Machine Learning - IBM Research
2024年2月20日 · 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
Quantum Machine Learning - IBM Research
2021年7月12日 · 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
What are foundation models? - IBM Research
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 ...
Systematic literature review: Quantum machine learning and its ...
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 ...
Artificial Intelligence - IBM Research
2024年12月20日 · International Conference on Machine Learning. ... ICLR 2024. 38. International Conference on Learning ...
Neuro-symbolic AI - IBM Research
2021年10月12日 · Neuro-symbolic AI. We see Neuro-symbolic AI as a pathway to achieve artificial general intelligence. By augmenting and combining the strengths of statistical AI, like machine learning, with the capabilities of human-like symbolic knowledge and reasoning, we're aiming to create a revolution in AI, rather than an evolution.
Machine Learning with Graphs in High-Performance Computing …
The intent of this workshop is to bring together researchers, practitioners, and scientific communities to discuss methods that utilize extreme scale systems for learning graph data. This workshop will focus on the greatest challenges in utilizing high-performance computing (HPC) for machine learning with graphs and methods for exploiting ...
What is synthetic data? - IBM Research
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.
When Machine Learning meets Dynamical Systems: Theory and …
The recent wave of using machine learning to analyze and manipulate real-world systems has inspired many research topics in the joint interface of machine learning and dynamical systems. However, the real world applications are diverse and complex with vulnerabilities such as simulation divergence or violation of certain prior knowledge.
What is retrieval-augmented generation? - IBM Research
2023年8月22日 · 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.