AI and its applications are not going away and will cause a significant amount of change to everyday life over the next decade. Whilst there has been a lot of buzz in the past that has not been fulfilled, advances in skills, computing power and modelling and ensuring that the hype is finally being realised. To some extent, we don’t even know what AI is capable of yet which is both exciting and scary!
3. Where are we now?
Why AI is powerful now:
- Big Data
- Computing Power
- Models and Algorithms
4. My Top 5 Trends in
Artificial Intelligence
• Some of the top trends as we move towards 2020:
• Machine and Deep Learning
• Computer Vision
• The Cloud
• IoT at the “Edge”
• Automated Machine Learning (AutoML)
5. Machine and Deep
Learning
• Machine learning models start out dumb and get
smart by being exposed to data
• ML is algorithms and statistical models to
perform a specific task without explicit
instructions, relying on patterns and inference
• Using data to make business decisions based on
predicted outcomes
• Deep Learning is ML on steroids, used by
autonomous vehicles, content creation
6. Computer Vision
• Enables computers and devices to see, observe
and understand what they see
• The flood of visual information from modern
devices, sensors and technology has been key for
the development of CV technology
• Pre-trained algorithms are useful and widely
available
• Essential technologies: Deep Learning and
Convolutional Neural Network (CNN)
7. Computer Vision
• Enables computers and devices to see, observe
and understand what they see
• The flood of visual information from modern
devices, sensors and technology has been key for
the development of CV technology
• Pre-trained algorithms are useful and widely
available
• Essential technologies: Deep Learning and
Convolutional Neural Network (CNN)
8. The Cloud
• AI and ML algorithms needs data, a lot of data
• Local data centers available
• Large vendors invests massively for the “Cloud
Consumption” market
• Most customers has a multi-cloud strategy
9. IoT at the “Edge”
• Process massive amount of data with
limited network bandwidth
• Connected Factory/Building/Oil Rig/Device
• Smart & effective Data Collection
• Privacy, Security & Offline support
10. Automated machine
learning (AutoML)
• Automating the process of applying Machine
Learning end-to-end
• Data scientists' skills are hard to automate
• Helps in optimizing algorithm parameters,
Learning, Preprocess and clean data,
Postprocess ML models and more
11. How to get started
• Strong BC with well documented KPI & targets
• Start small, think BIG
• Ensure involvement and governance
• Establish partnership
12. How to get started
You need someone who:
• Owns the Business Problem
• Understands Data, Data Quality & Data Security
• Understands Analytics – Machine Learning,
Statistics, Optimization and Forecasting
• Knows how to put analytics in action by
operationalizing for outcomes
13. Build AI
• Tailor made solutions
• AI components and Cognitive services
• ex. Natural Language Understanding, Text to
Speech, Image/Face Recognition & Personality
Insights
15. Hybrid and On-Prem
Computing
• Enterprise software as pre-packaged
Kubernetes applications
• Build once, run everywhere
• Hybrid cloud that scales and maintain security
16. Opportunities for you
MSPs can use AI to increase their profits:
- Condition-driven automation
- Repetitive task-driven automation
- Look for patterns
- Look to automate across multiple client sites
- Look for event triggers
17. What can we do
together?
• Increase profit with better insight
• End to end project deliveries
• Access to Technology and Competency
18. Whatever journey your organisation is on
to an optimised cloud enabled future,
don't take on the task alone.
Talk to the technology transformation experts at
Crayon and make your ambitions a reality.
Thank You!
www.crayon.com