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) …
Siri means a secret in Swahili and in Norse, a beautiful woman who leads you to victory. To those of us in Appleland using the voice-controlled personal assistant, it stands for "Speech Interpretation and Recognition Intelligence." And when you put Siri to work, she can move productivity mountains. I use Siri to give me directions while driving with Apple CarPlay. I ask her to remind me to stop by the grocery store on my Apple Watch.
Amazon CodeGuru (Preview) is a service launched at AWS re:Invent 2019 that analyzes the performance characteristics of your application and provides automatic recommendations on ways to improve. It does this by profiling your application's runtime (with CodeGuru Profiler) and by automatically reviewing source code changes (with CodeGuru Reviewer). For more information, see What Is Amazon CodeGuru Profiler? This post gives a high-level overview of how CodeGuru Profiler works, common ways to use it, and how to improve your understanding of your application's performance in production. It assumes a basic knowledge of the JVM (Java Virtual Machine) and related concepts such as threads and call stacks.
We blur the lines of reality with deep learning and next-generation computer graphics. We've created Xpression, a smartphone app which uses deep learning, allowing you to manipulate videos by imprinting your facial movements into a video of another person. Watch the video below to learn about the app. Just how have we done this? Using training data collected by a facial scanning system consisting of 50 cameras and polarized LED lights.
In less than 3 hours, you can understand the theory behind modern artificial intelligence, and apply it with several hands-on examples. This is machine learning on steroids! Find out why everyone's so excited about it and how it really works – and what modern AI can and cannot really do. At the end, you will have a final challenge to create your own deep learning / machine learning system to predict whether real mammogram results are benign or malignant, using your own artificial neural network you have learned to code from scratch with Python. You will need some familiarity with Python and linear algebra to follow along, but if you have that experience, you will find that neural networks are not as complicated as they sound.
The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last 10 years. The increasing availability of soil data that can be efficiently acquired remotely and proximally, and freely available open-source algorithms, have led to an accelerated adoption of ML techniques to analyse soil data. Given the large number of publications, it is an impossible task to manually review all papers on the application of ML in soil science without narrowing down a narrative of ML application in a specific research question. This paper aims to provide a comprehensive review of the application of ML techniques in soil science aided by a ML algorithm (latent Dirichlet allocation) to find patterns in a large collection of text corpora. The objective is to gain insight into publications of ML applications in soil science and to discuss the research gaps in this topic.
Institutions that include everyone understand that great benefit comes from seeing complex issues in many different ways. The most life-changing, rapid, and one-off decisions people must make are those to do with their health, and the health of their loved ones. Here too, the benefits of diversity are well understood. In medicine, there is a culture of "second opinions" – you can always ask another doctor for their opinion on a choice. This is acknowledged as a great strength of the medical community; indeed, the seeking of diverse (even possibly contradictory) opinions is actively supported by professionals realistic and humble enough to accept that there may not be one single right answer.
New technologies can bring more threats to corporate security, but because they increase information technology connectivity and vulnerabilities, they can also be used to fight against these problems. Cybersecurity software maker Imperva Inc. uses artificial intelligence and machine learning to do threat analytics and predictive attack research for its clients. "We are fighting against technologies like AI," said Pam Murphy (pictured), chief executive officer of Imperva. "But we are also using those technologies to help us decide where we need to continue to add capabilities to stop [cyberattacks]." Murphy spoke with Jeff Frick, host of theCUBE, SiliconANGLE Media's mobile livestreaming studio, during the RSA Conference in San Francisco.
Vantagepoint AI (www.vantagepointsoftware.com), is the software company that developed the first artificial intelligence (A.I.) trading software in the world available to retail investors and traders. This highly effective software, used by traders in over 120 countries successfully predicted the current market meltdown on February 18, 2020 by utilizing Artificial Intelligence. Vantagepoint traders had the insight to side-step the sudden selloff in equity prices as stock valuations tumbled by more than $2.5 trillion during the final week of February, wiping out many traders' years of hard-earned capital. VantagePoint Software's AI identifies global markets' hidden influencing factors and does advanced forms of linear and non-linear pattern recognition using patented intermarket analysis. The technology then employs a second patented process to generate predictive technical indicators capable of forecasting market changes up to 3 days in advance.
Facebook just expanded 3D photo posting to phones that don't actually capture depth data. The announcement was made moments ago on the Facebook AI blog, where the company's engineers went into depth on how exactly they pulled this off. "This advance makes 3D photo technology easily accessible for the first time to the many millions of people who use single-lens camera phones or tablets," reads the announcement. "It also allows everyone to experience decades-old family photos and other treasured images in a new way, by converting them to 3D." Facebook is obviously not the first to use AI to infer 3D data from a 2D image. Google has been doing it with the Pixel phones for years, and the LucidPix app we wrote about last month does much the same thing.
The IBM Data Asset eXchange (DAX) is an online hub for developers and data scientists to find free and open data sets under open data licenses. A particular focus of the exchange is data sets under the Community Data License Agreement (CDLA). For developers, DAX offers a trusted source for open data sets for artificial intelligence (AI). These data sets are ready to use in enterprise AI applications and are supplemented with relevant notebooks and tutorials. Also, DAX offers unique access to various IBM and IBM Research data sets and offers various integrations with IBM Cloud and AI services.