Getting the right product that lacks defects is not always easy, especially when the quality inspection has been carried out by a human. Although the human brain and eye have had approximately 200,000 years of practice to get things right, evolution is not perfect. That is why, in quality control and all that it encompasses, it’s sometimes a better option to use other, more reliable tools to help us do the job.
AI-based applications are the prime example of this. For one, they have a much higher level of accuracy and can do a task much faster than a human and, this is an important one, can continue on a task where the “monotony factor” doesn’t hamper their concentration, something that we, as flesh and blood, are all too guilty of.
DarwinAI, a Waterloo, Canada-based visual quality inspection startup founded in 2017 by Alexander Wong, Brendan Chwyl, Francis Li, and Mohammad Shafiee, provides manufacturers with such an end-to-end solution to improve product quality and increase production efficiency.
Its patented Explainable AI (XAI) platform, built from years of research (500+ publications including numerous awards), has to date adopted by numerous Fortune 500 companies that have effortlessly integrated DarwinAI’s product into their workflows because of
• Higher Accuracy:
Its XAI accelerates the creation and calibration of AI models to the customer’s specific use case, improving accuracy for better results
• Better Performance:
XAI models offer a higher performance than those produced by other AI offerings on powerful and costly edge equipment
• Smarter System:
XAI platform makes the system smarter over time by using a feedback loop that continually learns from real production data
• Trust & Transparency:
Explainability illustrates why AI makes the decision it does, which is important for optimizing performance and building trust with users — and which will soon be critical for using AI in regulated industries
• Quicker Implementation & Adoption:
Getting started with its product requires only a fraction of the number of data samples needed by traditional AI systems, making it much faster to get started; thus optimizing the entire design process
• More Real World Use Cases:
Unlike AI technologies that only work in contrived or academic scenarios, we solve real-world problems — where data quality and quantity may be limited, computing resources are scarce, and trust is an absolute necessity
With applications that cover manufacturing and healthcare, the startup’s Explainable AI (XAI) platform technology is a sure remedy for pain points witnessed across those verticals.
Alexander Wong is the first of four Co-Founders and DarwinAI’s Chief Scientist. Wong is the Canada Research Chair in Artificial Intelligence and Medical Imaging at the University of Waterloo and is a leading expert in AI (particularly deep learning) and computational imaging (particularly in skin cancer, prostate cancer, and lung cancer imaging, cardiovascular imaging, and microscopy) He has published over 570 papers in leading journals and conferences, as well as holds over 30 patents and patent applications in these areas.
Wong has received numerous research awards at conferences and organizations such as NeurIPS, CRV, CVIS, Society of Information Display, Ministry of Research and Innovation, and the Imaging Network of Ontario.
In the area of AI, Wong’s focus is on operational deep learning (co-inventor/inventor of Generative Synthesis, evolutionary deep intelligence, Deep Bayesian Residual Transform, Discovery Radiomics, and random deep intelligence). In the area of computational imaging, Dr. Wong’s focus is on integrative computational imaging systems for biomedical imaging (inventor/co-inventor of Correlated Diffusion Imaging, Compensated Magnetic Resonance Imaging, Spectral Light-field Fusion Micro-tomography, Coded Hemodynamic Imaging, High-throughput Computational Slits, and Spectral Demultiplexing Imaging).
He is also the co-founder of Elucid Labs, and a Member of the College of Royal Society of Canada and obtained Ph.D. in Systems Design Engineering from the University of Waterloo, Canada.
VP of Research at DarwinAI, Javad Shafiee is also a Research Assistant Professor at the University of Waterloo. He has a Ph.D. in Machine Learning and Computer Vision from the University of Waterloo, Canada.
Brendan Chwyl is the Director of Engineering at the startup. Prior to DarwinAI, Chwyl was a Research Assistant at the University of Waterloo. He received an MA in Design Engineering from the University of Waterloo, Canada.
Francis Li is the final Co-Founder and Director of Research at DarwinAI. With an MA in Computer Vision from the University of Waterloo, Canada, Li’s research interests extend to 3D computer vision (scanning, recognition, RGB-D) and image processing and he enjoys working on state-of-the-art research in AI and seeing its real-world applications.
In terms of DarwinAI’s financial status, the company has raised a total of $11.9 million in funding over five rounds, giving its Explainable AI platform enough financial resources to make it the premier AI visual quality inspection tool on the market.