e·qui·lib·ri·um /ˌēkwəˈlibrēəm,ˌekwəˈlibrēəm/ noun: equilibrium; plural noun: equilibria a state in which opposing forces or influences are balanced. The key to losing weight is to focus on inputs and outputs. If you are eating more calories than you are burning, you gain weight. If you are at a state of equilibrium, you maintain your current weight, […]
In Malcolm Gladwell’s book “Outliers”, he popularizes the concept that to be great at anything requires at least 10,000 hours of practice. He argues, citing various studies, that the more research conducted into acknowledged high-performing individuals across many fields, the less innate talent mattered and the more critical was a near-ritualistic devotion to preparation and […]
An interesting story of advanced analytics used not to fight fraud, but potentially to enable it, was highlighted when the Justice Department filed a civil complaint of fraud last week against both a health plan and its technology services provider. At the core of this complaint is the accusation that the technology services provider used […]
How can IDP software simultaneously push through both the complexity barrier and expand to more complex documents? Machine Learning, that’s how. Now, I won’t ever make the claim that machine learning is a magical silver bullet, but when it comes to the chore of crunching large amounts of data to identify patterns and optimal solutions, […]
Don’t call it “OCR” anymore. Intelligent Document Processing (IDP) or what analyst firm Deep Analysis calls “cognitive capture” is something well beyond the traditional approach of applying brute force OCR on documents in order to create searchable content. In fact, increasing OCR is not needed at all with more and more documents born digital. All […]
Catch Me If You Can – Today, AI-powered software can mimic human investigators, detect check fraud in milliseconds and stop the scam.
Find out how cognitive capture can help eliminate the heavy toll of fraud and human error that impacts health insurers and patients.
The need for a data science approach where machine learning is applied to cognitive capture starts with high quality input data. Find out why.
Here are some guideposts that are useful in evaluating the authenticity of an AI capture product – whether it’s really cognitive capture.
The automation industry is on year-3 of its infatuation with everything machine learning and ‘unparalleled accuracy’ claims, what’s changed?
No machine learning to-date works with zero training, but advances to reduce the training required for reliable results are underway. Details here.
Key factors driving IDP adoption involve data science and specifically the confidence score that is arguably the most important factor involved with any decision to adopt IDP.
