Amazon RekognitionĪWS Rekognition enables applications to analyze images and videos and automate manufacturing quality inspections. Amazon PollyĪWS Polly is an AI-powered cloud service text to speech conversion service available in over thirty one different languages and accents. Amazon Lex for AI ChatbotsĪWS Lex allows you to build chatbots with conversational AI that reduces your overhead costs while delivering a smart automated live chat experience. Using AI it can extract health information data like prescriptions, medical bills, medical reports, and more. Amazon Comprehend MedicalĪWS Comprehend Medical is a Software As a Service (SaaS) HIPAA compliant natural language processing (NLP) service for healthcare providers. With help from partners like ERPA, AI-based solutions can be applied to your company too, such as: Amazon ComprehendĪWS Comprehend can automatically extract targeted text from electronic documents, scanned images, and even handwriting, and derive meaning from unstructured text using natural-language processing. Tens of thousands of companies around the world are leveraging AWS AI solutions with its range of products that help their customers design, build, train, test, and deploy AI-based solutions for a wide range of business applications. Thus, computer scientists call it “machine learning.” Tweaking the rules by hand would be a tedious task that would take close to forever, so most ANNs contain logic to tweak their own rules. The rules are tweaked during the iterations of this training phase until the ANN can reliably get the “right” answer for a given input. ANNs “learn” by being fed immense amounts of annotated data. These rules are what determines how an ANN comes up with its answer (for example, whether a given image contains a dog). Each neuron “fires” a signal to one or more neurons in the next layer (or previous one, in some designs) according to a specific rule regarding its inputs. Signals propagate from the input layer to the output layer according to mathematical relationships. An ANN will typically have an input layer, which ingests the data the ANN is designed to analyze an output layer, which presents the results of the ANN's analysis and any number of intermediate (or “hidden”) layers. Neurons are commonly organized into “layers,” with one or more neurons in each layer. In an ANN, the “neurons” (which are objects modeled in code) are connected to other neurons. Most modern AI technologies are based on artificial neural networks (ANNs), whose principle of operation resembles that of biological neurons. Let's take a closer look at what AI is (and isn't), and how it's helping businesses enhance their analytics and other digital capabilities.Īt a high level, AI is any technology that is designed to emulate, at some scale, the workings of a biological brain. In this article, we discuss what AI is, various ways that the technology is being used in the enterprise, and how ERPA (an AWS Advanced Consulting partner) leverages the AWS AI support tools to help our clients realize a competitive edge. That said, any specific AI application today can do only the thing it was designed for, and nothing else. AI even helps email systems filter out spam and phishing emails. In fact, many people do not have a full understanding of AI technology or how it can benefit them and their businesses.Ĭompanies in many industries are applying AI technologies to everything from helping doctors diagnose diseases to helping banks and credit card companies identify fraudulent transactions. AI's meteoric rise in popularity and use doesn't mean everyone has adopted this technology though. With Artificial intelligence (AI) stories being all over the news these days, you may wonder where AWS AI fits in (if at all) within your organization's tech stack.
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