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first_img Tavus claims that the Griffin model causes 48% of video call participants to mistakenly believe they are interacting with a real person

AI startup Tavus released a new model called Griffin on October 1, referring to it as the first "human interaction model" that can understand and generate face-to-face conversations, paying attention not only to wording but also to expressions and pauses. Tavus stated that in tests, after a one-minute video call with Griffin-Lite, 26 out of 54 participants (48%) believed the other party was a real person; its previous generation system only convinced 1 out of 41 participants.Participants were told they would have a one-minute video call with another person to discuss things they were looking forward to this year, and only at the end of the call were they asked if they suspected the other party was not a real person. Tavus noted that those who became suspicious typically noticed within 20 seconds. This result comes from Tavus's own research page, where participants were recruited through a channel they call an independent research platform. Community comments on X pointed out that these results have not been independently verified and do not meet standard protocols.In the NVIDIA VideoFDB benchmark, Tavus claimed Griffin-Lite ranked first, with a generation dimension score of 3.83, the next best system scoring 2.8, and human reference scoring 3.92; the perception dimension score was 3.73, with the strongest baseline at 3.44 and human reference at 4.2. Tavus stated that NVIDIA independently conducted this evaluation. Griffin supports full duplex, allowing it to listen, see, and speak simultaneously, with an average audio-video delay of 0.43 seconds on the NVIDIA H100 chip. Tavus completed a $40 million Series B funding round led by CRV in November 2025.

The Inner Mongolia police in China are investigating a virtual currency money laundering case that used "free credit card repayment" as bait, involving nearly a thousand accounts

Recently, the police in Baotou, Inner Mongolia, China, investigated a virtual currency money laundering case. The criminal gang used "free credit card repayment" as bait to attract ordinary users to provide accounts. They received illicit funds from overseas gambling and fraud through false consumption, then contacted currency dealers to exchange for virtual currency and transferred it to designated addresses abroad. Through financial and on-chain data analysis, the police identified nearly a thousand involved accounts, with suspects distributed across Inner Mongolia, Shandong, Jiangsu, Hebei, Chongqing, and other regions.The Digital Currency Research Institute of the People's Bank of China stated that it is currently using large model technology to analyze the flow of funds in virtual currency transactions, restore the gang's trading patterns, and uncover clues related to illegal industries. Upon investigation, it was confirmed that seven members of the gang were illegally engaged in payment settlement business without approval from relevant national authorities, constituting the crime of illegal operation, and were sentenced to imprisonment ranging from one year and two months to two years and six months, along with fines.Using virtual currency for money laundering is a new type of money laundering crime that has emerged in recent years. Lv Wei, the president of the Inner Mongolia branch of the People's Bank of China, stated that enhancing the monitoring and identification capabilities for abnormal fund transactions related to virtual currency trading has helped successfully crack down on a major money laundering case involving virtual currency pyramid schemes, dismantling more than ten money laundering and points-running dens, and confiscating illegal gains of approximately 130 million yuan. In recent years, there have been coordinated efforts to promote the conviction and sentencing of four cases involving money laundering using virtual currency, forming a strong deterrent against illegal activities such as money laundering with virtual currency.

Wintermute: Bitcoin faces its first test after breaking through, with $82,500 becoming a key observation level

Wintermute posted that, on the macro front, risk assets continued to rise last week. Even with the U.S. 10-year Treasury yield breaking above 5%, a high not seen since 2007, there was no significant risk-averse sentiment in the market. Crypto assets led the way, with altcoins rising approximately 5%, followed closely by BTC, and the Nasdaq also recorded gains, while long-term U.S. Treasuries performed the weakest.The report believes that oil prices will be a key factor influencing the interest rate hike expectations for October. Currently, oil transportation through the Strait of Hormuz remains significantly below pre-conflict levels, with Brent crude prices nearing $103 per barrel. If oil prices continue to stay around or above $100 per barrel, market expectations for another rate hike in October may remain high, at which point the core issue will shift to whether risk assets can absorb further rate hikes in the short term while bonds remain under pressure.In the crypto market, BTC last week first stood above the 50-week moving average on a weekly basis, with the current level of $82,500 being the upper boundary of the previous consolidation range, which is also a key position to watch this week; if this level can stabilize, it may become the foundation for the previous breakout; otherwise, a drop below this level will reignite concerns about the validity of the breakout. Meanwhile, BTC's market share has increased, the breadth of altcoin gains is at a relatively high level, and institutional options trading continues to increase with low Delta bullish options and call spreads being added for year-end positioning.
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