Kids believe their generation has a much clearer understanding of gender compared to older generations, with 80% of kids and teens trusting people their age to understand who they are and their
gender, including how to articulate and express it. It has begun to surface in search results. The outcome will create challenges if not faced now.
Email personalization is the top method, with chatbots now in second place, Persado and Coresight Research report.
Attributing search results to source documents could help verify the accuracy of information. Researchers build transparent language models designed to evaluate sources.
The NewtonX Graph uses APIs to interface with private databases from partners including recruiting firms, professional associations, trade associations and conference organizers, data providers and
search engines such as Dow Jones Factiva, Bing, Google, LinkedIn, and Xing, among others. It scans for professionals that match customer criteria.
Google is working to correct racial as well as gender, sexual orientation, and other types of bias. AI training models pick up all these biases, such as recency.
Bing, with help from Microsoft Research, is using Natural Language Representation models to improve results on each search. On Tuesday the Microsoft search engine introduced a feature that serves a
one-word answer for queries, as well as a carousel of related excerpts from a variety of resources.
London-based Fabula applies machine-learning techniques to network-structured data. The new group will focus on natural-language processing, reinforcement learning, machine-learning ethics,
recommendation systems, and graph deep learning.