Finding solace in quantum computing

Google's announcement of Willow, a quantum chip that reduces errors as complexity rises, holds the promise of a real breakthrough in computing. Quantum computing assigns probabilities to the binary logic of classical computing, which allows for magnified processing capacity. However, quantum bits hold their state for only fractions of a second and are prone to error as more of these are added to a chip. Google's claim that it has found a way to reduce errors as it adds more qubits clears a hurdle in the commercial application of quantum computing. Other claims about how fast Willow is relative to classical computing may be open to interpretation, but that does not diminish Google's achievement in quantum chip architecture.

There is little immediate effect, though, of the breakthrough on the development of generative AI, for which Google admits the climb may have become steeper. LLMs on which generative AI trains are yet to generate profit for their creators. Some of this is due to computing costs, which a chip like Willow may eventually address. As AI reaches commercial viability, it will benefit from the possible practical applications of quantum computing. Yet, Google is claiming the supremacy of its chip on one metric by which they are assessed. It may have to work on other parameters that provide a more holistic assessment of a quantum chip's performance.

The field is still open for AI, and that is reflected in how investors are valuing its champions. Alphabet, Google's holding company, rose on news of Willow but is trailing Microsoft and Amazon in valuation gains this year. Tech companies will continue to chase their hardware fix in their AI race, but quantum computing is unlikely to deliver before algorithms profitably take over decision-making from humans on a wider scale. There is heavy lifting ahead in making AI commercially viable, which could affect the pace of quantum computing development.