A subfield of Machine Learning, Deep Learning allows organisations to accurately forecast opportunity to expedite decisions.
The buzz of ‘big data” has been invoked repeatedly for several years. The push was for the consideration of what technologies organisations' needed to consider for the expediential data growth they were expected to see.
The demands and pressures on infrastructure, personnel and legalities were all contention points for the ‘big data’ craze, but those with a forward-thinking strategy maximised the era of change with the interpretation that data collection would become there ‘value-added resource’.
Artificial Intelligence (AI) stirred excitement with the ability for cognitive functions to become automated and mimicked from the machine perspective.
In fact, AI techniques have been around for many years, they have just become dependencies we’ve become accustomed to, as our technology progresses and advances.
Machine Learning allows organisations to get “under the hood” of their data, helping data intelligence evolve to more predictive and instructive based outcomes.
Instead of backwards looking analytic decisions, machine learning allows a business to consider what next.
What should the organisation do, build or offer to remain successful?
Learning algorithms via the other intelligence methods give process advancement, forward-thinking strategy and resolutions.
Helping evolve an organisation's offerings and capabilities, whilst automating tasks.
However, these standard learning algorithms age with time and performance plateaus on goal/output, due to the amount of data.
The more data generated, supervised and labelled, simply increases performance, making a first-class algorithm to essentially make groundbreaking advancements in output.
These first-class algorithms are inspired by the structure and function of the brain called Artificial Neural Networks (ANN).
They learn from experience and take several inputs and compute a predicted answer, making Deep Learning practices turn the unthinkable into the possible.
Whether it be the simplicity of Alexa predicting and adding washing powder to your monthly Amazon pantry delivery or image recognition that can spot potential tumours on an MRI scan far faster and with greater accuracy than a human, there is no denying that now is the time organisations are considering switching vision to reality.
We know organisations have problems to solve, some big life-changing problems, others have complexities which cause defragmentation for their day to day operations.
No matter how big or small, evidence shows they need help exploring the paths available to them, to not only solve that problem today, but to continue to resolve that problem in future years ahead.
With dedicated, powerful and practical Deep Learning solutions Arrow can help you create and develop your Deep Learning practice.
Arrow can help partners gain valuable real-world skills which are only ever achievable through hands-on experience.
This next era of computing we refer to as Deep Learning brings not only a revolution to the data centre but also to the traditional practice as a partner.
With viewing each opportunity as being an individual problem it means that significant customisation and support will be required as well; as a dedicated platform created to uphold the volume and velocity of data.
Deep Learning solutions require accelerated servers using custom processing components dedicated to computing mathematics extremely quickly and in parallel to complete a job in a timely manner.
These custom processing components are those which are commonly referred to as Graphical Processing Units (GPUs).
GPUs traditionally are found in high-end consumer PCs for gaming purposes and perhaps have not been always associated with the data centre before now.
However, the fundamentals of the process of rendering a screen with high-definition graphics are the same foundation of mathematical problem solving required for deep learning algorithms.
Arrow has developed a pre-built, market-validated solution to breakthrough performance for GPU accelerated applications.
Designed specifically to provide Deep Learning behind the firewall, the solution allows companies to retain, complete control over sensitive training data, as well as significantly lower costs of running continuous deep learning tasks.
Understand the technologies, see the referenced architecture and understand how you can position this innovative solution to your customers today.
Author: Julie Stephens