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) …
In this tutorial, you will learn step-by-step how to implement a poker bot in Python. First, we need an engine in which we can simulate our poker bot. It also has a GUI available which can graphically display a game. Both the engine and the GUI have excellent tutorials on their GitHub pages in how to use them. The choice for the engine (and/or the GUI) is arbitrary and can be replaced by any engine (and/or GUI) you like.
Google Home and the Amazon Echo have new competition. Baidu, which runs China's most popular search engine, has produced the Raven H, a voice-activated speaker that runs on an artificial intelligence platform. The Raven H is the first product in Baidu's upcoming AI plan, following its acquisition in earlier this year of Beijing-based smart home startup, Raven. 'Humans & machines have been interacting w/ one another for years, but raven H aims to create a world in which this interaction is seamless.' If anything, the new speaker's design looks like none of the competition, and appears to be able to flip up to face the user, when activated.
Since 1996, most cars made for sale in the US have had what's known as an on-board diagnostics, or OBD-II, port. Located under the dashboard, this opening allows mechanics and manufacturers to access data about the vehicle's mileage and current state of health. By plugging a specialized sensor into this port and downloading an app to interpret its findings, you can bypass the pros and tap into this on-board information yourself. You can't go wrong with Dash, which provides both the free app (available for iOS and Android) and the hardware you'll need. In fact, it offers a variety of sensors, ranging in price from $10 to $99.
Last fall, Google Translate rolled out a new-and-improved artificial intelligence translation engine that it claimed was, at times, "nearly indistinguishable" from human translation. Jost Zetzsche could only roll his eyes. The German native had been working as a professional translator for 20 years, and he'd heard time and time again that his industry would be threatened by advances in automation. Every time, he'd found, the hype was overblown--and Google Translate's makeover was no exception. It certainly wasn't the key to translation, he thought.
Earlier this year, we open-sourced a research project called AirSim, a high-fidelity system for testing the safety of artificial intelligence systems. AirSim provides realistic environments, vehicle dynamics and sensing for research into how autonomous vehicles that use AI that can operate safely in the open world. Today, we are sharing an update to AirSim: We have extended the system to include car simulation, which will help advance the research and development of self-driving vehicles. The latest version is available now on GitHub as an open-source, cross-platform offering. The updated version of AirSim also includes many other features and enhancements, including additional tools for testing airborne vehicles.
In this post, we learn about building a basic search engine or document retrieval system using Vector space model. This use case is widely used in information retrieval systems. Given a set of documents and search term(s)/query we need to retrieve relevant documents that are similar to the search query.
Summary: This is the first in a series about Chatbots. In this first installment we cover the basics including their brief technological history, uses, basic design choices, and where deep learning comes into play. In subsequent articles we'll describe in more detail about how they are actually programmed and best practice dos and don'ts. According to Chatbot.org there are currently 1,331 active chatbots in the world. That's a lot for a technology that didn't even exist two or three years ago.
"Today, AI augments what we do, but in the future you'll see decisions made by (AI) entities," said Bernt Wahl, executive director of the Brain Machine Consortium. Wahl argues a logical progression of technological advances will result in smarter, more proactive AI systems. "With the web we created all these search engines and collected all this information," said Wahl, adding that systems like IBM's Watson now help determine whether all that information being collected is accurate. "In the future we'll have a'wisdom engine' that can take the knowledge we know is accurate and make decisions based on that,' he said. Jack Berkowitz, vice president of products and data science for Oracle's Adaptive Intelligence effort said AI has proven useful in helping companies filter the massive amounts of new data they're accumulating.
With Google turning to artificial intelligence to power its flagship search engine business, has the SEO industry been left in the dust? The old ways of testing and measuring are becoming antiquated, and industry insiders are scrambling to understand something new -- something which is more advanced than their backgrounds typically permit. The fact is, even Google engineers are having a hard time explaining how Google works anymore. With this in mind, is artificial intelligence changing the SEO industry for better or worse? And has Google's once-understood algorithm become a "runaway algorithm?"
With the rise of Big Data has come the accompanying explosion in roles that in some way involve data. Most who are in any way involved with enterprise technology are at least familiar with them by name, but sometimes it's helpful to look at them through a comprehensive lens that shows us how they all fit together. In understanding how data roles mesh, think about them in terms of two pools: one is responsible for making data ready for use, and another one that puts that data to use. The latter function includes the tightly-woven roles of Data Analysts and Data Scientist, and the former includes such roles as Database Administrator, Data Architect and Data Governance Manager. A car is only as good as its engine, and according to PC Magazine the Database Administrator (DBA), is "responsible for the physical design and management of the database and for the evaluation, selection and implementation of the DBMS."