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The legislation to establish crypto market structure is one of three bills the US House of Representatives is expected to consider starting next week.

AI models generate immense value from user data. It’s time to demand onchain attribution and pay the people whose data makes AI possible with Payable AI, to ensure fair recognition and payment for everyone.

Meta's latest AI hire follows several developments and partnerships aimed at making the tech giant a leader in the burgeoning sector.

The ride-hailing giant has reportedly offered AI “coders for hire” since at least November.

Mark Zuckerberg bets $15 billion on an AI company as stablecoins win over Fortune 500 companies.

Lawmakers asked Mark Zuckerberg whether Meta had had any influence on the GENIUS stablecoin bill and its plans to potentially issue its own digital currency.

Mark Zuckerberg is reportedly assembling a superintelligence group that will include Scale AI founder Alexandr Wang.

The case for holding Bitcoin on a firm’s balance sheet is compelling, CoinShares’ Butterfill told Cointelegraph, and “the pace of adoption is accelerating.”

The AI arms race is moving too fast for safety, with companies pushing boundaries and governments lagging. AI-driven dehumanization and the unchecked proliferation of autonomous weapons require responsible leadership before it’s too late.

Meta will use nuclear energy to power its data centers and AI models with a 20-year deal to secure 1.1 gigawatts of energy from an Illinois facility.

Meta shareholders shut down a proposal to assess whether Bitcoin should be added to its balance sheet, with just 0.08% of votes in favor of the idea.

“EagleEye” will be the first headset Meta will make in partnership with defence contractor Anduril, says the firm’s co-founder, Palmer Luckey.

The decentralized AI industry has a chance to carve out market share, but it will need to prove its security and usefulness. Centralized AI’s dominance risks privacy, transparency and ethical standards.

Meta’s chief AI scientist, Yann LeCun, has reportedly said “world-based models” would be a better approach to AI, as these would be trained on real-life scenarios.

GPUs dominate the AI landscape, but CPUs remain an untapped resource capable of powering diverse AI tasks efficiently. Decentralized compute networks could save costs and scale AI infrastructure in smarter ways.