IBM exceeded revenue estimates for the second quarter of 2021, increasing revenue for the quarter by approximately 3% to $ 18.7 billion compared to the same quarter in 2020.
IBM CEO Arvind Krishna attributed much of the growth to post-pandemic business and general economic recovery. The company’s Global Business Services consulting business was a major contributor to revenue growth, with revenue exceeding 11% year-over-year for that unit, while IBM’s systems-related revenue declined approximately 7% over the same period and Global Technology saw the Services segment a slight increase in sales.
On a conference call, Krishna extensively discussed the latest achievements – such as the company’s launch of 2nm chip technology in May – and near-term market opportunities, but also took time to hype the company’s quantum computing innovations and how they are being implemented real business value for IBM customers.
“Quantum is an area with incredible prospects that should unlock hundreds of billions of dollars in value for our customers by the end of the decade,” he said, according to the Motley Fool Results Log. “To help business and society take advantage of quantum computing, we have drawn up a roadmap to build more than 1,000 qubit computers by 2023.”
Krishna added, “We forge a number of important partnerships to advance the business and science of quantum computing and post-quantum encryption. For this quarter we have announced a cooperation with the University of Tokyo in Japan, the STFC Hartree Center in Great Britain and the Fraunhofer Institute in Germany. This builds on the partnership we announced last quarter with the Cleveland Clinic. “
IBM also announced earlier this month that it is introducing a heavy-hex lattice architecture for quantum computing, which is expected to help reduce error rates, and an issue that continues to haunt the emerging quantum computing sector.
The latest quantum computing innovations from IBM have been rolled into one Natural physics paper published last week in which the company explained “how our quantum kernel algorithm offers demonstrable exponential acceleration over classic machine learning algorithms for a specific classification problem,” said an email from an IBM spokeswoman. “Classification is one of the most fundamental problems in machine learning … As data sets are becoming more and more complex and neural networks are becoming ever more sophisticated and expensive to train, quantum computers offer an opportunity to increase the performance of machine learning models.”
RELATED: What Is Quantum Computing?