On Monday, ID.me released a statement from CEO and founder Blake Hall about what the vendor said is its commitment to federal guidelines for facial recognition technology. Hall said the vendor uses one-to-one face match technology and not one-to-many facial recognition. One-to-one face match is a simple application of the technology that is comparable to using one's face to unlock a smartphone or be verified at an airport, Hall said in an interview with TechTarget. "It's something that Americans do broadly all across the country when they're proving their identity in person," Hall said. "What it specifically is not is like taking one person's photo and then taking like a city's worth of images and trying to like match that person's face."

When Katica Roy returned to work after the birth of her daughter, her supervisor asked her to take on two new teams, tripling her workload in a matter of two weeks without additional pay or a promotion. Meanwhile, management asked a male colleague to take on one extra team. With his new responsibilities came a promotion and more pay. In order to get the pay equity due her, Roy notified her human resources team about the Lilly Ledbetter Act, a federal law that helps pay practices are non-discriminatory and fair, without gender or other bias, by making it easier to file equal-pay lawsuits. While she ended up succeeding in her gender bias protest, the process led Roy to found and become CEO of Pipeline Equity, a SaaS vendor that uses cloud-based AI, machine learning and natural language processing (NLP) technology to improve the financial performance of its users by trying to close the gender equity gap.

AWS has made its CodeGuru tool generally available for developers. The tool, initially released in preview at the AWS re:Invent conference last December, uses machine learning to make recommendations on how developers can improve the quality of their code quality, as well as identify an application's most expensive lines of code. "CodeGuru helps you improve your application code and reduce compute and infrastructure costs with an automated code reviewer and application profiler that provide intelligent recommendations," said Danilo Poccia, chief evangelist for the EMEA region at AWS, in a blog post. "Using visualizations based on runtime data, you can quickly find the most expensive lines of code of your applications. With CodeGuru, you pay only for what you use."

As part of this expansion, IBM added more data scientists and AI engineers, which has resulted in new projects, such as the Model Asset eXchange (MAX) and the Fabric for Deep Learning (FfDL) which is pronounced "fiddle." MAX is an open source ecosystem for data scientists and AI developers to share and consume models that use machine learning engines, such as TensorFlow, PyTorch and Caffe2, Diaz said. It also provides a standard approach to classify, annotate, and deploy these models for prediction and inferencing. Additionally, developers can train and deploy MAX models for production workloads that use Watson Studio, such as internet-of-things applications, said Guido Jouret, chief digital officer at ABB. IBM's MAX not only avoids the cost and time for developers to create these models themselves, but they also get access to the open source community to continually add and improve on these models, said Kathleen Walch, senior analyst at Cognilytica, based in Washington, D.C.. "It helps level the playing field for smaller companies [that] don't have as much data or resources," she said. Meanwhile, FfDL presents a cloud-native service for popular open source frameworks TensorFlow, Caffe and PyTorch.