The Challenge of implementing AI
Artificial Intelligence initiatives are still considered experimental, with unknown business results, and can represent a challenge to IT and operations functions alike.
It is later – when companies decide to institute these innovations – that trouble may ensue. Most often, available AI resources prove inadequate, given that data scientists, quantitative mathematicians and experts with experience in AI are all in short supply, the world over.
Alignment between IT and the business can also create sub-par results for AI initiatives.
The Comtrade Difference
The great advantage of our implementation services model is our vast experience in global delivery, coupled with our extensive network of research organizations. Dubbed the AI Collective, it gives our clients access to an “A” team of experts, career-long practitioners who have a realistic, in-depth knowledge of genuine capabilities of AI today.
• Machine learning
• Data mining
• Artificial neural networks
• Natural Language Processing/Analysis
• Image/Face Recognition
• Knowledge representation
• Productizing new AI algorithms
• Productizing AI product ideas
• Open-source support of AI products
• Updating legacy AI solutions with new results from research
• Deep learning: Caffe, Torch, TensorFlow
• Microsoft Azure ML Studio
• ML in Python: Scikit-learn and R libraries