There's a lesson I once learned from a CEO--a leader admired not just for his strategic acumen but also for his unerring eye for quality. He's renowned for respecting the creative people in his company. Yet he's also unflinching in offering pointed feedback. When asked what guided his input, he said, "I may not be a creative genius, but I've come to trust my taste." That comment stuck with me. I've spent much of my career thinking about leadership.

Motivated by applications in electronic games as well as teaching systems, we investigate the problem of dynamic difficulty adjustment. The task here is to repeatedly find a game difficulty setting that is neither'too easy' and bores the player, nor'too difficult' and overburdens the player. The contributions of this paper are (i) the formulation of difficulty adjustment as an online learning problem on partially ordered sets, (ii) an exponential update algorithm for dynamic difficulty adjustment, (iii) a bound on the number of wrong difficulty settings relative to the best static setting chosen in hindsight, and (iv) an empirical investigation of the algorithm when playing against adversaries.

The use of Python for social media text mining and natural language processing is an important and valuable concept. The concept has tremendous potential for ... Do You Want to Analyse Product Reviews or Social Media Posts to see whether they are positive or negative? Do you want to be able to make Computers understand Natural Language? Then this course is just right for you! We will go over the basic, theoretical foundations of Natural Language Processing (NLP) and directly apply them in Python.

An artificial intelligence taught itself to manipulate blocks by setting increasingly difficult goals. Unlike human students, computers don't seem to get bored or frustrated when a lesson is too easy or too hard. But just like humans, they do better when a lesson plan is "just right" for their level of skill. Coming up with the right curricula isn't easy, though, so computer scientists wondered: What if they could make machines design their own? That's what researchers have done in several new studies, creating artificial intelligence (AI) that can figure out how best to teach itself.

I had more than a month to try out the new Honor 10 and here is my honest review on what I think of the phone. Hint – AI camera is awesome! I got the chance to review the Honor 10 over the period of more than a month recently and there are tons of stuffs that I like about it. Of course there are some misses along the way but I feel those are forgivable. But when it comes to AI features in the camera, the Honor 10 scores high in my books.

Safety stock is among the most critical elements in the pharmaceutical supply chain. Yet safety stock has also proven very difficult to manage and optimize, even as it locks down working capital and drives up inventory costs. Pharmaceutical companies typically maintain high levels of safety stock to achieve better service levels that maximize revenue of high-margin products and drive customer satisfaction. Also called buffer stock, it provides a safety net against variability such as unanticipated delays in raw materials or transportation, or unusually high demand. Stockouts that result from inadequate safety stock could be highly damaging to the business, with millions in lost revenue and potential brand damage if vital medicines are unavailable.

From 50 ways to leave your lover, as the song goes, to 750 types of shampoos, we live in an endless sea of choices. And although I haven't been in the market for hair products in a while, I understand the appeal of picking a product that's just right for you, even if the decision-making is often agonizing. This quandary (the "Goldilocks Syndrome", of finding the option that is "just right") has now made its way to the travel industry, as the race is on to deliver highly personalized and contextual offers for your next flight, hotel room or car rental. Technology, of course, is both a key driver and enabler of this brave new world of merchandising in the travel business. What is allowing airlines, hotels and other travel companies to behave more like modern-day retailers is the clever use of self-learning systems, heuristics trained by massive data sets and haptic-enabled video hardware.

The vultures of Britain's International Centre for Birds of Prey don't know it, but they're dupes. Every day, the giant birds carefully tend to their eggs, rotating them periodically so they incubate just right. But…take a closer look at that nest. Not every egg in there is made of calcium carbonate, and they don't always contain baby birds. No, at this conservation center, some of those eggs are actually 3-D printed.

Motivated by applications in electronic games as well as teaching systems, we investigate the problem of dynamic difficulty adjustment. The task here is to repeatedly find a game difficulty setting that is neither `too easy' and bores the player, nor `too difficult' and overburdens the player. The contributions of this paper are ($i$) formulation of difficulty adjustment as an online learning problem on partially ordered sets, ($ii$) an exponential update algorithm for dynamic difficulty adjustment, ($iii$) a bound on the number of wrong difficulty settings relative to the best static setting chosen in hindsight, and ($iv$) an empirical investigation of the algorithm when playing against adversaries.