During the month of March, IBM Research put the spotlight on a number of women scientists and engineers, and asked them about their professional and personal motivations, journeys and experiences as women — and particularly, as women in STEM. They represent the breadth of career experiences at IBM Research, across disciplines, geographies, ethnicities, tenures and backgrounds, who share a passion for science and tech, as well as a commitment to help all women rise to meet their aspirations.
To help the developers that update legacy applications, our team has created Mono2Micro (monolith-to-microservice) – an AI assistant that modernizes legacy applications to help move them to the cloud as microservices. Our tool simplifies and speeds up the often error-prone “application refactoring” process of partitioning and preserving the original semantics of the legacy, monolith applications.
A patent is evidence of an invention, protecting it through legal documentation, and importantly, published for all to read. The number of patents IBM produces each year – and in 2020, it was more than 9,130 US patents – demonstrates our continuous, never-ending commitment to research and innovation.
IBM delivers first-of-its-kind security homomorphic encryption services offering for companies to begin experimenting with FHE.
IBM Research has partnered with Red Hat to bring iter8 into Kiali. Iter8 lets developers automate the progressive rollout of new microservice versions. From Kiali, developers can launch these rollouts interactively, watch their progress while iter8 shifts user traffic to the best microservice version, gain real-time insights into how competing versions (two or more) perform, and uncover trends on service metrics across versions.
New IBM, Fujifilm prototype breaks world record, delivers record 27X more areal density than today’s tape drives
IEDM 2020: Advances in memory, analog AI and interconnects point to the future of hybrid cloud and AI
At this year’s IEEE International Electron Devices Meeting, IBM researchers will describe a number of breakthroughs aimed at advancing key hardware infrastructure components, including: Spin-Transfer Torque Magnetic Random-Access Memory (STT-MRAM), analog AI hardware, and advanced interconnect scaling designed to meet those hardware infrastructure demands.
In 2021, our hybrid cloud predictions show that we expect businesses to address challenges in ways that will apply new resources and strategies to drive business outcomes, in a world that will continue to require new advances in cloud and AI research.
Our latest breakthrough in AI training, detailed in a paper presented at this year’s NeurIPS conference, is expected to dramatically cut AI training time and cost. So considerably in fact that it could help completely erase the blurry border between cloud and edge — offering a key technological upgrade for hybrid cloud infrastructures.
Unfortunately, there are no default scheduler plugins in Kubernetes to consider the actual load in clusters for scheduling. To achieve that goal, we developed a way to optimize resource allocation through load-aware scheduling and submitted our "Trimaran: Real Load Aware Scheduling" Kubernetes enhancement proposal, with the hope of soon merging this feature into the Kubernetes scheduler plugin.