Last November, Emil Eifrem, one of roughly 100,000 people watching Mr. Jassy's keynote in the hall or remotely, braced for what he expected to be one of the announcements, a data-graphing service. Mr. Eifrem's company, Neo4j Inc., says it defined the technology, which allows customers to analyze data on Amazon's platform and others. Two years ago, as it researched the market, Amazon visited Neo4j asking for help building a similar product, said Mr. Eifrem, Neo4j's chief executive. Mr. Jassy did announce Amazon's competing service in Las Vegas and made it widely available this week. "When Amazon launches in your space, you're stupid if you don't get scared by that," Mr. Eifrem said, "because they do tend to outcompete everyone."
Amazon Web Services on Wednesday introduced a new set of tools that bring cloud customers the same AI capabilities that power Amaon.com, in the form of an API. Amazon Personalization is a real-time personalization recommendation service, while Amazon Forecast offers time-series forecasting. "This top layer is for companies and builders who don't want to mess with the models at all," AWS CEO Andy Jassy said. Primers: What is AI? Everything you need to know about Artificial Intelligence Machine learning? The AI, machine learning, and data science conundrum: Who will manage the algorithms?
Amazon Web Services' (AWS) CEO Andy Jassy has said his company will continue to focus on getting new products and services to market at speed, despite that resulting in lengthy delays for the majority of its 14 regions. "It's always a trade-off when you're launching these services," Jassy told ZDNet. "Do you want to wait until you have the services available in our 14 regions and 38 availability zones or do you actually want to get them into the hands of customers as quickly as possible." Jassy explained that having the services in the hands of customers as soon as possible allows the cloud giant to receive fast feedback that aids in bettering the services as they are rolled out globally. "We pretty consistently will choose speed over big, monolithic launches that mean we get capabilities in customers' hands a lot later.
The launch of Amazon Elastic Inference lets customers add GPU acceleration to any EC2 instance for faster inference at 75 percent savings. Typically, the average utilization of GPUs during inference is 10 to 30 percent, Jassy said. With a growing number of enterprises embracing machine learning on the cloud, Amazon Web Services is introducing new capabilities and tools to improve inference. Specifically, it's launching Amazon Elastic Inference and unveiling a new processor called AWS Inferentia. "If you think about the cost equation... the vast majority of cost - probably about 90 percent of it - is in inference," AWS CEO Andy Jassy said at the re:Invent conference in Las Vegas.
Amazon Web Services (AWS) has packaged up another in-house Amazon capability and made it available to customers, having announced Contact Lens for Amazon Connect on Tuesday. CEO Andy Jassy has touted that Contact Lens for Amazon Connect -- the company's omnichannel cloud contact centre service -- will stitch together new abstractions for machine learning so AWS customers can have an easy to consume function. "Amazon Connect is one of the fastest growing services in the history of AWS … off to a blazing start," he said during the day one keynote of AWS re:Invent in Las Vegas. "Using the same customer service technology Amazon has used … it's really easy to use." According to Jassy, Connect is the first call centre in the cloud with machine learning in mind.