Discover the future of AI Machine Learning Models
Artificial Intelligence and related technologies will soon be a critical component in businesses, within a sizable number of software packages, and part of our daily lives. “Gartner has predicted that by 2020, AI will be one of the top five investment priorities.” Global software vendors are after this new rush. Although the promise of new returns has compelled software business owners to invest in AI technologies, the fact is that most organizations do not have a skilled workforce to embrace AI.
According to Gartner
“Artificial Intelligence and Machine Learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing, or application.”
The Future of AI
In this era, research has driven to build a machine that works like a human. The thinking machine is AI’s prevalent gift to humankind; the grand entry of AI has suddenly changed the operational rules of business. In the recent years it is proven that intelligent machines like digital assistants, self-driving vehicles, and robotic factory workforce are possible. AI has changed most industry sectors and continues to enter new territories.
The Future of Machine Learning
Here are a few expectations about Machine Learning, based on present technology trends and ML’s systematic progression towards maturity:
- ML will be an essential part of all AI systems.
- As ML assumes increased importance in business applications, there is a strong possibility of this technology being offered as a Cloud-based service known as Machine Learning-as-a-Service (MLaaS).
- Connected AI systems will empower ML algorithms to constantly learn, based on emerging data.
- There will be a huge rush for hardware vendors to augment CPU power to accommodate ML data processing.
Building Machine Learning Models
The machine learning process feels a lot tougher than it should be to most developers because the process to build and train models, then deploy them into production is too complex and too slow.
However, with the right set of tools and services offered by AWS, we can make it possible much quicker and easier.
Join Royal Cyber for an interactive workshop to learn how your enterprise can build ML Models with the following tools
Amazon SageMaker
AWS DeepLens
AWS Greengrass
Amazon Rekognition
AWS Lambda
Amazon EC2 C5 instances
Whether it be in your workplace or wherever your interests take you, these models get to production faster with less effort and at a lower cost.
Join us for this workshop that will spin around DevOps tools to build ML Pipeline. For more information you can write to us at info@royalcyber.com or visit https://www.aiagentbot.com.
