Feb 20, 2024 · Machine Learning. Machine learning uses data to teach AI systems to imitate the way that humans learn. They can find the signal in the noise of big data, helping businesses improve their operations. We've been in the field since since the beginning: IBMer Arthur Samuel even coined the term “Machine Learning” back in 1959. Our work

Snap Machine Learning (Snap ML in short) is a library for training and scoring traditional machine learning models. Such traditional models power most of today's machine learning applications in business and are very popular among practitioners as well (see the 2019 Kaggle survey for details). Snap ML has been designed to address some of the ...

Aug 22, 2023 · As the name suggests, RAG has two phases: retrieval and content generation. In the retrieval phase, algorithms search for and retrieve snippets of information relevant to the user’s prompt or question.

Jul 12, 2021 · Quantum Machine Learning. We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug discovery to fraud detection. We're doing foundational research in quantum ML to power tomorrow’s smart quantum algorithms. Our work

Feb 8, 2023 · Aim a firehose of data at a human, and you get information overload. But if you do the same to a computer, you get machine-learning models that can learn to complete sentences as you type or detect tumors in medical scans that are often too subtle for a human eye to see.

May 9, 2022 · Similarly, late last year, we launched a version of our open-source CodeFlare tool that drastically reduces the amount of time it takes to set up, run, and scale machine learning workloads for future foundation models. It’s the sort of work that needs to be done to ensure that we have the processes in place for our partners to work with us ...

Nonetheless, there are other fields like machine learning, finance, or chemistry where quantum computation could be useful with current quantum devices. This manuscript aims to present a review of the literature published between 2017 and 2023 to identify, analyze, and classify the different types of algorithms used in quantum machine learning ...

Browse our catalog of recent publications authored by IBM researchers. This works shows why IBM is one of the most important contributors to modern computing.

The Machine Learning for Drug Development and Causal Inference group is developing machine learning models for innovative drug discovery technologies and bringing them to fruition for IBM clients. Our researchers believe that drug discovery can benefit from technologies that learn from the rich clinical, omics, and molecular data being ...

Oct 5, 2023 · Part of the Linux Foundation, PyTorch is a machine-learning framework that ties together software and hardware to let users run AI workloads in the hybrid cloud. One of PyTorch’s key advantages is that it can run AI models on any hardware backend: GPUs, TPUs, IBM AIUs, and traditional CPUs.