Since last few years, Artificial Intelligence has gone from a science-fiction dream to a crucial part of our everyday lives. We use AI systems to interact with our mobiles through IoT devices like Siri and Alexa etc. Cars like Tesla integrated with AI, to find surroundings and enable automation in driving and in the same way there are a lot of technological areas that are going to impact future generations.
International Data Corporation foretells that AI Share in the enterprise market will grow 50% by 2021, i.e., 50 Billion USD. It's nothing but extensive AI research that will empower us to find how to realize AI value today and in the future.
Artificial Intelligence will soon become pervasive, but today only top companies and experts lead the AI innovative path in order to develop AI systems. It has been a high entry barrier for many businesses, primarily because of difficulty in deployments of the AI system. Lack of unified frameworks and limited implementations of AI in Speech and Image processing. So develop Artificial Intelligence models in these areas is not an easy task, previously we have few frameworks which are used to build the AI models. But these frameworks are not up to the mark for building AI applications. So, here comes the solution for accelerating AI growth.
Linux Foundation’s Deep Learning, AT&T, and TechMahindra organizations have developed an Open-source AI framework named as "ACUMOS AI" that is hosted by Linux OS. It provides a large ecosystem for AI adoption; Acumos AI is used to build innovative AI, Deep Learning, and Machine learning models very effectively. This project will help scientists to focus on their creative ideas to build enhanced AI models.
What is ACUMOS AI?
Acumos is an Open Source Platform, which supports to develop, integrate, deployment and training of Artificial Intelligence models. Actually, an Acumos AI was originally coded by AT&T and Tech Mahindra that was hosted by Linux Foundation's Deep Learning on its platform. It would have made a positive impact on AI Space to create more AI systems and to integrate with well-known frameworks such as SciLearn, TensorFlow, H2O, and Rcloud By creating a wider ecosystem to accelerate the growth of AI in commercial and industrial problems. It drives a data-centric process for developing machine learning applications. ACUMOS provides a container-based deployment for both private and public environment.
ACUMOS AI provides an ecosystem to build AI, machine learning, and Deep Learning models. It enables you to create an innovative infrastructure for scientists to focus on their splendid ideas in AI. The main theme of ACUMOS AI is "MAKING Artificial Intelligence ACCESSIBLE TO EVERYONE."
How it will Impact on Artificial Intelligence Space?
Previously we have so many popular AI frameworks that have been there to build AI apps. But unfortunately, the integration of AI apps developed using these frameworks is not an easy task for beginners, because it is totally involved with the cloud-based environment. Only the advanced programmers will do that. So ACUMOS AI consists of Design Studio based on Linux which helps you to integrate these frameworks with each other and it provides ease form of deployment for beginners.
ACUMOS Architecture
ACUMOS provides full power to data scientists in order to publish creative AI models with custom integrated solutions.
It is completely interoperable with any other ACUMOS AI models which are built regardless of any other AI frameworks. These models built with any other supportive and collaborative languages such as Java, Python, and R can also be developed, deployed and catalogued.
ACUMOS contains five major modules, which plays a vital role in ACUMOS environment and ease the process of AI development in the ACUMOS ecosystem.
Team UP: In this module, ACUMOS provides an open-source ecosystem for people to collaborate, experiment, and share their ideas and solutions to bring better outputs.
Marketplace: Acumos brings AI into the mainstream of the marketplace and it also acts as go-to-site for making data-powered decisions. Moreover, it also makes AI an easy-to-use initiative in the design studio and marketplace.
Onboarding: Due to the main focus on the interoperability, ACUMOS provides enhanced support for diverse AI toolkits. Furthermore, many onboarding tools are available that include H2O, TensorFlow, generic Java, RCloud and so on to perform well.
Design Studio: It is a graphical tool in the ACUMOS which is mainly designed for chaining, filters, multiple models and many more together into a particular solution like a run-time environment. This model can be used in different environments to solve different data sources and problems.
SDN and ONAP: This is defined as a community to many marketplace solutions and can also be directly deployed into SDC.
Steps to Create AI Models in ACUMOS based on Linux
There are four major steps have been involved in the AI development process on ACUMOS platform.
1. Creating Artificial Intelligence Applications
In this step, we need to create AI applications with API and that applications are trained by different kinds of Machine Learning/Deep learning libraries such as TensorFlow, SciKit-Learn, RCloud, and H20.
2. Dockerize the application and Register to Acumos AI
Dockerizing an application is defined as a method of changing an application to run, debug, and test within a Docker Container. Although, this process is also involved in ACUMOS platform to Register AI apps into the ACUMOS environment. Dockerization makes use of environment variables and configuration files to create an environment-friendly application.
3. Integrating and Sharing Knowledge
Previously we have popular AI frameworks are available such as Tensorflow, SciKit-Learn, RCloud and H20. They are used to build AI applications very effectively. But their integration with each other framework is not possible individually. So the ACUMOS provides a platform for integration and sharing knowledge among different AI applications. The different AI applications will share their knowledge to produce better outputs.
4. Share AI applications into Marketplace.
Install developed AI apps in the Marketplace, which consists of both public and private modules. It also has infrastructure engineers to maintain the deployed AI apps.
What are the Frameworks and Languages Supported by ACUMOS?
ACUMOS is the platform which supports the integration of different AI frameworks and languages to ease the deployment of AI models. Here is the list of frameworks and languages supported by ACUMOS.
ACUMOS is a framework to harmonize the AI developing process with existing frameworks such as TensorFlow, SciKit Learn, RCloud, H2O, and various other programming languages such as Java, Python and R. By leveraging an ACUMOS framework, for which all of the source code is readily adaptable. The supported tools and languages by ACUMOS will grow over time, which will lead to developing a wide range of AI applications.
Acumos AI Frameworks
1. Athena:
Athena is Acumos project first released framework. It was released on 12th December 2018. Athena is a stable version, but data scientists notice that few bugs are detected while developing AI models. For this Linux Foundation released another updated framework to eliminate the bugs and issues with the Athena.
2. Boreas:
Boreas is a newly updated framework for Acumos AI. It was released on June 5th 2019. Boreas can support Dockerized, ONXX, and PFA models. Support enhanced to Acumos AI works on Kubernetes.
ACUMOS AI Features
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ACUMOS categorize the difference among the Machine Learning/Deep Learning libraries that are encased by common Application programming interface.
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Dockerization of AI applications provides easy development and deployment.
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ACUMOS GUI tool called Design studio that is used to develop visual programming code for AI applications.
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ACUMOS provides a marketplace for sharing, rating, and collaborative intelligence with Artificial Intelligence models in both public and private places.
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Provides larger ecosystem for Artificial Intelligence.
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API connect, toolkits as microservices, and chain models.
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It provides an option to export AI applications in the form of Docker images to run in private and cloud environments.
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It produces onboarding ramp for AI toolkits and ML models.
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Adding models with tool kits is an easy task with ACUMOS platform.
Conclusion
Artificial Intelligence is the technology that is going to change the facets of technology in the near future. Perhaps there are so many drawbacks beyond this revolution, which are going to stop the innovation in the AI space. But ACUMOS based on Linux doesn’t let this happen, because it enables to accelerate the AI innovation space by integrating with various popular AI frameworks (TensorFlow, SciKit Learn, RCloud and H20) with each other.
