If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
When Kobe Bryant was announced as the third NBA 2K cover athlete earlier this year following his tragic death, NBA fans around the world were elated about the possibilities. I was excited because I figured that a list of challenges would be included, similar to what Michael Jordan received when he graced the cover of "NBA 2K11." Instead, the Mamba Edition gives users a few meaningless in-game tokens like 100,000 virtual coins, 10,000 MyTeam points, MyTeam packs and access to a few Bryant jerseys and shoes for your MyPlayer to sport. As noted earlier, the Mamba Edition does grant an upgrade to the next console generation, so you don't have to buy another copy for PS5 or Series X … but you do have to shell out $40 more dollars when some game franchises are allowing free next-gen upgrades.
Amazon announced that it's annual Prime Day shopping event would be on October 13 and 14 this year, but we're already starting to see Prime-exclusive deals available. One of them knocks the 3rd-generation Echo Dot to its lowest price ever -- only $20 -- when you buy two of them and use the code DOTPRIME2PK at checkout. That means you'll spend a total of $40 for two Echo Dots, which is $10 less than the normal price and $2 less than their 2019 Black Friday sale price. Remember -- this is an early Prime Day deal, so you must be an Amazon Prime member to get the savings. The company continues to offer 30-day free trials to new Prime subscribers, so you can sign up and take advantage of this deal as well as be all set for Prime Day when it rolls around in about two weeks. It's also worth calling out that the Echo Dots in this deal are the previous models.
AI Outside In is a column by PAIR's writer-in-residence, David Weinberger, who offers his outsider perspective on key ideas in machine learning. His opinions are his own and do not necessarily reflect those of Google. Suppose you want a machine learning system to suggest paint names based on any color you specify. This has been done hilariously by Janelle Shane -- "burf pink," "navel tan" -- but let's say we want to do it more seriously (and without any reference to how Shane actually did it). Machine learning, at least of the common sort called "supervised learning", learns from the data you give it, so you first want to gather a large set of colors to which humans have applied various labels.
The objective of this post is three-fold. The first part discusses the motivation behind sparsemax and its relation to softmax, summary of the original research paper in which this activation function was first introduced, and an overview of advantages from using sparsemax. Part two and three are dedicated to the mathematical derivations, concretely finding a closed-form solution as well as an appropriate loss function. In the paper "From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification", Martins et al. propose a new alternative to the widely known softmax activation function by introducing Sparsemax. While softmax is an appropriate choice for multi-class classification that outputs a normalized probability distribution over K probabilities, in many tasks, we want to obtain an output that is more sparse.
With enormous amount go textual datasets available; giants like Google, Microsoft, Facebook etc have diverted their focus towards NLP. Let's these Tweets put things into perspective: This is barely the tip of the iceberg. So while you were trying to understand and implement a model, a bunch of new lighter and faster models were already available. I read them all to realize most of the research is re-iteration of similar concepts. Learn to use what's available, efficiently, before jumping on to what else can be used In practice, these models are a small part of a much bigger pipeline.
Digital Twin Earth will help visualize, monitor, and forecast natural and human activity on the planet. The model will be able to monitor the health of the planet, perform simulations of Earth's interconnected system with human behavior, and support the field of sustainable development, therefore, reinforcing Europe's efforts for a better environment in order to respond to the urgent challenges and targets addressed by the Green Deal. ESA's 2020 Φ-week event kicked off this morning with a series of stimulating speeches on Digital Twin Earth, updates on Φ-sat-1, which was successfully launched into orbit earlier this month, and an exciting new initiative involving quantum computing. The third edition of the Φ-week event, which is entirely virtual, focuses on how Earth observation can contribute to the concept of Digital Twin Earth – a dynamic, digital replica of our planet which accurately mimics Earth's behavior. Constantly fed with Earth observation data, combined with in situ measurements and artificial intelligence, the Digital Twin Earth provides an accurate representation of the past, present, and future changes of our world.
Artificial intelligence (AI), Machine learning, NLP, Robotics, and Automation are increasingly prevalent in all aspects and are being applied to healthcare as well. These technologies have the potential to transform all aspects of health care from patient care to the development and production of new experimental drugs that can have a faster roll-out date than traditional methods. There are numerous research studies suggesting that AI can outperform humans at key healthcare tasks, such as diagnosing ailments. Here is a great example, AI'outperforms' doctors diagnosing breast cancer¹. Artificial intelligence is a collection of technologies that come together form artificial intelligence. Tech firms and startups are also working assiduously on the same issues.
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The health & safety of our attendees & speakers is our primary concern. While this currently proves to be a tricky time for public gatherings, Dataiku is still committed to providing great tech content & facilitating discussions in the data science space. As such, weve decided to pivot towards online webinars via our partner platform, BrightTalk. Google 2:45pm: Q&A Talk Abstract: In this talk, Sanjay will discuss how to perform machine learning using SQL for a variety of model types & the flexibility of using BQML to import & export models. Speaker bio: Sanjay Agravat is a Machine Learning Specialist for Google Cloud based out of Atlanta, GA.