damn it!
This is another reason I fucking hate these 1 click websites and shite like that. This fucking website was created with WiX and my God, it's a fucking nightmare.
Good news is client is recreating the website.3
The hype of Artificial Intelligence and Neutral Net gets me sick by the day.
We all know that the potential power of AI’s give stock prices a bump and bolster investor confidence. But too many companies are reluctant to address its very real limits. It has evidently become a taboo to discuss AI’s shortcomings and the limitations of machine learning, neural nets, and deep learning. However, if we want to strategically deploy these technologies in enterprises, we really need to talk about its weaknesses.
AI lacks common sense. AI may be able to recognize that within a photo, there’s a man on a horse. But it probably won’t appreciate that the figures are actually a bronze sculpture of a man on a horse, not an actual man on an actual horse.
Let's consider the lesson offered by Margaret Mitchell, a research scientist at Google. Mitchell helps develop computers that can communicate about what they see and understand. As she feeds images and data to AIs, she asks them questions about what they “see.” In one case, Mitchell fed an AI lots of input about fun things and activities. When Mitchell showed the AI an image of a koala bear, it said, “Cute creature!” But when she showed the AI a picture of a house violently burning down, the AI exclaimed, “That’s awesome!”
The AI selected this response due to the orange and red colors it scanned in the photo; these fiery tones were frequently associated with positive responses in the AI’s input data set. It’s stories like these that demonstrate AI’s inevitable gaps, blind spots, and complete lack of common sense.
AI is data-hungry and brittle. Neural nets require far too much data to match human intellects. In most cases, they require thousands or millions of examples to learn from. Worse still, each time you need to recognize a new type of item, you have to start from scratch.
Algorithmic problem-solving is also severely hampered by the quality of data it’s fed. If an AI hasn’t been explicitly told how to answer a question, it can’t reason it out. It cannot respond to an unexpected change if it hasn’t been programmed to anticipate it.
Today’s business world is filled with disruptions and events—from physical to economic to political—and these disruptions require interpretation and flexibility. Algorithms alone cannot handle that.
"AI lacks intuition". Humans use intuition to navigate the physical world. When you pivot and swing to hit a tennis ball or step off a sidewalk to cross the street, you do so without a thought—things that would require a robot so much processing power that it’s almost inconceivable that we would engineer them.
Algorithms get trapped in local optima. When assigned a task, a computer program may find solutions that are close by in the search process—known as the local optimum—but fail to find the best of all possible solutions. Finding the best global solution would require understanding context and changing context, or thinking creatively about the problem and potential solutions. Humans can do that. They can connect seemingly disparate concepts and come up with out-of-the-box thinking that solves problems in novel ways. AI cannot.
"AI can’t explain itself". AI may come up with the right answers, but even researchers who train AI systems often do not understand how an algorithm reached a specific conclusion. This is very problematic when AI is used in the context of medical diagnoses, for example, or in any environment where decisions have non-trivial consequences. What the algorithm has “learned” remains a mystery to everyone. Even if the AI is right, people will not trust its analytical output.
Artificial Intelligence offers tremendous opportunities and capabilities but it can’t see the world as we humans do. All we need do is work on its weaknesses and have them sorted out rather than have it overly hyped with make-believes and ignore its limitations in plain sight.
Doesn't it happen to you that you examine too much stock code photos?
"'new Mail()'? Now I want to know what library that is."
(It was just an example, it is probably just a masked PHPMailer)10
Easter egg numero uno: on lifestride.com, when you search for "our puppy" you're presented with a full screen image of an awesome stock photo dog.