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) …
This is a follow-up tutorial prepared after Part I of the tutorial, Mastering Word Embeddings in 10 Minutes with TensorFlow, where we introduce several word vectorization concepts such as One Hot Encoding and Encoding with a Unique ID Value. I would highly recommend you to check this tutorial if you are new to natural language processing. In Part II of the tutorial, we will vectorize our words and trained their values using the IMDB Reviews dataset. This tutorial is our own take on TensorFlow's tutorial on word embedding. We will train a word embedding using a simple Keras model and the IMDB Reviews dataset.
Errol Baran, the senior vice president for business development and innovation at BBC Global News gives The Drum a peek into Project Songbird, the publisher's AI-powered synthetic voice which'reads' articles from BBC.com. Project Songbird is BBC News' new smart text-to-speech based commercial proposition for its digital properties. The Beeb hopes will allow its audiences to listen to their favorite feature articles hands-free without the need to actively click and browse. Built with cognitive and behavioral integrated tech software, the project will capitalize on consumer demand for audio content and leverage on BBC's editorial coverage. Built with the ability to download in the background, the audio product aims to offer a dynamic advertiser experience.
This branch of artificial intelligence curates your social media and serves your Google search results. Soon, deep learning could also check your vitals or set your thermostat. MIT researchers have developed a system that could bring deep learning neural networks to new – and much smaller – places, like the tiny computer chips in wearable medical devices, household appliances, and the 250 billion other objects that constitute the IoT. The system, called MCUNet, designs compact neural networks that deliver unprecedented speed and accuracy for deep learning on IoT devices, despite limited memory and processing power. The technology could facilitate the expansion of the IoT universe while saving energy and improving data security.
Anyone that has dealt with Machine Learning (ML) understands that data is a fundamental ingredient to it. Given that a great deal of the world's organized data already exists inside databases, doesn't it make sense to bring machine learning capabilities straight to the database itself via predictive AI layers? Database users meet the most important aspect of applied machine learning, which is to understand what predictive questions are important and what data is relevant to answer those questions. Bringing machine learning to those who know their data best can significantly augment the capacity to solve important problems. To do so, we have developed a concept called AI-Tables.
The obvious method is to cross-reference a claim with existing facts to verify whether that claim is true. This is accurate and highly explainable, but it also comes at some significant costs. Not only does it assume that the claim is checkable (e.g., what if a world leader decided to say "the entire universe was created last Thursday"), but it also requires a huge database of evidence because the AI needs sufficient evidence on so many different areas in order to be able to verify an acceptable proportion of claims. The alternate method is to use the context of a claim to try to make an assumption on whether or not it's true. For example, if the claim was made by The Onion, we could probably assume it's not true.
From self-driving cars to SIRI, artificial intelligence (AI) is progressing rapidly, but where's it all headed? Well, the thing to note is that there's definitely a divergence rather than a convergence of intelligence between man and machine. Artificial intelligence is a capacity for logic that is demonstrated by machines, in contrast to the heuristic natural intelligence displayed by animals. The question is, can the former ever become equivalent to the latter? I guess to answer this we must first understand what AI really is.
Corporate contact centers are embracing big data to offer an improved and more customized customer experience. Also, presently, contact centers are digitizing and collecting each customer interaction that happens by means of telephone, social media, email, text or even face to face. Following this move into big data, contact centers are utilizing speech analytics to take their products, processes and customer service efforts step ahead. Voice analytics is the process of digitally analyzing interactions between customers and agents. What's more, despite the fact that the innovation has been around for over 10 years, late headways in digitalization, machine learning and artificial intelligence (AI) have made it all the more remarkable and have empowered contact centers to change piles of data into real-time insights.
The artificial intelligence applied research startup Abzu identifies false news with its proprietary QLattice. In the latest Reuters Institute Digital News Report, less than four in ten people said that they trust most news most of the time (that's 38% surveyed in January 2020, a fall of four percentage points from 2019)¹. Today's global crises make it all too obvious the necessity for dependable and factual journalism, yet we are exposed to a continuum of information authored by innumerable sources with debatable credentials. Slaves to our most basic emotions -- fear, disgust, and surprise² -- we are inflamed by an addictive negative feedback loop of our own creation. We crave the truth, but data shows we force-feed ourselves lies.
These people may look familiar. They may look like users you've seen on Facebook, Twitter or Tinder, or maybe people whose product reviews you've read on Amazon. They look stunningly real at first glance, but they do not exist. They were born from the mind of a computer. There are now businesses that sell fake people.
This week we'll celebrate Thanksgiving in the US, and nostalgia will be all over TV screens and Peacock resurrects Saved by the Bell with a cast that includes new younger actors and several of the stars from the original show. Other throwbacks include Mad Max on Ultra HD Blu-ray and a Buck Rogers box set, but for something newer you can check out Peninsula, a sequel to the excellent Korean zombie movie Train to Busan as it arrives on Ultra HD Blu-ray. Netflix's latest feature film is Mosul, along with its Hillbilly Elegy movie. Criterion is also releasing a special edition of Netflix's Martin Scorsese feature The Irishman, however it's sadly only available in 1080p Blu-ray without the benefit of 4K and Dolby Vision HDR. For an all-new option, try Superintelligence on HBO Max, where Melissa McCarthy stars as a woman chosen by an all-powerful AI for surveillance via her various connected devices.