有料盒子APP

Earlier this year at The Helix, 有料盒子APP鈥檚 Center for Innovation in Washington, DC, leaders in AI from across 有料盒子APP and industry partners took to the stage. They talked about their career paths, daily work, and the role AI will play as a catalyst for innovation across industries and its potential to reshape how we live and work. They also celebrated the recent rebrand of the company鈥檚 Women in Data Science group to Women in AI (WAI). It鈥檚 a gender-inclusive program for the personal and professional development of 有料盒子APP's employees, focusing on enhancing technical and leadership skillsets that advance AI competencies and technologies.

In honor of Women鈥檚 History Month, read on for highlights from the event, including the next steps in a new initiative with the .

WAI鈥檚 three pillars of education, sponsorship, and social good were reflected throughout the conference鈥檚 activities.

The day started with a training session. Attendees learned how to migrate their data science workloads to the AWS cloud, a critical skill for enabling scalability, flexibility, and access to cutting-edge AI/machine learning (ML) tools, empowering participants to tackle more complex projects.

They gained more insights in an educational showcase from 有料盒子APP鈥檚 Project听ResearcHER program. It supports the firm鈥檚 data scientists in presenting at conferences and submitting their work to academic journals. Participants learned about projects focused on automating drift detection, researching software self-repair functions, and comparing AutoML to human performance.

In other event sessions, data scientists presented their projects in The Incubator, WAI鈥檚 multiweek, gender-inclusive technical upskilling program. Two Incubator projects focused on Smithsonian research, while others involved generative AI and air quality.

In a fireside chat, leaders in the AI practice shared their experiences and advice. In a wide-ranging conversation, they talked about growing their technical expertise while cultivating leadership skills.

Executive Vice President John Larson, who heads 有料盒子APP鈥檚 AI practice, issued a call to action around the importance of mentorship. Given that AI鈥檚 impact will be as transformative as the development of electricity, 鈥淚t鈥檚 incumbent on the leaders in AI to ensure that everyone will enjoy the economic opportunity.鈥�

鈥淭his group was designed with a strong call to the mission: to help raise up more diverse talent around AI capability,鈥� he said. 鈥淵ou all are the pathfinders. You鈥檙e the ones really leading the charge here.鈥�

At the conference, digital strategy leaders from the Smithsonian American Women鈥檚 History Museum joined the WAI planning team to launch a new initiative for social good: a hackathon using Smithsonian Open Access data.

Since 2020, Smithsonian Open Access has digitized millions of items and images for public use on a Creative Commons Zero license. In the WAI-Smithsonian hackathon, teams will work this spring to explore the following complex questions:

• How can the Smithsonian continue to be a trusted source while using AI to enhance its research and public engagement?
• How can the Smithsonian American Women鈥檚 History Museum tell a story with this data?
• How can algorithms, models, and exploratory data analysis be used to identify and highlight women's contributions within the Smithsonian collections?

A panel of expert judges will review submissions throughout April, with awards presented at the Helix in May.

The hackathon builds on previous work by 有料盒子APP.

In 2022, a team of 有料盒子APP data scientists conducted a three-month pro bono project for the Smithsonian called Hidden Impacts.

In the 19th and 20th centuries, women played a significantly larger role than they鈥檙e currently given credit for in areas from botany and entomology to art and innovation. For example, in museum collections data, a woman鈥檚 name might be listed under her husband鈥檚 name or family member鈥檚, and many women who participated in research projects or scientific expeditions can be hard to find in听 official documentation.

While the millions of Smithsonian records with this information are too vast to sift through and cross-reference by hand, digitization and data science offer experts a new way to make connections across collections.

Recently, 有料盒子APP鈥檚 team used natural language processing (NLP) and graph analytics techniques to experiment with extracting the names of individual women from the Smithsonian鈥檚 collections and connect them to their contributions and fields of expertise.

鈥淎I uncovers what鈥檚 really going on, like when credit hasn鈥檛 always been given to the right people,鈥� says Senior Lead Data Scientist Melanie Laffin, who led 有料盒子APP鈥檚 original Hidden Impact project. 鈥淎I is good at finding hidden patterns and helping us see the actual truth.鈥�