Imagine sitting across from your new virtual assistant, Nadia. Although you’re staring into the eyes of a computer-generated image, “she” has extremely detailed and lifelike physical features. Her face has a bone structure and her muscles appear to move exactly like a human’s. She even has realistically detailed skin blemishes.
Nadia is a “digital human” that was released earlier this year by Soul Machines, an Auckland-based company that develops highly detailed avatars with personality and character. Nadia was created for the National Disability Insurance Scheme (NDIS) in Australia, using IBM Watson’s AI technology.
She was designed to help disabled people learn more about the NDIS and the resources it provides. Customers can go on the NDIS website and interact with her directly. One of the most compelling features of Nadia is her level of emotional responsiveness. She can “see” who she is talking to and customize her conversation based on emotional cues. For instance, if Nadia senses a customer is upset or distraught, she will change her behavior instantaneously to respond more empathetically.
The third era of AI
Nadia is a product of the latest era of artificial intelligence, a period marked by the proliferation of intelligent virtual assistants and robots with specific skill sets. Netflix and Pandora brought us the first wave of AI, which defined the curation era. Next, Siri brought us the voice interface. Now, in addition to developments like Nadia, we are seeing virtual assistants such as Alexa, Clara, and x.ai.
This great awakening of AI is fueled by super fast computers, powerful software, greater connectivity, and the Internet of Things. At the same time, AI advancements such as deep learning and neural networks (computational models that function much like biological brains) are expanding the capacity for machines to be more like humans. The capabilities of these neural networks are also creating a new reliance on artificial intelligence that goes beyond the completion of mundane tasks. AI technologies are now tasked with filling important roles in modern communities.
Juniper Research found that chatbots alone could save businesses $8 billion a year by 2022, with health care and banking benefiting most. Health care is particularly active in creating widespread AI solutions for the general public. One interesting example is a project from Stanford University. Researchers at the school are training an algorithm to identify skin cancer, one of the most common types of cancer in humans. The Stanford scientists loaded an algorithm with nearly 130,000 skin-lesion images that represented more than 2,000 diseases to test whether the computer could distinguish harmless moles from malignant melanomas and carcinomas. It did so with surprising accuracy, performing as well as a panel of 21 board-certified dermatologists. The team plans to make the system available on smartphones in the future.
Scrambling to claim stake in AI
As the value and need for AI increases, so do the investments in the space. Nearly 140 private companies developing AI technology have been acquired since 2011, with 40 acquired in 2016 alone. AI startups raised more than $5 billion worldwide in 2016, which marks a five-year high. Google has adopted an AI-first strategy for its business categories. Apple, Amazon, Facebook, and Salesforce have all jumped into the AI race as well. Other major tech giants competing in the space include General Electric and Samsung.
Major companies are already implementing AI in many consumer-facing products and services. Here are just a few of the areas where companies have created consumer touchpoints with the technology:
- Auto manufacturing: In the automotive industry, AI is helping self-driving cars communicate with one another by sharing data and information about the infrastructure and traffic conditions around them. Apple CEO Tim Cook recently called the challenge of autonomous vehicles “the mother of all AI projects.”
- Food and beverage: London-based IntelligentX Brewing Co. uses machine-learning algorithms to automatically analyze customer feedback on its bottled beers. This influences how its human brewers create new products targeted to drinkers’ rapidly changing tastes.
- Manufacturing and logistics: Last holiday season we saw an interesting innovation by Amazon: The retailer employed 45,000 robots alongside human workers in 20 fulfillment centers. This number was up from 30,000 in 2015.
- Travel: Companies like Boxever and John Paul are leveraging machine learning and AI to enhance customer experiences by better anticipating needs and providing more engaging interactions.
- Retail: San Francisco-based personalized clothing e-tailer Stitch Fix uses software to design apparel. AI systems process trillions of possible combinations of patterns, cuts, and colors, factoring in customer purchasing behavior and information about the latest fashion trends to design new offerings. And as VentureBeat previously reported, Neiman Marcus’ app implements AI to help customers find the products they’re looking for. The app lets customers submit photos of items they like and get suggestions for similar items from the store’s stock.
- Health care: Ellie, a “virtual therapist” funded by the Defense Advanced Research Projects Agency (DARPA), was designed by University of Southern California’s Institute for Creative Technologies to detect signs of depression and PTSD in veterans by tracking and responding to visual and verbal cues.
According to Accenture, artificial intelligence could double annual economic growth rates by 2035 and boost labor productivity by up to 40 percent. Productivity may seem like a vague descriptor, but look at health care. Advancements in productivity from helpful assistants such as Ellie and Nadia result in better preventative health care, diagnoses, treatment, and health outcomes. That’s how bots are helping to build a better world.
Kal Patel is senior vice president of digital health at Flex, a sketch-to-scale solutions provider that designs and builds intelligent products for a connected world.
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