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) …
As many of you will know, artificial intelligence is a passion of mine. I believe in its potential to boost productivity, solve problems, and make the world a better place. For me, it's more than just talk; I am building an entire business around AI and I stand with the users and creators of AI who see its potential and the exciting places it can take us. But not everyone is like us. Despite growing body evidence to the contrary, many people still see AI as a dark force; a development to be feared instead of celebrated.
"What in the name of Paypal and/or Palantir did you just say about me, you filthy degenerate? I'll have you know I'm the Crown Prince of Silicon Valley, and I've been involved in numerous successful tech startups, and I have over $1B in liquid funds. I've used that money to promote heterodox positions on human enhancement, control political arenas, and am experimenting with mind uploading. I'm also trained in classical philosophy and was recently ranked the most influential libertarian in the world by Google. You are nothing to me but just another alternative future. I will wipe you out with a precision of simulation the likes of which has never been seen before, mark my words."
Researchers at Facebook AI recently introduced and open-sourced a new framework for self-supervised learning of representations from raw audio data known as wav2vec 2.0. The company claims that this framework can enable automatic speech recognition models with just 10 minutes of transcribed speech data. Neural network models have gained much traction over the last few years due to its applications across various sectors. The models work with the help of vast quantities of labelled training data. However, most of the time, it is challenging to gather labelled data than unlabelled data.
Understanding individuals' feelings are fundamental for organizations since clients can communicate their feelings and sentiments more transparently than ever before. By automatically analyzing customer feedback, from study reactions to social media discussions, brands can listen mindfully to their clients, and tailor products and services to address their issues. Sentiment analysis is a machine learning method that recognizes polarity (for example a positive or negative thought) within the text, whether a whole document, paragraph, sentence, or clause. Marketing is ending up being one of the artworks most disrupted by the digital revolution. A lot to the aversion of customary marketing proponents and maybe to the pleasure of technologists, it is presently a lot about codifying the whole knowledge chain – catching the abundance of digital data, sorting out it, applying algorithms to process it and taking care of back noteworthy decisions to different functions– all in real-time, with end to end automation, and at lightening quick speed.
Today any smartphone can generate 3D Photos, but the popular AI-powered effect is actually fairly new. It was back in 2018 that Facebook first introduced a machine learning-based 3D photo feature that allowed users to generate an immersive 3D image from normal 2D pictures. Leveraging the dual-lens "portrait mode" capabilities that had recently become available in smartphones, the feature quickly gained traction and began evolving. This June, a research team from Virginia Tech, National Tsing Hua University and Facebook designed an algorithm that generates even more immersive 3D photos from a single RGB-D (colour and depth) image. And in August, Facebook democratized the technique with a novel system able to generate 3D photos even on low-end mobile phones or without an Internet connection. Facebook isn't the only tech giant using AI to generate 3D photos -- in recent months, Google has introduced its own AI techniques for generating 3D photos from 2D images.
Hostile and hateful remarks are thick on the ground on social networks in spite of persistent efforts by Facebook, Twitter, Reddit and YouTube to tone them down. Now researchers at the OpenWeb platform have turned to artificial intelligence to moderate internet users' comments before they are even posted. The study conducted by OpenWeb and Perspective API analyzed 400,000 comments that some 50,000 users were preparing to post on sites like AOL, Salon, Newsweek, RT and Sky Sports. Some of these users received a feedback message or nudge from a machine learning algorithm to the effect that the text they were preparing to post might be insulting, or against the rules for the forum they were using. Instead of rejecting comments it found to be suspect, the moderation algorithm then invited their authors to reformulate what they had written.
More and more is happening…. More connectivity occurs now in a calendar year than occurred in a million years a billion years ago. So somehow as we approach the present, we find ourselves in an ever denser realm of activity, interrelationship, connectivity, and the result of this is more of the same: producing a shrinking globe, ever more immersive technologies, dissolution of political, social, gender, class boundaries, of all sorts…. We're about to become unrecognizable to ourselves as a species. And then there's that new Netflix docudrama, The Social Dilemma, that, in the words of one review, "examines the various ways social media and social networking companies have manipulated human psychology to rewire the human brain and what it means for society in general."
The market for AI (artificial intelligence) technologies is going to expand tremendously in the next decade. Grand View Research says the global AI market will reach $733.7 billion by 2027, growing at a CAGR (compound annual growth rate) of 42.2%. One of the many sectors that will increasingly look to leverage AI technologies between now and 2027 (and beyond) is first response. In fact, in some cases, the first-response industry is already engaged in piloting AI technologies for use on the front lines. What AI-related innovations are to come, and how will they make first responders' jobs easier?
Is social media ruining the world? The common denominator of all these phenomena is that they're fueled in part by our seemingly innocuous participation in digital social networking. But how can simple acts like sharing photos and articles, reading the news, and connecting with friends have such destructive consequences? These are the questions explored in the new Netflix docu-drama The Social Dilemma. Directed by Jeff Orlowski, it features several former Big Tech employees speaking out against the products they once upon a time helped build.
The economic recession that follows as a consequence of the Covid-19 crisis and in particular the demise of certain sectors of the economy (physical retail, hospitality sector, etc) means that there will be greater pressure on politicians around the world to consider how to stimulate GPD growth in the post-pandemic world. However, there are also increasing pressures on politicians to combat the threat posed by Climate Change. Are the desired objectives of GDP and employment growth as well as reducing pollution at odds with each other? What if there is a pathway to GDP growth with the creation of new jobs and yet at the same time we are able to reduce emissions of Green House Gasses (GHGs)? A report entitled "How AI can enable a sustainable future" by PWC and commissioned by Microsoft (lead authors Celine Herweijer of PWC and Lucas Joppa of Microsoft) estimates that using AI for environmental applications across four sectors – agriculture, water, energy and transport. The report estimated that such applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual.