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Artificial Intelligence as a Service

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AI Demonstration

The following videos demonstrate how AI can be employed to perform object detection. Telemus AI™ systems can run sophisticated neural networks at scale.

@realanthq Artificial Intelligence Test - Flinders St Station, Melbourne, Australia - 29 March 2022 #compsci #ai ♬ скрипка.. - .яконч

AI Partners

Telemus AI™ works with world leading technology partners to ensure you get access to bleeding-edge artificial intelligence.

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AWS
Node
OpenAI
Tensorflow
OpenCV
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Node

AI Services

Telemus AI™ provides cutting-edge artificial intelligence via a Software as a Service framework. We deliver AI capabilities for all and support the drive forward in the democratisation of AI.

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Neural Networks
Artificial neural networks are composed of nodes connected by edges; these networks can be composed of multiple layers. Given high volumes of quality training data, they have proven to be highly effective in solving non-linear and intractable problems.
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Machine Learning
Machine learning algorithms have an extensive history and are broadly categorised as supervised or unsupervised. These algorithms can generalise solutions to a wide range of problems. They are currently used extensively in modelling.
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Language Processing
Language processing has been employed in a variety of applications. Detection and translation tools have become widely available and utilise a combination of natural language processing and statistical learning techniques. Text can also yield insights by analysing the sentiment expressed across social media networks.
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Computer Recognition
Computer Recognition is a complex area. While problems surrounding digital image storage and retrieving have been solved with well-established solutions, analysing images and identifying features has long been a challenge. Recent advancements in facial recognition have recently been deployed widely, with object detection also gaining prominence.
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Reinforcement Learning
Reinforcement Learning employs state agents and probabilistic models to explore optimal solutions. Inspired by positive and negative reinforcement identified in biology, it has gained popularity. The algorithms use random changes in candidate solutions to identify optional models.
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Expert Systems
Specialised systems have been recently developed to emulate the decisions made by domain experts. They are widely used in applications that require constant monitoring. The advantage of using expert systems is that they can ensure that key considerations are always met and assist domain experts in processing a multitude of variables.

AI Applications

Technology powered by Artificial Intelligence will become pervasive in daily life, here is a non-exhaustive list of applications.

  • Language Models
  • Facial Recognition
  • Voice Recognition
  • Object Detection
  • Recommendations
  • Autonomous Vehicles
  • Search Engines
  • Art Generation
  • Code auto-completion
  • Virtual Assistants
  • Fraud Prevention
  • Protein Folding
  • Sales Forecasting
  • Traffic Monitoring
  • Sentiment Analysis
  • Financial Monitoring
  • Language Translation
  • Spam Filters
  • Music Composition
  • Video Colourisation
  • Personalisation
  • Game Playing
  • Art from Text
  • Health Screening

AI Ready

The Telemus AI™ platform delivers AI capabilities right out of the box, allowing your organisation to realise the benefits of the latest cutting edge technology faster.

AI Case Studies

Explore our case studies to see how AI can be applied in your organisation. If your organisation has a specific use case where AI can be of benefit, Contact to organise an obligation free discussion.

Reinforcement Learning
Customer Personalisation
Monitor patterns to suggest products customers might be interested in purchasing
Computer Recognition
Surveillance Footage Object Detection
Monitor CCTV footage and track people and objects in realtime
Expert Systems
Automated Traffic Monitoring
Automatically monitor traffic to detect anomalies and improve safety
Language Processing
Social Media Sentiment Analysis
Analyse social media sentiment to determine how people feel about your brand
Machine Learning
Financial Monitoring
Track billions of transactions and monitor them for anomalies in realtime
Neural Networks
Sales Forecasting
Accurately predict future sales with vast quantities of existing data
Artificial Neural Network

AI Development and Integration

Analyse

Define the problem to be solved and determine the requirements of the AI system
Capture

Prepare high-quality training datasets via various internal and external sources
Construct

Build a suitable AI system and train it with domain-specific data to solve the formulated problem
Evaluate

Test the AI system using real-world data and scenarios to ensure it generalises the problem
Integrate

Determine how best to integrate the AI system within the organisation and what parameters the AI will operate within
Support

Provide continuous updates and support of the AI system, work on constant improvements to increase accuracy to an even greater degree

LatestAI Articles

Our articles provide key information on how to prepare your organisation for AI, as well as how AI can be implemented within your organisation.

Artificial Intelligence vs Classical Computing

Classical Computing methods have posed many difficulties in solving intractable problems. Advancements in AI have been recently applied in solving complex technical problems, including facial recognition and object recognition.

Organisational Applications Suited to AI

Organisations have traditionally relied on Business Intelligence (BI) reports and Data Analytics to assist in high-level Automated Traffic Monitoring. AI is well suited to identifying complex trends across multiple variables.

Preparing Organisational Data for use with AI

Organisational data is captured and stored in different formats, from spreadsheets to relational databases and Word documents to text files. Leveraging organisational data involves a series of pre-processing steps to make it suitable for use in AI systems.

Integration and Productionisation of AI

Many organisations have been successful in producing useful AI models via Ad-Hoc analysis. A major challenge is the productionisation of AI models to allow the entire organisation to leverage the capability.

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