Core Insights - The article discusses a unique case where judges in Nanjing, China, conducted a live-streaming sale of crabs to help a debtor repay their debts, showcasing an innovative approach to judicial asset disposal [3][11][22] Group 1: Judicial Innovation - The judges transformed from legal professionals to live-streaming hosts, selling crabs directly from a debtor's pond, which attracted over 200,000 viewers and generated sales of 57,000 yuan in just 2.5 hours [3][11] - This method of selling perishable goods like crabs is rare in judicial auctions, which typically focus on higher-value items like real estate or vehicles [5][7] Group 2: Market Dynamics - The crabs were sold at a price of 240 yuan for 10 live crabs, which were well-received by customers for their quality and freshness [3][4] - The approach aims to maximize the value recovered for debtors while minimizing waste, as traditional bulk auctions often lead to unsold items [24][31] Group 3: Broader Implications - The case reflects a potential shift in how courts handle asset liquidation, moving towards a more retail-oriented model that could increase participation and efficiency in the auction process [22][24] - Similar past instances include the sale of low-value items like soft drinks, indicating a trend where courts may resort to selling food and beverage items when other assets are unavailable [10][18]

Group 1 - The core issue of embodied AI is the sim-to-real dilemma, where high fidelity in simulation conflicts with cost, leading to challenges in transferring successful strategies from simulation to real-world applications [2] - The potential of 3D Gaussian Splatting (GS) technology has been underexplored, with recent advancements enabling high-fidelity 3D representations from standard devices, addressing the gap between low-cost real scene reconstruction and embodied navigation [3][4] - The proposed method, EmbodiedSplat, consists of a four-stage pipeline that captures real scenes using low-cost mobile devices and reconstructs them in high fidelity for effective training and deployment [4][6] Group 2 - The first stage involves capturing RGB-D data using an iPhone 13 Pro Max and the Polycam app, which simplifies the process and reduces operational barriers [11] - The second stage focuses on mesh reconstruction, utilizing DN-Splatter for 3D GS training, ensuring geometric consistency and minimizing reconstruction errors [11][12] - The third stage includes simulation training with a composite reward function to balance success, path efficiency, and collision avoidance, employing a two-layer LSTM for decision-making [10][13] Group 3 - The fourth stage is real-world deployment, where the Stretch robot connects to a remote server for strategy inference, allowing real-time navigation based on observed images [14][17] - Experiments validate the zero-shot performance of pre-trained strategies in new environments, revealing that scene scale significantly impacts performance [20][22] - Fine-tuning pre-trained strategies leads to substantial performance improvements across various environments, demonstrating the effectiveness of personalized adjustments [25][28] Group 4 - The study highlights the limited success of zero-shot transfer from simulation to real-world scenarios, with significant performance gaps observed [32] - Fine-tuning enhances the transferability of strategies, with success rates increasing significantly after adjustments [32][35] - The necessity of large-scale pre-training is emphasized, as it provides foundational knowledge that aids in adapting to new environments and overcoming real-world challenges [35][44]

Trade-in Programs & Discounts - Carriers offer up to $1,100 discount for trading in iPhone 13 Pro or newer models, which equals the price of a new iPhone 17 Pro [3][4] - Apple offers up to $320 for iPhone 13 Pro Max trade-ins [3] - Trade-in programs are not exclusive to the iPhone 13 Pro Max, but extend to newer models [3] Market & Consumer Behavior - Consumers are being told not to trade in their iPhone 13 Pro Max, based on perceived high value [1][2] - Wireless carriers are using trade-in deals to encourage customers to sign up for new plans [4]

Investment Analysis - Investing in Bitcoin (BTC) instead of buying an iPhone each year from 2017 to 2024 would have yielded significant profits, with an average profit of over 800% across all years [4] - The analysis shows zero losses when investing in BTC instead of purchasing iPhones during the specified period [4] - The best buying opportunity for BTC was during the 2018 bear market crash [2] Comparative Cost Analysis - The price of iPhones increased slightly from $1,000 to $1,200 over eight years (2017-2024) [4] - The amount of BTC needed to purchase an iPhone in 2025, with BTC at approximately $111,000, is just 0.011 BTC [9] Profitability Examples - Purchasing an iPhone X in 2017 required 0.072 BTC, which is now worth approximately $7,992, resulting in a profit of $6,993 (700% gain) [1] - Purchasing an iPhone XS Max in 2018 required 0.289 BTC, which is now worth approximately $32,079, resulting in a profit of $30,980 (2,815% gain) [2]