Images and videos are critical for ensuring user engagement on the web. For instance, on a retail website, images of a product from different angles or a 360-degree video of the product can lead to higher conversion rates. For a news website, users are more likely to read articles with visual media accompanying the content. It has been reported that posts that include images produce a 650-percent higher user-engagement rate than text-only posts. Communicating intent to users through contextual images and videos is important.

AI-as-a-service (AIaaS) is becoming increasingly popular, with the likes of Amazon AI (which includes Rekognition), Clarifai, Google Cloud Vision, IBM Watson, and Microsoft Cognitive Services gaining traction. One of the main economic drivers within AIaaS is the prevalence of microtransactions. Visual cognition startup CloudSight has announced that it will now support Bitcoin Lightning payments, accepting microtransactions to gather and share visual knowledge to allow AI to learn from AI. CloudSight utilizes data to train deep learning neural networks to automatically caption images. With a database of over half a billion images and all the associated metadata, CloudSight says its image recognition API is one of over 30 patents pending worldwide. The incorporation of Bitcoin Lightning means that microtransactions between devices can happen at great speed, unlocking an exchange of information that was previously difficult.

SAN FRANCISCO: There's a dirty little secret about artificial intelligence: It's powered by hundreds of thousands of real people. From makeup artists in Venezuela to women in conservative parts of India, people around the world are doing the digital equivalent of needlework _drawing boxes around cars in street photos, tagging images, and transcribing snatches of speech that computers can't quite make out. Such data feeds directly into machine learning'' algorithms that help self-driving cars wind through traffic and let Alexa figure out that you want the lights on. These repetitive tasks pay pennies apiece. But in bulk, this work can offer a decent wage in many parts of the world _ even in the U.S.

There's a dirty little secret about artificial intelligence: It's powered by an army of real people. From makeup artists in Venezuela to women in conservative parts of India, people around the world are doing the digital equivalent of needlework -- drawing boxes around cars in street photos, tagging images, and transcribing snatches of speech that computers can't quite make out. Such data feeds directly into "machine learning" algorithms that help self-driving cars wind through traffic and let Alexa figure out that you want the lights on. These repetitive tasks pay pennies apiece. But in bulk, this work can offer a decent wage in many parts of the world -- even in the U.S.

There's a dirty little secret about artificial intelligence: It's powered by hundreds of thousands of real people. From makeup artists in Venezuela to women in conservative parts of India, people around the world are doing the digital equivalent of needlework -- drawing boxes around cars in street photos, tagging images, and transcribing snatches of speech that computers can't quite make out. Such data feeds directly into "machine learning" algorithms that help self-driving cars wind through traffic and let Alexa figure out that you want the lights on. These repetitive tasks pay pennies apiece. But in bulk, this work can offer a decent wage in many parts of the world -- even in the US.

There's a dirty little secret about artificial intelligence: It's powered by an army of real people. From makeup artists in Venezuela to women in conservative parts of India, people around the world are doing the digital equivalent of needlework --drawing boxes around cars in street photos, tagging images, and transcribing snatches of speech that computers can't quite make out. Such data feeds directly into "machine learning" algorithms that help self-driving cars wind through traffic and let Alexa figure out that you want the lights on. These repetitive tasks pay pennies apiece. But in bulk, this work can offer a decent wage in many parts of the world -- even in the U.S.

As humans, we know that the picture in the header of this blog is that of a broken coffee cup. We've been conditioned, over time, to recognize the visual cues – the cup's edges, the handle, the color of the spilled liquid, and even the logo printed on the side. Our brains add it all up and within milliseconds come to the correct conclusion. But what if you've never seen a broken coffee cup before? The CloudSight.ai story starts with the problem statement: How do you go beyond traditional image recognition to deliver a deep learning-powered service that helps organizations tap new meaning from their data?

This popular internet meme demonstrates the alarming resemblance shared between chihuahuas and muffins. These images are commonly shared in presentations in the Artificial Intelligence (AI) industry (myself included). But one question I haven't seen anyone answer is just how good IS modern AI at removing the uncertainty of an image that could resemble a chihuahua or a muffin? For your entertainment and education, I'll be investigating this question today. Binary classification has been possible since the perceptron algorithm was invented in 1957.

You've probably seen this internet meme demonstrating the alarming resemblance of chihuahuas and muffins. Everyone in the AI industry (including myself) loves putting the image in their presentations. But, one question I haven't seen anyone answer rigorously is: just how good IS modern AI at disambiguating between a chihuahua and a muffin? For your entertainment and education, I'll be investigating this question today. Binary classification has been possible ever since the perceptron algorithm was invented in 1957.

Generally speaking, Computer Science degrees tend to be a little bit behind the times. Many schools require syllabuses to be planned months, if not years in advance, meaning that both undergraduates and postgraduates miss out on the cutting edge of tech. But I've noticed that many schools are catching up and are now teaching in-vogue topics like artificial intelligence and machine learning, even at an undergraduate level. For the Los Angeles-based Cloudsight, this represents a golden opportunity to put its product front-and-center to a new generation of aspirant computer scientists. As a result, it has announced that its computer vision API will soon be free for educational institutions.