IBM beat revenue estimates for the second quarter of 2021, increasing revenue for the quarter by about 3% to $18.7 billion, compared to the same quarter in 2020.
IBM CEO Arvind Krishna attributed much of the growth to a post-pandemic rebounding of business activities and the general economy. The company’s Global Business Services consulting business was a major contributor to the revenue increase, with revenue more than 11% year-over-year for that unit, while IBM’s systems-related revenue declined about 7% for the same period, and its Global Technology Services segment saw a slight revenue increase.
On an earnings call, Krishna discussed recent achievements--like the company’s unveiling of 2-nm chip technology in May--and near-term market opportunities at length, but also took time to hype the company’s quantum computing innovations and how they could translate to real business value for IBM customers.
“Quantum is an area of incredible promise slated to unlock hundreds of billions of dollars of value for our clients by the end of the decade,” he said, according to the Motley Fool earnings transcript. “To help business and society reap the benefits of quantum computing, we have put a road map in place to build 1,000-plus qubit computer by 2023.”
Krishna added, “We are forging a series of major partnerships to advance the business and science of quantum computing and post quantum encryption. This quarter, we have announced we'll join forces with the University of Tokyo in Japan, the STFC Hartree Centre in the United Kingdom 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 adopting a heavy-hex lattice architecture for quantum computing that is expected to help reduce error rates, and issue that has continued to hound the emerging quantum computing sector.
The latest of IBM’s quantum computing innovations was discussed in a Nature Physics paper published last week, in which the company explained “how our quantum kernel algorithm provides a provable exponential speedup over classical machine learning algorithms for a certain classification problem,” according to an email from an IBM spokeswoman. “Classification is one of the most fundamental problems in machine learning… Given that datasets are getting more complex and neural networks are becoming more sophisticated and expensive to train, quantum computation offers an avenue to increase the power of machine learning models.”
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