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During a session of the House Audit Committee last Thursday, members of parliament (MPs), the Data Protection Commissioner and representatives from the Welfare Benefits Administration Service (WBAS), the Gaming & Casino Supervision Commission and the National Betting Authority (NBA) convened to discuss ways to identify and restrict gambling activity among GMI beneficiaries, as reported by Cyprus Mail.

While the intention is to protect vulnerable households and ensure welfare is spent on essential needs, proposed measures are being complicated by legal, technical and privacy obstacles.

Harris Tsangarides, executive director of the Gaming & Casino Supervision Commission, said his department had noticed spikes in gambling activity coinciding with GMI payment dates, prompting the regulator to consider “technical solution” to cross-reference GMI beneficiary lists with casino membership records.

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The American Gaming Association estimates that the exchanges have siphoned more than $1.3 billion in would-be tax revenue from states. One of the AGA’s primary spokespeople pin its fight against prediction markets is former New Jersey governor Chris Christie, who championed the PASPA case to the Supreme Court.

As with PASPA, this matter revolves heavily around federalism versus states’ rights. Traditional sports betting is governed by individual state regulators with varying laws and regulations. Federal derivatives are regulated by the CFTC, which has fully embraced prediction markets under US President Donald Trump after rejecting them in previous administrations.

The web of lawsuits and court rulings involving prediction markets has greatly complicated the issue of jurisdiction. Kalshi has been forced to limit trading in multiple states, most notably Nevada, and the CFTC has gone to unprecedented lengths to protect its licencees. This includes suing nine states directly and issuing emergency orders to reject state mandates.

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Cubeia’s first phase was an open approach to AI. Developers could use it whenever they wanted. Phase two brought structure, with everyone using the same agents and working through the same AI-driven pipeline. That required Cubeia to solve questions around quality, reliability and how agents could work together, while getting employees comfortable with the new way of working. Grenstad believes that work has largely been completed.

“During the hybrid period in Q1, Cubeia solved 259 issues. Once it moved to the AI-driven process, that figure rose to 421 – a 62% increase. Larger projects increased from 17 to 58. So the answer is yes: moving to AI-driven development has increased our output tremendously,” Grenstad says.

But the more important question now is what Cubeia does with that capacity. “Because we’re not spending as much time coding, we’re spending more time on the business: talking about value and understanding the domain,” he says.