Published January 15, 2025
By : Staff Writer
Aimee Do was a business integration specialist, program, and people manager with Boeing Global Services. In 2013, she received a Special Recognition Award for managerial leadership, technology, and community services at the WOC STEM Conference.
For more than 30 years, she provided mentoring and coaching to young adults. Many have become engineers, medical doctors, managers, and small business owners.
Aimee developed a mentoring program for more than 400 engineers and technical employees. She also leveraged her project management experience to provide consultation on improved operations.
Aimee served as president and CEO of a non-profit 501(c)3 corporation providing scholarships to financially challenged college and K-12 students.
She was an active donor to the Seattle Cancer Alliance, Swedish Cancer Institute, and the Virginia Mason Foundation.
During her career in the aerospace industry, Aimee worked as a software engineer at IBM, HP, and Hughes Aircraft Company.
She earned a master's degree in engineering management from Washington State University and a bachelor's degree in mathematics and computer science.
Recently, two senators from Oregon and Nebraska introduced resolutions to the Senate honoring computer science icons: Ada Lovelace and Grace Hopper.
Ada Lovelace is often referred to as the “first programmer” for her work on the world's first mechanical computer and recognizing the machine’s future potential.
Grace Hopper was a United States Navy Admiral and computer scientist, who developed the programming language Common Business Oriented Language (COBOL), still used today.
NVIDIA's "Grace" CPU is named in honor of Grace Hopper, the pioneering computer scientist and U.S. Navy rear admiral who made significant contributions to the development of programming languages.
This naming pays tribute to her legacy in computing.
In March 2024, NVIDIA launched the Blackwell platform, enabling organizations to build and run real-time generative AI on trillion-parameter large language models at costs and energy consumption that are up to 25 times lower than its predecessor.
The Blackwell GPU architecture incorporates six transformative technologies for accelerated computing, aimed at unlocking breakthroughs in data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing, and generative AI—key emerging opportunities for NVIDIA.
"For three decades, we've pursued accelerated computing to enable transformative breakthroughs like deep learning and AI," said Jensen Huang, founder and CEO of NVIDIA.
"Generative AI is the defining technology of our time. Blackwell is the engine to power this new industrial revolution. Working with the most dynamic companies in the world, we will realize the promise of AI for every industry."
Notable organizations expected to adopt the Blackwell platform include Amazon Web Services, Dell Technologies, Google, Meta, Microsoft, OpenAI, Oracle, Tesla, and xAI.
The Blackwell architecture itself is named after mathematician David Blackwell, who was renowned for his work in game theory, probability theory, information theory, and statistics—fields that have influenced the design and training algorithms of transformer-based generative AI models.
Blackwell was the first African American scholar to be inducted into the National Academy of Sciences.
With the Grace Blackwell architecture, enterprises and researchers can prototype, fine-tune, and test models on local Project DIGITS systems running the Linux-based NVIDIA DGX OS.
They can then seamlessly deploy these models on NVIDIA DGX Cloud™ accelerated cloud instances or data center infrastructure.
This approach allows developers to prototype AI on Project DIGITS and subsequently scale their solutions using the same Grace Blackwell architecture and the NVIDIA AI Enterprise software platform.
Project DIGITS users have access to a wide library of NVIDIA AI software for experimentation and prototyping, including software development kits, orchestration tools, frameworks, and models available in the NVIDIA NGC catalog and the NVIDIA Developer portal.
Developers can fine-tune models using the NVIDIA NeMo™ framework, accelerate data science with NVIDIA RAPIDS™ libraries, and run popular frameworks such as PyTorch, Python, and Jupyter notebooks.
To build intelligent AI applications, users can also utilize NVIDIA Blueprints and NVIDIA NIM™ microservices, which are available for research, development, and testing through the NVIDIA Developer Program.
When AI applications are ready to transition from experimentation to production, the NVIDIA AI Enterprise license provides enterprise-grade security, support, and access to NVIDIA AI software product releases.
