Amazon’s cloud services platform Amazon Web Services recently announced three AI services it said will make it easy for developers to build apps that can understand natural language, turn text into speech, have conversations using voice or text, analyze images and recognize faces, objects and scenes.
This, in turn, underscores the increasing importance of AI to consumers, brands and marketers, but also raises some questions about how it will – and should – be developed.
Building apps with AI capabilities has been challenging to date because doing so requires access to vast amounts of data and specialized expertise in machine learning and neural networks, Amazon said in a press release.
“The combination of better algorithms and broad access to massive amounts of data and cost-effective computing power provided by the cloud is making AI a reality for application developers,” added Raju Gulabani, vice president of databases, analytics and AI at AWS, in a statement. “Thousands of machine learning and deep learning experts across Amazon have been developing AI technologies for years to predict what customers might like to read, to drive efficiencies in our fulfillment centers through robotics and computer vision technologies and to give customers our AI-powered virtual assistant, Alexa. Now, we are making the technology underlying these innovations available to any developer…we are excited to see how customers use Amazon Lex, Amazon Polly and Amazon Rekognition to build a new generation of apps that have human-like intelligence and can see, hear, speak and interact with people and their environments.”
Here’s a closer look at Amazon’s new AI services:
Amazon Lex is a service for building conversational interfaces using voice and text that is built on the same automatic speech recognition technology and natural language understanding that powers Alexa.
And, according to Amazon, Lex makes it easy to bring natural language capabilities to most apps. Developers can build and test bots directly from the AWS Management Console by typing in a few sample phrases along with instructions for getting the required parameters to complete the task and the corresponding clarifying questions to ask the user. Amazon Lex then builds the language model and asks the follow-up questions needed to complete the task.
In a statement, Firoze Lafeer, CTO of Capital One Labs at Capital One said Lex “offers potential to speed time to market for a new generation of voice and text interactions, such as our recently launched Capital One skill for Alexa.”
Momentum CTO Jason Snyder, however, questioned the degree of training required, particularly for understanding the context of a specific application.
“[Amazon] demoed an airline flight-booking with natural language using Lex and Polly. Apparently, interpretation was based on a knowledge graph that lets you add metadata,” he said. “I’d wager developers will have to do more than build an app hook up the APIs. But what more?”
Per Amazon, Polly allows developers to add natural-sounding speech capabilities to existing applications like newsreaders and e-learning platforms or create new categories of speech-enabled products.
Developers can send text to Amazon Polly using the SDK or from within the AWS Management Console and Polly returns an audio stream that can be played directly or stored in a standard audio file format. With 47 voices and support for 24 languages, developers can choose from both male and female voices with a variety of accents, Amazon said.
“We’ve long been interested in providing audio versions of our stories, but have found that existing text-to-speech solutions are not cost-effective for the speech quality they offer,” said Joseph Price, senior product manager at The Washington Post, in a statement. “With the arrival of Amazon Polly and its high-quality voices, we look forward to offering readers more rich and versatile ways to experience our content.”
And, finally, Amazon Rekognition enables developers to build applications that analyze images and recognize faces, objects and scenes. It uses deep learning to automatically identify objects and scenes and provides a confidence score that lets developers tag images so that application users can search for specific images using key words. Amazon Rekognition can locate faces within images and detect attributes, such as whether or not the face is smiling or the eyes are open. Amazon Rekognition also supports advanced facial analysis functionalities such as face comparison and facial search. Using Rekognition, Amazon said developers can build an application that measures the likelihood that faces in two images are of the same person, thereby being able to verify a user against a reference photo in near real-time. Similarly, developers can create collections of millions of faces detected in images and can search for a face similar to their reference image in the collection.
Combined, Lex, Polly and Rekognition demonstrate a bright future for AI.
In fact, one ad tech CEO said Amazon AI means the e-commerce giant is building out its arsenal to win the cloud wars and has positioned itself to catapult into the lead.
Further, Kerry Liu, CEO of retail intelligence platform Rubikloud, said he believes this investment should be a wake-up call for retailers if they want to remain competitive.
“[The] announcement of Amazon AI should be a sign that retailers need to take a step back and analyze their business and where they have the ability to invest. It will be important for these organizations to have a significant tech budget allocated to innovative processes so that they can integrate deep learning functionality within their software infrastructure,” Liu said. “There should be a sense of urgency across retailers to incorporate machine learning and AI into their platform in order to meet consumer demands for a tailored experience. Clearly Amazon has made this strategic investment given industry trends and expectations and if retailers don’t jump on this technology now, they risk falling behind.”
Scott Horn, CMO of customer engagement software and services provider 7, agreed.
“Amazon’s announced advances in AI demonstrate yet another example of the value businesses are putting on the power of machine learning. Abilities like natural language processing…are markers of an industry-wide race to better serve customers through AI. When used in a retail context, AI automates assistance on the front lines of customer service, saving human agents for higher stake scenarios, such as for retention and upselling purposes,” Horn said. “These advances are not only applauded by businesses, but also by customers. According to 7’s new customer experience study…two in five consumers are open to interacting with a chatbot in a retail scenario and nearly one-third of them (28.9%) prefer it over the phone or email. This level of adoption points to a profitable opportunity for retailers as they consider future CX investments.”
Snyder, however, said the biggest issue in his mind is ethical.
“Google has been using cognitive services and machine learning in its product set for more than a decade. Amazon has been working on AI, too, but not as long. Recently, Google, Amazon, Microsoft, IBM and Facebook formed an alliance to address the ethical issues. My point is there needs to be more prominent voices pushing for AI research and conversations regarding ethics and safety,” he added.
That’s because while he called AI one of the most beneficial technologies humanity has produced, Snyder noted it is our responsibility – especially in the context of persuading, like marketing and advertising - that machine intelligence clearly state its purpose as utility, information or entertainment.
“As an industry, it is imperative that as this technology enters culture, that we collectively develop and evolve AI in a responsible manner,” he added.