Artificial Intelligence, Machine Learning & Deep Learning  (AI):

 

Artificial intelligence (AI) is an area of computer science which enables the creation of intelligent to be displayed by machines so they will work and react like humans. Some of the activities computers with AI – artificial intelligence are designed for, include:

  • Knowledge
  • Reasoning
  • Problem solving
  • Perception
  • Learning
  • Planning
  • Ability to manipulate and move objects

The ability to mine larger amounts of data, information and knowledge in order to gain competitive advantage and the importance of data and text analytics in this context is gaining a momentum.
As the distribution of structured and unstructured data continues to grow the need to uncover the knowledge, contained within these big data resources, is a must.
Cognitive computing will be the key in extracting knowledge from big data. Strategy, process centric approaches and interorganizational aspects of decisions, support in this space, will continue to provide inputs on how to process big data to enhance decision making.
AI and machine learning are dependent on large amounts of data. But big data is hard to organize and analyze.
What are the changes:

Big data technology — We have the ability now to process huge quantities of data that previously required extremely expensive hardware and software.

Availability of large data sets — ICR, transcription, voice and image files, weather data, and logistics data are now available in ways that were never possible in the past; even old “paper sourced” data is coming online.

Machine learning at scale — “Scaled up” algorithms such as recurrent neural networks and deep learning are powering the breakthrough of AI.

To be effective with AI, Machine learning and Deep Learning requires having a healthy understanding of the data infrastructure to support it.

Data integration is one of the most difficult tasks for IT to do, and it is only intensifying as concepts like data aggregation in analytics, where sets of data can be combined into a searchable repository for new types of business queries.

Terasky specialists will help to reevaluate how the organization have collected data; how they capture, inspect, process and analyze data; and, more specifically, how they make use of it and build applications.

Terasky has more than 2 decades experience and knowledge of management and retrieval of data and information; physical, logical, virtual, cloud based methods; management, storage and querying of structured and unstructured data.

The rise of deep learning, an advanced machine learning technique that is heavily used in AI and Cognitive Computing relies on GPU fast development and strong attention got.

AI, Machine and Deep learning are about the data. It requires powerful CPU’s, fast Networking and a data.

Terasky engagement with NVIDIA, based on its knowledge years ago that AI could and would need to leverage the superior floating point parallel computation of graphics processing units (GPUs), closed the circle where the data management, applications and infrastructure development had been finalized into a complete AI, Machine and Deep Learning solutions.

TeraSky portfolio of Professional Services, based on the unique opportunities brought by Storage solutions, Data Protection, and Open Source Data Management technologies made possible to manage all types of Data, which is vital for AI, Machine and Deep learning.

TeraSky, as an integrator, who is a preferred partner for EMC, IBM, NVIDIA, Nutanix, has all the mentioned skills and can help you to implement AI, Machine and Deep Learning Solutions in benefit to your IT.