A worldwide lockdown was thrust upon you. While you're already used to sitting on that couch occasionally to'Netflix and chill' after a tiring workweek, this time you don't have other alternatives for entertainment beyond that couch. You're browsing through the content across all OTT platforms and eventually end up binge-watching innumerable shows. All of these suited to your taste, almost tailor-made for you. In the end, you're possibly a satisfied consumer of the content.

Harrison Ford plays Deckard in Ridley Scott's 1982 noir thriller, "Blade Runner," the 25th anniversary theatrical release, "Blade Runner: The Final Cut" opens Friday at Bay Area theaters. Ran on: 11-29-2007 & quo;Blade Runner: The Final Cut,&quo; with Harrison Ford, revisits the Ridley Scott film 25 years after its original release. Ran on: 11-29-2007 ALSO Ran on: 11-30-2007 Harrison Ford plays Rick Deckard in Ridley Scott's & quo;Blade Runner: The Final Cut,&quo; a restored version of the 1982 movie. The world is like a bad science-fiction movie right about now. The streets are nearly empty, making it easy to think up last-man-on-Earth scenarios.

The coming decade will see many other innovations out of which Artificial Intelligence will be the main highlight among all.

In the end training a network is the solution of a very high dimensional non-linear optimization problem ( finding the minimum of a function). The graphic shows a two dimensional optimization problem and how the gradient descent algorithm aproaches the minimum ( center). In 2D this is trivial, in higher dimensions computationally intensive. The slider sets the step size. You want big steps to find the solution fast, but if the step size gets to big, the optimizer starts to oscilate.

It has been shown that word embeddings derived from large corpora tend to incorporate biases present in their training data. Various methods for mitigating these biases have been proposed, but recent work has demonstrated that these methods hide but fail to truly remove the biases, which can still be observed in word nearest-neighbor statistics. In this work we propose a probabilistic view of word embedding bias. We leverage this framework to present a novel method for mitigating bias which relies on probabilistic observations to yield a more robust bias mitigation algorithm. We demonstrate that this method effectively reduces bias according to three separate measures of bias while maintaining embedding quality across various popular benchmark semantic tasks.

We are at a crossroads. A crossroads that will in large part determine the future of journalism. The Covid-19 pandemic has caused an unprecedented crisis that could decimate certain media organizations. One possible solution has been proposed: artificial intelligence (AI). AI refers "to intelligent machines that learn from experience and perform tasks like humans," according to Francesco Marconi, a professor of journalism at Columbia University in New York who has just published a book on the subject: Newsmakers, Artificial Intelligence and the Future of Journalism.

So says the famed quote from Shakespeare's The Tempest, alleging that we can look to what has already happened as an indication of what will happen next. This idea could be interpreted as being rather bleak; are we doomed to repeat the errors of the past until we correct them? We certainly do need to learn and re-learn life lessons--whether in our work, relationships, finances, health, or other areas--in order to grow as people. Zooming out, the same phenomenon exists on a much bigger scale--that of our collective human history. We like to think we're improving as a species, but haven't yet come close to doing away with the conflicts and injustices that plagued our ancestors. What might happen over the course of this year, and what information would we use to make educated guesses about it?

Great to have you on the show, Ali. Thank you, Stephan, for having me here. It's a real pleasure to have me here. I listen to your podcast. It's great to be on it. It's great to have you on it. I've been trying to get you on this show for a while now. I'm really happy to have that finally come to pass. I'd love for our listeners to understand a bit more about the under the hood of Trendy Butler. How is this powered by an AI where all your competitors–the different subscription box companies–they seem to rely on human stylists, and you've got an AI? Most of them use a lot of AI to make their decision making. Except with us, we rely heavily on our AI. Obviously, there is still a stylist because as much as you could throw as many AIs as you want on to this, still there's an element of creativity that's needed for a person to be applying to this. You never could control, let's say the system picking an orange short with a purple shirt, you got to sometimes stop it. Most of it is actually done through our essentially wired AI system that picks these clothes for people now. The way it works under the hood, it's a little different from how others do it. I'm sure you heard of things like Stitch Fix, Trunk Club, and all these guys. The little difference is that, instead of having stylists being assisted by this AI to make these decisions, we do it the other way around. We have the AI make the decisions, and the stylists really look and see if they made these maybe improper decision making. The way it works, usually how people attack the problem or others attack the problem, is that each person they bring them up, and then look at the historical goals that they've… Because throughout the process when you signed up, you essentially are asked multiple questions. Those questions essentially help us guide our styling methods and questionnaires. The way we do it is we turn this process upside down. When we acquire a customer, we ask them a set of questions. Those questions could be from your sizing, your preference in patterns, the type of pants that you like. Then we go a little further, we look at your occupation, we look at your location, the location tells us a lot about you. That tells us the type of clothes that you want. If you send someone in Florida a heavy jacket, I'm sure they're not going to like it. The location makes a lot of sense. Occupation makes a lot of sense.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. Will machines ever be able to replace or replicate human creativity? That is a question that we repeatedly ask ourselves as we continue to innovate and invent new creative tools. The printing press, the gramophone, the camera, the camcorder, the typewriter, the synthesizer, word processors, photo editing software, and many other tools we have invented over the past centuries have brought fundamental changes to creativity and arts. But what has remained constant throughout history is the human element.