Over the course of our last few posts on Artificial Intelligence , we’ve seen how artificial Intelligence applications affect the world of personal and business efficiency, marketing and customer communication. So does artificial intelligence work when it comes to developers? How do developers and big software build and use artificial intelligence to improve the world of AI? We took a closer look and here’s what we found.
Who is running Artificial Intelligence today?
When it comes to AI, companies like Google, Facebook, Twitter, Apple and Microsoft are racing to acquire smaller AI startups and create the ultimate sticky experience powered by artificial intelligence that will have users hooked. It looks as though whoever captures the AI space, will capture customer attention as well as large chunks of revenue and market share. Facebook’s AI Research, Google Brain and Google Deepmind are all examples of AI algorithms that learn from themselves and get better at what they do over time.
The problem is: These algorithms are taught to do the niche biddings of Facebook, Google or whichever company that comes out on top. Sure, Google is already creating self-driving cars and Facebook has invested in bots and virtual reality companies – but they aren’t going to be able to create immediate changes in every industry where artificial intelligence applications are needed.
And that is why we need Artificial Intelligence for Developers
For AI to truly make a difference around the world and reach industries, geographies and demographics that it hasn’t yet, developers need to understand artificial intelligence applications and work on bringing them to fruition across the board. As meta as it may sound, developers need to develop AI that other developers can work on and use to take forward their ideas and apps. This is an essential factor that is necessary to exploit artificial intelligence and its potential to solve many of the pressing issues humanity faces today.
Image: CNN Money
Artificial intelligence companies have opened up their algorithms for developers to use to create new applications and products. This is a great way to encourage developers to explore this nascent area which is poised to be worth close to $9.2 billion in the next 5 years. We took at the look at the areas and tools which developers can look to to start building AI frameworks and applications.
Cognitive Architecture is an attempt to summarize and compute the psychology and cognitive abilities of a human mind into a computer model. These architectures maybe built along the premise that the mind functions like a computer, whereas many turn over this assumption or use other factors along with it. If humans are looking to begin work on AI, especially to create a more widespread general artificial intelligence applications rather than ones that performs niche tasks, a cognitive architecture framework is a place to start.
OpenCog: An open-source software project whose aim is to create an open-source framework for artificial general intelligence (AGI).
Soar: A general cognitive architecture for developing systems that exhibit intelligent behavior.
Open Source Platforms
The open source movement is all about opening up code frameworks and sharing them with other developers to encourage innovation, disruption and neutrality of information exchange. Open source providers only ask developers to mention modifications they make to systems and code so everyone using the source code can learn and have the option of using it. Artificial intelligence applications can be built using these frameworks, with modificiations and improvements that inspire the next generation of AI developers.
Protege: A free, open-source ontology editor and framework for building intelligent systems.
Seldon: An open, enterprise-grade machine learning platform that adds intelligence to organizations.
OpenCV: Open-source computer vision, a library of programming functions aimed mainly at computer vision.
Teach your application, make it cooler.
Artificial Intelligence applications and editors need to be able to interact with objects, systems, databases to learn from them and get better at tackling problems in the real world. These databases and systems such as maps, voice recordings, images, video clips and text provide the raw material and data that will form the core of any artificial intelligence systems capabilities.
Jasper: Want to control a machine with your voice? Use Jasper to build always-on, voice-controlled applications
Clarifai: Image and Video recognition tool with a REST API that could be integrated with your preferred language along with a Python, Java and Node.js API. Their service is free for up to 5000 uses a month.