Engineers have always tried to give the robot the gift of sight. So, they have to replicate the human vision process with computers, algorithms, cameras and more. In the DIY area, a Raspberry Pi is the queen of prototyping platforms. So, why not to use it in computer vision applications. The projects started coming fast and furious for navigation, localization, recognition, classifications, monitoring, reading and more.
This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. Since the early days of artificial intelligence, computer scientists have been dreaming of creating machines that can see and understand the world as we do. The efforts have led to the emergence of computer vision, a vast subfield of AI and computer science that deals with processing the content of visual data. In recent years, computer vision has taken great leaps thanks to advances of deep learning and artificial neural networks. Deep learning is a branch of AI that is especially good at processing unstructured data such as images and videos.
"Computer vision" has a decidedly sci-fi ring, so it's no surprise the idea of smart devices becoming all-seeing tools has captured people's imaginations. Yet the true potential of the tech is held back by a widespread misunderstanding of what great applications look like and what they can achieve. Where did computer vision come from? It's the product of a proliferation of cheap, high-quality cameras, which has expanded the scope for imagery captured in public, private, and commercial domains. At the same time, advances in machine learning and deep learning technology are allowing us to transform those images into digital signals that support a wide range of actions.
Artificial intelligence and the application of it across nearly every aspect of our lives is shaping up to be one of the major step changes of our modern society. Today, a startup that wants to help other companies capitalise on AI's advances is announcing funding and emerging from stealth mode. Allegro.AI, which has built a deep learning platform that companies can use to build and train computer-vision-based technologies -- from self-driving car systems through to security, medical and any other services that require a system to read and parse visual data -- is today announcing that it has raised $11 million in funding, as it prepares for a full-scale launch of its commercial services later this year after running pilots and working with early users in a closed beta. The round may not be huge by today's startup standards, but the presence of strategic investors speaks to the interest that the startup has sparked and the gap in the market for what it is offering. It includes MizMaa Ventures -- a Chinese fund that is focused on investing in Israeli startups, along with participation from Robert Bosch Venture Capital GmbH (RBVC), Samsung Catalyst Fund and Israeli fund Dynamic Loop Capital.