AI

Peeking into AI’s ‘black box’ brain — with physics

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.

AI

Who. What. Why. New IBM algorithm models how the order of prior actions impacts events

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.

AI

IBM’s Squawk Bot AI helps make sense of financial data flood

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.

Peeking into AI’s ‘black box’ brain — with physics

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.

Continue reading

Who. What. Why. New IBM algorithm models how the order of prior actions impacts events

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.

Continue reading

IBM’s Squawk Bot AI helps make sense of financial data flood

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.

Continue reading

COVID-19 a year later: What have we learned?

We’ve learned a lot during the past year about how to address global crises, but in my mind, one lesson cannot be ignored: The need for more strategic collaborations across institutions and sectors.

Continue reading

IBM’s innovation: Topping the US patent list for 28 years running

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.

Continue reading

After an unpredictable 2020, here’s what to expect for hybrid cloud in 2021

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.

Continue reading

IBM’s Dmitri Maslov joins IEEE’s 2021 class of Fellows 

IBM's Dr. Dmitri Maslov named IEEE Fellow for “quantum circuit synthesis and optimization, and compiling for quantum computers.”

Continue reading

Light and in-memory computing help AI achieve ultra-low latency

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 […]

Continue reading

Goldman Sachs & IBM researchers estimate quantum advantage for derivative pricing

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.

Continue reading

The future of crypto: IBM makes a new leap with Fully Homomorphic Encryption

IBM delivers first-of-its-kind security homomorphic encryption services offering for companies to begin experimenting with FHE.

Continue reading

The IBM Quantum Challenge Fall 2020 results are in

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, […]

Continue reading

IBM-Stanford team’s solution of a longstanding problem could greatly boost AI

IBM-Stanford team’s solution of a longstanding problem could greatly boost AI.

Continue reading

IBM launches blockchain for high-end textile for transparency of the supply chain

A new solution for the textile industry use blockchain allows users to track the entire spectrum of fabric manufacturing.

Continue reading