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) …
"I never forget a face", "She's got an honest face", "You could see it in his face", and "She looks young for her age" are just a few of the often-used phrases suggesting that faces are important for our interactions with other people and what we think we know about them. But can people really remember faces as well as they think they do, and can we really tell someone's age from their face? Or can artificial intelligence (AI) do it better? And can we really tell if someone is trustworthy just by looking at their face? Research shows that humans exhibit a wide range of facial recognition abilities.
Humans have always been thrilled with the concept of human-like robots and Artificial Intelligence (A.I.). Hollywood movies and science fiction have perhaps inspired several scientists to start working towards this direction. Although the AI bubble has burst many times, significant developments and breakthroughs are now renewing public interest in this field. In 2017, Gartner placed general AI at the stage of early adoption in its hype cycle. It also placed deep learning and machine learning technologies at the peak of this hype cycle.
Machine-learning technology powers many aspects of modern society: from web searches to content filtering on social networks to recommendations on e-commerce websites, and it is increasingly present in consumer products such as cameras and smartphones. Machine-learning systems are used to identify objects in images, transcribe speech into text, match news items, posts or products with users' interests, and select relevant results of search. Increasingly, these applications make use of a class of techniques called deep learning. Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data. In a simple case, you could have two sets of neurons: ones that receive an input signal and ones that send an output signal.
Are you more of a Ronaldo or a Kane? A new AI-powered tool, which uses facial recognition technology to find your football doppelganger, will help you find out. The artificial Intelligence will attempt to match your likeness with one of the 736 professional sportsmen currently competing in the World Cup in Russia. You can test the hilarious tool below – or via this link. To test the'Find Your World Cup Twin' tool, hit the Upload Image button at the bottom of the screen.
Amongst all this hype and bandwagon jumping on Artificial Intelligence (AI), Machine Learning (ML), and Cognitive Technologies is also a sense of unease. How is it that a technology that has roots going back as far as the beginnings of computing is suddenly now the hot "must have" technology that's powering ever-more dramatic amounts of money being pumped into a few skyrocketing startups? The industry has gone through two major waves of AI development and promotion with their own periods of sky-high hype only to sink dramatically back to earth once people realized the limitations of what surely was being hyped as being on the cusp of sentience. And so here we are again, in the "summer" of this wave's AI adoption wondering if this will all last, or if billion-dollar unicorns are being funded in an environment that's sure to pull back the reins of overinflated expectations. As discussed in previous newsletters, podcasts, and research on this subject, an AI Winter is a period of declined interest, funding, research, and support for artificial intelligence and related areas -- in essence, a "chill" on the growth of the industry.
Apple Inc.'s next breakthrough may be powered by Augmented Reality (AR). A recent report by Bloomberg outlines Apple's'big step' towards the AR space through talented hires and acquisitions in the related field. According to the report, with the goal of making smart glasses, in the short term, Apple's AR features may first show up on the iPhone. Bloomberg's report comes after its November story published last year, which highlighted Apple's wearable expansion into'digital glasses'. The AR industry is gaining momentum and could be a huge global market worth $90 million by 2020.
Are you ready for R2D2 and C3PO to take over? No, Yes, Maybe or Does not compute? Ready or not, Machine Learning and Artificial Intelligence (AI) are steadily taking over every aspect of routine life including automation in the field of IP. In all aspects of life, the AI revolution is here to help us, even though the solution is removing the human broker from the workflow. Over the last 20 years, Machine Learning and AI have helped to change and shape the IP patent information industry.
In today's blog post you are going to learn how to perform face recognition in both images and video streams using: As we'll see, the deep learning-based facial embeddings we'll be using here today are both (1) highly accurate and (2) capable of being executed in real-time. To learn more about face recognition with OpenCV, Python, and deep learning, just keep reading! Inside this tutorial, you will learn how to perform facial recognition using OpenCV, Python, and deep learning. We'll start with a brief discussion of how deep learning-based facial recognition works, including the concept of "deep metric learning". From there, I will help you install the libraries you need to actually perform face recognition. Finally, we'll implement face recognition for both still images and video streams.
"Humans tend to overestimate technology in the short term but underestimate it in the long term," said Tom Foster, editor at large for Inc. magazine, during a panel he moderated on innovations in machine learning at South by Southwest (SXSW) in March. Artificial intelligence (AI) was a recurring theme across panels at SXSW 2018's Interactive Conference held in Austin, Texas. The topic was particularly popular in tracks titled "Intelligent Future" and "Startup & Tech Sectors." Many AI experts marveled at recent advances in the technology while pondering its future. "I've been working in AI for now more than 30 years and in the past eight years there are things that have occurred that I never thought would happen in my lifetime," said Adam Cheyer, co-founder of Viv Labs, during a discussion on innovations in AI.
There is no doubt that the artificial intelligence (AI) phenomenon will have a profound impact on businesses large and small this year; that part is easy to predict. What impact it will have, and whether this is a good or a bad thing, is harder to tell. Let's start with the basics of AI. "In our broad definition, AI is a collective term for computer systems that can sense their environment, think, learn, and take action in response to what they're sensing and their objectives. Forms of AI in use today include, among others, digital assistants, chatbots and machine learning. AI is already at work in industry (from sport and manufacturing to investing and healthcare).