AI might be a hot topic but you'll still need to justify those projects. UPS and FedEx anticipate delivering close to 1 billion packages in the next few weeks. Moving that much merch quickly and accurately would be impossible without the recent automation revolution in the logistics industry. Robotics technology developed by Kiva has enabled Amazon to fulfill orders same-day in many locations. Though human workers still play a vital (albeit controversial, according to recent reports) role in the picking, packing, and palletizing that go into dispatching goods to your doorstep, there can be no question that we're getting ever-closer to a so-called lights-out shipping warehouse, one in which all the workers are robots.

That this book is slightly dated in a very dynamic field seems to matter less than I expected. It covers the basic issues, reviews achievements and goals, and is structured well. As a collection by different authors who may not have written their pieces to be collated into a volume by Scientific American, the book works but is patchy. I note that Minsky seems to imply that genes do not have repair mechanisms - untrue, but even this great man admits to off days, although SA's editing role should have clarified this point (as a collection of articles I assume it was even twice published). Similarly, sloppy logic/wording when explaining about engineering another hundred human genes to improve longevity detracts slightly from an otherwise delightful article. Minsky's statement "Might not such people, who feel they might not have much to lose (when they die), be dangerous?" is a gem that applies well beyond this topic.

The late Herbert Simon was a veritable renaissance man. His autobiography, "Models of My Life," discusses the single thread that underlined all of his intellectual conquests in artificial intelligence, sociology, cognitive science, psychology and economics. This one thread, animated by philosophical positivism and ripe scientific thirst, was his deep obsession with modeling and researching decision-theoretic behavior. It's interesting to note that even though decision theory (how intelligent agents percieve and act upon choices amid various modalities) serves as the impetus for Simons work, he uses "Models" instead of "Model" in the book's title. For you see, beautifully fitting of his memoir, this book delves into how Simon's one passion was his "heuristic" in choosing which of many paths he could have taken througout his life. The upshot: Simon's own life emulated the heuristic search (in AI) that he helped invent!

If you ask 100 people for the definition of "artificial intelligence," you'll get at least 100 answers, if not more. At AWS, we define it as a service or system which can perform tasks that usually require human-level intelligence such as visual perception, speech recognition, decision making, or translation. On this new AWS blog, we'll be covering these areas and more, with in-depth technical content, customer stories, and new feature announcements. The challenges related to building sophisticated AI systems center mostly around scale: the datasets are large, training is computationally hungry, and inferring predictions can be challenging to do at scale or on lower-power and mobile devices. Customers have been using AWS to solve these general problems for years, and the ability to be able to access storage, GPUs, CPUs, and IoT services on demand has emerged as a perfect fit for intelligent systems in production.

According to analyst Forrester, artificial intelligence (AI), big data and analytics will increase businesses' access to data, broaden the types of data that can be analysed, and raise the level of sophistication of the resulting insight. For 2017, Forrester expects investment in AI to triple. Read about the new best practices for the ERP systems and how to tackle the growth of ERP integrations. This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent.

If the basics of retail are elementary, then it should be no surprise that a technology named Watson is leading what may be one of the biggest trends in 2017. Watson is the name of an artificial intelligence technology (AI) by IBM; many may remember Watson for its $1 million winning streak on "Jeopardy." Today, several major retailers -- from Macy's to 1-800-Flowers.Com -- are using or testing the supercomputer's cognitive computing capabilities to more acutely predict (and serve) customer wishes. Most recently, Staples announced plans to implement Watson technology to bring to life its Easy Button. Infused with the technology, the button can now take Staples orders by voice, text, email, messaging app or mobile app.

We are excited to announce that an AWS Deep Learning AMI for Ubuntu is now available in the AWS Marketplace in addition to the Amazon Linux version. The AWS Deep Learning AMI, now available on AWS Marketplace, lets you run deep learning in the Cloud, at any scale. Launch instances of pre-installed, open source deep learning frameworks, including Apache MXNet, to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques. The AWS Deep Learning AMI lets you create managed, auto-scaling clusters of GPUs for large-scale training, or run inference on trained models using the latest versions of MXNet, TensorFlow, Caffe, Theano, Torch, and Keras. With the addition of an Ubuntu version, you have the choice to run on the operating system of your choice.

Employees stand outside the new Amazon Go grocery store in Seattle, Washington, U.S., on Tuesday, Dec. 6, 2016. Inc. unveiled technology that will let shoppers grab groceries without having to scan and pay for them -- in one stroke eliminating the checkout line. Are no-checkout stores like Amazon Go going to become common-place by 2025? Why or why not? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. There is little doubt, many if not all of the concepts from the Amazon Go store will be adopted by A-level retailers over the next 5 years.

We want to hear how you would harness machine learning to have a truly positive effect on society. The ability to recognise patterns has been fundamental in the progression of modern civilisation: from sailors using the night sky to navigate the oceans, to scientists observing natural phenomena to construct theories of the world. With the advent of powerful computers and large datasets, these days machine learning (ML) is allowing computers to recognise patterns and learn from data like never before. You can already see this in the world around you: online retailers suggest products you might be interested in, your phone can translate spoken words to text on the screen and cars are learning to drive themselves. This year we've expanded the competition and encourage students aged 16 to apply.