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QuantrolOx uses machine learning to control qubits

TechCrunch

QuantrolOx , a new startup that was spun out of Oxford University last year, wants to use machine learning to control qubits inside of quantum computers. Current methods, QuantrolOx CEO Chatrath argues, aren’t scalable, especially as these machines continue to improve. million (or about $1.9

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The key to operational AI: Modern data architecture

CIO

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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Bridging the IT skills gap, Part 1: Assessing current strategies and introducing GenAI as a unified solution

CIO

The gap between emerging technological capabilities and workforce skills is widening, and traditional approaches such as hiring specialized professionals or offering occasional training are no longer sufficient as they often lack the scalability and adaptability needed for long-term success. Contact us today to learn more.

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Unlocking the full potential of enterprise AI

CIO

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] AI in action The benefits of this approach are clear to see.

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The AI Future According to Google Cloud Next ’25: My Interesting Finds

Xebia

Native Multi-Agent Architecture: Build scalable applications by composing specialized agents in a hierarchy. ADK powers the newly announced Agentspace, Google’s research agent and Google customer support agents. BigFrames provides a Pythonic DataFrame and machine learning (ML) API powered by the BigQuery engine.

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Scaling AI talent: An AI apprenticeship model that works

CIO

We are fully funded by the Singapore government with the mission to accelerate AI adoption in industry, groom local AI talent, conduct top-notch AI research and put Singapore on the world map as an AI powerhouse. Because a lot of Singaporeans and locals have been learning AI, machine learning, and Python on their own.

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How Machine Learning is Used in Finance and Banking

Exadel

The banking landscape is constantly changing, and the application of machine learning in banking is arguably still in its early stages. Machine learning solutions are already rooted in the finance and banking industry. Machine learning solutions are already rooted in the finance and banking industry.