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.
Snap machine learning - IBM Research
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 ...
Machine Learning and Data Mining - IBM Research
Since then, machine learning for structured data has become one of the major research areas in data mining and machine learning. Proud of our successes, we are actively tackling the frontiers in machine learning and data mining, and applying the results to the real world, taking full advantage of our merit of proximity to advanced companies and ...
What is federated learning? - IBM Research
2022年8月24日 · In vertical federated learning, the data are complementary; movie and book reviews, for example, are combined to predict someone’s music preferences. Finally, in federated transfer learning, a pre-trained foundation model designed to perform one task, like detecting cars, is trained on another dataset to do something else, like identify cats.
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.
What is AI inferencing? - IBM Research
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 …
What is retrieval-augmented generation? - IBM Research
2023年8月22日 · Retrieval-augmented generation (RAG) is an AI framework for improving the quality of LLM-generated responses by grounding the model on external sources of knowledge to supplement the LLM’s internal representation of information. RAG implementation in an LLM-based question-answering system has two main benefits: It ensures that the model has ...
Machine Learning for Drug Development and Causal Inference
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 ...
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.
What are foundation models? - IBM Research
2022年5月9日 · 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 ...