Dormant Wallet Moves 999.953 $BTC ($78.12M) After 6 Years of Inactivity

According to data from prediction market platform Predict.fun, the quarterfinal match of the 2026 League of Legends World Championship will pit TES against IG. As of now, IG’s win probability stands at 53%, while TES’s is 47%, with the two sides’ predicted odds being relatively close. Per the tournament schedule, this match will officially kick off at 06:00 Beijing Time, adopting a BO5 format; the winner will advance to the semifinals. The remaining quarterfinal matches will be held consecutively from November 4 to 7, with the other three matchups being GEN vs LYON, DK vs BLG, and T1 vs KC respectively. Note: Prediction market probabilities may change in real time based on market trading; please refer to the latest odds on the platform.

According to monitoring from Onchain Lens, FalconX has once again transferred 50,000 HYPE tokens to Coinbase, valued at around $4.2 million. Cumulative transfers of HYPE to Coinbase over the past three days total 350,000 tokens, worth approximately $30.57 million.

Beating AI Express News: ByteDance’s AI Agent platform Coze announced it will phase out its current enterprise version. Starting November 30, new customer purchases of Coze’s standard and flagship enterprise editions will no longer be accepted. Old packages on Volcano Engine will be discontinued on December 31 this year, while new enterprise packages will be fully phased out on December 31, 2027. Existing enterprise customers can still renew subscriptions and add seats, but their service term cannot exceed the aforementioned date. An IDC report shows that in 2025, Coze ranked first in China’s public cloud agent development platform market with a 19.3% revenue share. However, the annual software revenue of this niche market is only around 250 million yuan, with Coze’s corresponding scale roughly estimated at about 48 million yuan. There were prior signs of this exit: in August, ByteDance integrated Coze and the TRAE team into its Doubao system, and later launched the office Agent “Doubao Work”. The AI programming, agent development, and office execution capabilities originally scattered across different products have begun to be centralized under Doubao.

Binance founder Changpeng Zhao (CZ) told an interviewer that following the attack, Binance immediately came forward to clarify that user funds were unharmed and user assets were safe. While this was a straightforward statement, it effectively halted the spread of panic and prevented a chain reaction. The market recognized the incident would not lead to further spillover effects. Unlike past cases where platforms or lending protocols collapsed, leaving users to absorb losses, this time users would not be forced to bear related losses— a stark contrast to previous incidents that often triggered second and third rounds of cascading shocks. First, this statement calmed the market, Zhao noted. Second, Binance’s ability to stand behind this commitment on its own credibility made users willing to trust the firm’s words, especially since much of the fund flow and transaction data on the blockchain is public and transparent. Users understood Binance had sufficient financial strength to cover any losses: the exchange holds the SAFU (Secure Asset Fund for Users), a futures insurance fund, as well as robust capital reserves and a strong balance sheet. It is this rapid response, proactive accountability, and ability to ensure all users are protected and all losses are covered that gradually restored calm to the market. One notable detail: on the day of the hack, the cryptocurrency market’s decline was actually smaller than that of the tech stock market—a scenario almost unheard of. Typically, when stocks fall, crypto markets drop more sharply as investors sell digital assets to hold cash. But this time, even amid a major hack in the crypto sector, the market’s pullback was milder. Zhao said this shows investors remained largely calm overall, and reflects the solid trust in platforms built over years. “I am very proud of this,” he added.

Beating AI Express (Dongcha) reports: Hume has launched the Audio Decision API, which enables direct queries of audio recordings. Supported questions include "How many people are speaking?", "Did the customer service agent interrupt the client?", and "Does the client sound agitated?" The tool can also pinpoint the exact timestamps of laughter and sighs. Users can submit up to 25 queries at a time; the model delivers judgment results and probabilities without prior transcription of audio content. Previously, analyzing metrics like number of speakers, emotional shifts, interruptions, and background noise in a call required combining multiple specialized models, with each new analysis task often needing adjustments to the entire workflow. Hume centralizes these judgments into a single model that processes audio directly to answer queries. Developers only need to modify their questions to analyze new audio features and conversational behaviors, eliminating the need to retrain models or design custom classifiers. A single API can cover a wide range of distinct audio analysis tasks. The model is trained on over 10 million human judgment data points, aiming to predict how average people would react to the same audio. For example, a 70% "agitated" output indicates approximately 70% of listeners would perceive the speaker’s tone as agitated. In official preliminary tests, the model’s agreement rate with multi-reviewer consensus reached 70.7%, outperforming the 56.5% average of individual human raters. Hume reported an average score of 82% across 10 audio benchmarks, higher than Gemini 3.8 Flash’s 78% and Qwen 3.8-Omni-Flash’s 76%. The API is currently available via permission application only, priced at $0.47 per million input tokens. Per official examples, analyzing a 5-minute call costs roughly $0.012. It supports audio clips from 5 seconds to 5 minutes per request; real-time analysis requires submitting short audio segments sequentially.

Binance founder CZ said in an interview, "Security breaches always seem impossible until they happen, right? But often, right before an incident, people overlook key details. Therefore, every security incident is actually preventable with sufficient effort and attention. I believe we can learn many lessons from these cases. Without sufficient technological application and market uptake, the tech sector may struggle to secure adequate investment. Thus, market demand must grow in tandem, and the two must reinforce each other. We cannot wait until technology reaches 100% maturity to act, as technology will never be absolutely mature—it is always in a state of continuous improvement. AI technology is advancing at a rapid pace, but it also brings many challenges, including security risks. In the past, we might see a single hack every month or even less frequently, but now they can happen weekly. Just yesterday, four cryptocurrency exchanges were hit by separate hacking incidents. I predict that the frequency and speed of hacks will continue to rise in the future, as bad actors increasingly leverage AI. At the same time, we must also make greater use of AI technology to strengthen defenses. To counter a powerful adversary, you often need to possess comparable capabilities. Therefore, we must build our own AI-powered capabilities to address these threats. There is no so-called 'perfect time' to wait until technology is fully mature and all security issues are resolved before acting. Technology and security defenses are always evolving."