You may be the first person in your company focusing on the need to create or implement ethical AI. If so, I’d like to share some lessons learned that could help you in your work.
On December 19th, 2018, 2 dozen women working on AI ethics in tech companies, non-profits, and industry analysts came together for a day to share their experiences and insights, as well as to brainstorm solutions to big challenging we are facing.
We talked with T-Mobile about the larger trends and shifts in the communications industry, and how being customer-obsessed leads to business growth.
AI + Analytics is making the needs of the modern business user a reality in 2019. That’s why you need these six capabilities to take advantage of data insights now.
New year, new resolutions, new technologies! We talked with our product leaders, marketers and visionaries to predict what the future holds for CRM and beyond.
Read how USAA made a culture shift to put member experiences at the center of everything they do. The result is USAA now offers omnichannel services to their insurance policyholders to gain efficiencies and increase loyalty.
This summer, Salesforce Research announced our inaugural deep learning research grant for university researchers and faculty, non-profit organizations, and NGOs. Our goal is to identify and support diverse individuals with innovative ideas to join us in shaping the future of AI.
Check out these digital marketing tactics SMBs should do from MobileMonkey CEO, Larry Kim.
This post is for those responsible for implementing AI systems but do not have a background in data science, statistics, or probability. The intention is to create an approachable introduction to the key concepts to identify potential bias (error) in their training data.
It has been empirically observed that different local optima, obtained from training deep neural networks don't generalize in the same way for the unseen data sets, even if they achieve the same training loss.
