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The MGA also found that only a small number of respondents had fully established AI risk assessment processes or incident-response plans.

Speaking at the launch event, MGA CEO Charles Mizzi emphasized that the framework is meant to foster progress rather than stifle it.

“Our role as a regulator is not to stand in the way of innovation, but to help create the certainty and confidence needed for innovation to flourish responsibly,” Mizzi said.

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The investing and news site announced last week that it halted an arrangement in which it used Polymarket prediction market data for a dedicated hub on the website.

That relationship ended in April, just six months after it started. Yahoo Finance confirmed the end of that agreement to Bloomberg but noted that Polymarket remains an advertising partner.

“The new hub will display probability data from Polymarket for key economic, government, & market outcomes,” said Polymarket in a post on X last November. “Each probability view will be paired with related news, quotes, & analysis from Yahoo Finance + its partners. By combining trusted data with in-depth analysis, the hub will empower investors to make smarter, more strategic prediction market investments.”

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In the old model, Grenstad says, the product owner decided what to build, the developer decided how to build it, QA tested it and operations eventually handled the release.

As discussed last month, QA has become part of the process rather than a final stage. Product engineers consider from the planning stage what can be automated and what needs manual testing, while QA specialists now strengthen automation and identify gaps in coverage.

The responsibility for a piece of work increasingly extends from identifying the problem to building, releasing and measuring the result.