Between 2000 and 2001, IBM Research made headlines when it launched an internet-enabled designer watch running Linux, an open-source operating system. Dubbed WatchPad, its aim was to demonstrate the capabilities of the then-novel OS for mobile and embedded devices.
Our team has developed Physics-informed Neural Networks (PINN) models where physics is integrated into the neural network’s learning process – dramatically boosting the AI’s ability to produce accurate results. Described in our recent paper, PINN models are made to respect physics laws that force boundaries on the results and generate a realistic output.
To address the problem of ordinal impacts, our team at IBM T. J. Watson Research Center has developed OGEMs – or Ordinal Graphical Event Models – new dynamic, probabilistic graphical models for events. These models are part of the broader family of statistical and causal models called graphical event models (GEMs) that represent temporal relations where the dynamics are governed by a multivariate point process.
In our recent work, we detail an AI and machine learning mechanism able to assist in correlating a large body of text with numerical data series used to describe financial performance as it evolves over time. Our deep learning-based system pulls out from large amounts of textual data potentially relevant and useful textual descriptions that explain the performance of a financial metric of interest – without the need of human experts or labelled data.
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's Dr. Dmitri Maslov named IEEE Fellow for “quantum circuit synthesis and optimization, and compiling for quantum computers.”
Ever noticed that annoying lag that sometimes happens during the internet streaming from, say, your favorite football game? Called latency, this brief delay between a camera capturing an event and the event being shown to viewers is surely annoying during the decisive goal at a World Cup final. But it could be deadly for a […]
In a new preprint now on arXiv, “A Threshold for Quantum Advantage in Derivative Pricing”, our quantum research teams at IBM and Goldman Sachs provide the first detailed estimate of the quantum computing resources needed to achieve quantum advantage for derivative pricing – one of the most ubiquitous calculations in finance.
IBM delivers first-of-its-kind security homomorphic encryption services offering for companies to begin experimenting with FHE.
What does programming for the not-so-distant quantum future look like? From November 9 to 30, more than 3,300 people from 85 countries applied for the 2,000 seats of the IBM Quantum Challenge to find out. As our cloud-accessible quantum systems continue to advance in scale and capability with better processors of larger number of qubits, […]
IBM-Stanford team’s solution of a longstanding problem could greatly boost AI.