It is clear that the application and prevalence of Artificial Intelligence (AI) in our daily lives is here to stay. Although there will continue to be evolution and new perspectives on topics like ethics, data security and privacy, model upkeep, and more, one can’t deny that AI is transforming the way that we do business. More specifically, Generative AI has paved the way for smarter and more efficient practices, with applications from streamlined research to image generation.
There is a slew of lesser-known technologies than Generative AI that are making big impacts. Let’s dive into Emotion AI, Ambient Digital Scribes, and Edge AI.
Emotion AI
Emotion AI, as can be inferred by the name, is a branch of artificial intelligence whose purpose is to analyze human emotion, and subsequently react and model it. There is already broad application, as emotion AI is used for scenarios like non-invasively monitoring patients for signs of anxiety via their heart rate and respiration rate with subsequent consideration of diagnosis, to analyzing frustration in the voices of customers calling into call centers and using the cues to adjust conversation tactics and tone in real time. Consider Pizza Hut’s application via their “Your Mood, Your Pizza” campaign in India, The company installed in-store devices to analyze customer emotions and provide personalized pizza recommendations in return, elevating the customer experience to best meet their needs in a new and innovative way. Emotion AI technology analyzes facial expression, voice patterns, text, and/or physiological signals, and utilizes sentiment analysis to interpret the emotions, allowing organizations to have a real-time data point to decide their next action.
To contextualize with one more scenario, consider this feel-good story from Hyundai, where they provided a mini EV to a hospital in Barcelona for transporting kids from their hospital rooms to treatment rooms. The vehicle can go no more than 4mph and has several different features that collect data on the child’s emotion through heart rate, breathing rate, and facial emotions, and react to stabilize and try to make the child more comfortable.
Ambient Digital Scribes
Ambient digital scribes augment traditional transcribing & note taking through using AI to capture real-time conversations. Through the harnessing of natural language processing and machine learning, ambient digital scribes take spoken language and convert it to text. The technology doesn’t require any ongoing activity or input from the user and the machine learning technology enables continuous improvement of the situational context to better capture the interaction. Additionally, ambient digital scribe systems incorporate security measures to ensure data privacy. The application of this technology is robust and can be used from the most basic day-to-day meetings to transcribe and summarize key points, to enabling healthcare professionals to have more personable conversation with their patients without worrying about capturing all of their key information. The technology has already been quite successful within healthcare, saving physicians within The Permanente Medical group who are using the technology an average of one hour a day in note taking.
Edge AI
Edge AI, according to BuiltIn, is “the implementation of artificial intelligence in an edge computing environment, which allows computations to be done close to where data is actually created, rather than at a centralized cloud computing facility or an offsite data center.” Distilled down, edge AI computes algorithms on IOT devices (as opposed to in a cloud computing environment), allowing for more efficiency, security, and reliability of the computation, all while saving energy as well through minimizing data transfer to the cloud.
Given the prevalence and growth IoT devices and the overall market, and their diverse use in industries like manufacturing, retail, and healthcare, Edge AI has the potential to create more efficient and intelligent technology systems. Siemens is doing just that, utilizing this technology for more effective resource allocation and planning/execution of maintenance, creating an optimized and more productive manufacturing environment.
Perhaps the most exciting part of emerging technologies, like the examples above, is the concept of composability – utilizing different types of artificial intelligence together to build and work smarter. We help clients do exactly that, navigating this ever-changing landscape of technology, all the time. If this sounds intriguing, reach out below!
Dayna Larson
is an Associate Principal at Cortico-X with experience in life sciences, consumer products, financial services, and technology sectors.
