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Artificial Intelligence

Whether you are talking about deep learning, strategic thinking or another species of AI, the foundation of its use is in situations that require lightning-fast responses. With AI, machines can work efficiently and analyse vast amounts of data in the blink of an eye, solving problems through supervised, unsupervised or reinforced learning.

Early days of AI

While its early forms enabled computers to play games such as draughts against humans, AI is now part of our daily lives. We have AI solutions for quality control, video analytics, speech-to-text (natural language processing) and autonomous driving, as well as solutions in healthcare, manufacturing, financial services and entertainment.

A powerful tool for businesses and organisations

Artificial intelligence can be a very powerful tool for both large corporations generating significant data and small organisations that need to process their calls with customers more effectively. AI can streamline business processes, complete tasks faster, eliminate human error, and much more.

AI at the edge

Progment is pioneering a new frontier of AI by harnessing data and gaining insights at the edge. We empower success with real-time analytical AI for automation, prediction and control to help you realise the value of your data faster and leverage limitless opportunity for innovation, growth and success.



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Our future plan

There are many trends being embraced today that will drive the future of software development. But where the trends are at — in terms of adoption — varies between innovators who are ahead of the curve, early adopters who are next up, and early majority who are embracing the trends.

Innovators are adopting:

  • Deep learning: a subset of machine learning based on artificial neural networks.
  • Blockchain: a growing list of records that are linked with cryptography.
  • AI: machine intelligence used in software development (e.g., AI writing code or AI in software testing).
  • Serverless / lambda: a way to build serverless applications (e.g., AWS Lambda).
  • Reactive programming: a model structured around asynchronous data streams (e.g., Java Completable Future).
  • Orchestration: a way to automatically configure, coordinate, and manage systems (e.g., cloud orchestration).
  • GraphQL: an open-source data query and manipulation language for APIs. GraphQL is one of the top open source trends today.
  • Microservices: a technique to break an application up into a collection of loosely-coupled services.
  • Immutable infrastructure:an approach to manage service or software deployments (e.g., Infrastructure as Code).
  • API design: the process of developing application programming interfaces (APIs) that expose backend data and application functionality for use in new applications.