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Google adds SandboxAQ’s quantitative AI models to cloud offerings

SandboxAQ, a quantum computing startup spun off from Alphabet, announced that its Large Quantitative Models (LQMs) are now available on Google Cloud.

Google, in its response to the probe, noted the CMA's comment that search was vital for growth.Google has no plans to comply with the soon-to-be formalised set of rules.(File photo)

Quantum startup SandboxAQ said its large quantitative models (LQMs) will be available on Google Cloud, the company told Reuters on Tuesday, as cloud providers look to AI tech to fuel growth.

LQMs are designed to handle large-scale numerical datasets, perform complex calculations and statistical analysis, and can be used to develop sophisticated financial models or to automate trading strategies.

The partnership will make it easier for enterprises to use Google Cloud to develop its LQMs and deploy them, allowing Sandbox, a firm spun off from Google-parent Alphabet in 2022, to expand the distribution of its platform to a larger pool of potential customers.

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“More than 80% of the economy is run by math and quantitative relationships. And that’s where quantitative AI really shines, and it’s very complementary to language models,” CEO SandboxAQ, Jack Hidary said.

This is the first time Sandbox will have its models available on a third-party platform.

The Palo Alto-based startup secured $300 million in a funding round last month, boosting its valuation to $5.6 billion and was backed by investor firms including Fred Alger Management, T. Rowe Price, and Breyer Capital.

SandboxAQ said its models are used in sectors such as life sciences, financial services and navigation.

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Google has been intensifying its efforts in quantum computing and announced in December that it had made significant progress by developing a new generation of quantum chips, overcoming a major challenge in the field.

Microsoft also touted the potential of quantum computing earlier this month and unveiled its “Quantum Ready program”, while Nvidia’s CEO Jensen Huang said the technology’s practical use was likely two decades away.

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