Zcash co-founder proposes terminating automatic ZCG fund allocation, with the remaining 8% of block subsidies to be transferred to NSM.

According to CoinGecko data, PEARL has fallen from a two-day high of roughly $2.44 to around $1.82 as of October 27, a drop of approximately 25.4%. Its current market capitalization stands at $628 million, with a fully diluted valuation (FDV) of $3.67 billion. The token's price decline has also lowered the USD value of mining output. F2Pool's Pearl page indicates that, based on current network metrics, 1 TH/s of hash power yields about 0.01364887 PRL per day. Calculations using the graphics card hash rate table from the NiceHash mining pool guide show the following theoretical daily outputs: RTX 3080 Ti (129 TH/s) yields ~1.76 PRL, equivalent to ~$3.20; RTX 3080 (115 TH/s) ~1.57 PRL, ~$2.86; RTX 3070 (70 TH/s) ~0.96 PRL, ~$1.74; RTX 3060 Ti (65 TH/s) ~0.89 PRL, ~$1.61; RTX 3060 (47 TH/s) ~0.64 PRL, ~$1.17. For 20-series GPUs, theoretical daily outputs are as follows: RTX 2080 SUPER (48 TH/s) yields ~0.66 PRL, ~$1.19; RTX 2060 SUPER (39 TH/s) ~0.53 PRL, ~$0.97; RTX 2060 (24 TH/s) ~0.33 PRL, ~$0.60. These figures are theoretical daily output values calculated based on current token price and nominal hash rate, and do not account for electricity costs, pool fees, or equipment depreciation. F2Pool's PRL mining pool uses a 1% PPLNS payout model; actual earnings are also affected by share fluctuations and network difficulty changes, so the above amounts should not be treated as net profit.

Insight from Beating AI News: Ant Group’s Lingguang App has launched version 2.0, shifting its focus from chatbot and mini-app generation to a personal AI Agent that assists users with long-term task management. The new version features long-term memory and proactive execution: users only need to state their goals, and the AI will organize steps, follow up continuously, and proactively alert users to key changes, eliminating the need for repeated inquiries. Its new "Help Me Manage" function handles long-term, recurring tasks, such as checking product prices at set intervals and notifying users when they drop to a specified level, or tracking flights, hotels, and travel itineraries to adjust plans promptly in case of delays or restrictions. The update also adds a "My Life" page that centralizes ongoing managed tasks and progress updates requiring user attention. Beyond alerts, Lingguang can now perform actual actions. Previous beta tests showed it connects to external services via Skills and MCP, with examples including sending messages on DingTalk, and querying or controlling smart home devices.

According to Farside data, U.S. spot Bitcoin ETFs posted a net inflow of $110 million yesterday, with only BlackRock’s IBIT disclosing inflow/outflow figures. Separately, U.S. spot Ethereum ETFs saw a net outflow of $88.6 million. Of that total, BlackRock’s ETHA recorded a net outflow of $104.7 million, while Fidelity’s FETH reported a net inflow of $16.1 million.

Glassnode said in a recent post that investors who bought Bitcoin (BTC) recently have moved out of the strong selling zone. In late September, nearly all positions held by short-term BTC holders were in profit, a figure that has since dropped to around 70%. For investors expecting BTC’s uptrend to continue, current entry conditions have improved significantly compared to a month ago. The decline in the profit ratio of short-term holders indicates that selling pressure from take-profit orders has eased, though this does not guarantee BTC will rise going forward.

Moody's Analytics chief economist Mark Zandi stated that the Federal Reserve will not and should not raise interest rates again at its meeting this week. The U.S. economy is facing growing risks, with the Fed's own policy missteps being one of them. This is the clear message conveyed by Moody's "Risk Matrix". The matrix assesses risks by evaluating two key metrics: the likelihood of each risk materializing over the next 12 to 18 months, and the potential economic damage it could cause if it occurs. A large number of red alerts have been triggered in the matrix, signaling that risks are becoming more probable or more severe. (Jinshi)

Bitcoin analyst Willy Woo has published an article introducing a BTC Monte Carlo simulation model inspired by Sminston With, which generates price paths based on Bitcoin’s historical market performance via a random number generator to simulate potential future trends. Woo noted the model made three key adjustments: first, it incorporates BTC’s cyclical market structure; second, it reconstructs Bitcoin’s true probability distribution from historical data, rather than fitting it to a preset ideal distribution; third, it uses data from the 2018 market bottom through the 2022 market bottom as input, deliberately excluding earlier BTC market data to better reflect the modern market environment shaped by derivatives, ETFs and rapid liquidation mechanisms. Additionally, the model retains a power-law scaling mechanism to capture the phenomenon of diminishing returns for BTC across each cycle. Woo specifically highlighted the 28th percentile simulation path, as it aligns with a pattern he observed: the next market bottom may find support near the previous cycle’s peak. Previously, Sminston With shared another Monte Carlo experiment projecting BTC simulations to 2034, which ran 5,000 total trials. Its results showed no simulated price fell below the current ~$80,000 level; the median result was ~$1.48 million, and even the lowest 5% of outcomes reached ~$464,000. It is important to note that these figures are simulation results based on specific assumptions and historical data, not definitive price predictions. The model’s conclusions are subject to factors including input data, diminishing return assumptions, and changes in market structure.