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More Tether FUD from WSJ

The Wall Street Journal’s report about stale allegations from long ago is wholly inaccurate and misleading. Bitfinex and Tether have world-class compliance programs and adhere to applicable Anti-Money Laundering, Know Your Customer, and Counter-Terrorist Financing legal requirements.

Bitfinex and Tether are proud partners of global law enforcement, and routinely and voluntarily assist the United States Department of Justice and other law enforcement organizations across the world in preventing money laundering, terrorism, and other crimes by bad actors.

These unfair attacks will not distract us from continuing with those efforts and offering the most liquid and reliable stablecoin experience, which the market has clearly recognized by making us the leaders in the industry.

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$450 Million Frozen And Counting: T3 Financial Crime Unit Continues Global Crackdown on Illicit Crypto Flows

14 May 2026 – The T3 Financial Crime Unit (T3 FCU), a joint initiative by Tether, TRON, and TRM Labs, announced today that it has frozen over USD 450 million in illicit assets globally, strengthening regulatory collaboration to target cryptocurrency-related financial crimes. This year, T3 FCU has successfully supported investigations into crimes involving banned or […]

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Tether Launches Developer Grants Program to Fund Local-First AI and Payments Infrastructure

11 May, 2026 – Tether, the largest company in the digital asset ecosystem, announced today that it is launching a grants program to fund developers building on its open technology stack, with no cap on total payouts, tied to specific technical deliverables. The grants program is now open, and developers can apply to active tasks. […]

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Tether Unveils Medical AI That Runs on Phones, Outperforms Much Larger SoTA Models, and Can Cut the Cloud Out Entirely

7 May 2026 – Tether’s AI Research Group today launched QVAC MedPsy, a new class of medical language models designed to run directly on smartphones, wearables, and other devices with limited processing power, delivering performance that rivals and, in some cases, surpasses significantly larger models while remaining local and private. Instead of scaling performance through […]

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