National payment systems

 National payment systems are established by central banks or governments to ensure payment sovereignty, lower costs, and reduce reliance on Western-dominated networks like SWIFT. [1]

🇧🇷 Brazil

• Pix: Created by the Central Bank of Brazil, it is a highly successful instant bank transfer network utilizing QR codes and phone numbers.
• Elo: A prominent domestic card network supporting credit and debit transactions. [1, 2, 3]

🇨🇳 China

• CIPS (Cross-Border Interbank Payment System): Offers clearing and settlement services for cross-border Renminbi (Yuan) transactions, serving as a direct alternative to SWIFT.
• UnionPay: The massive state-backed domestic and international card scheme.
• Digital Yuan (e-CNY): China's central bank digital currency (CBDC) actively used for pilot programs and domestic retail payments. [1, 2, 3, 4, 5]

🇷🇺 Russia

• SPFS (System for Transfer of Financial Messages): Developed by the Central Bank of Russia as a SWIFT replacement following international sanctions.
• Mir: The national card payment system managed by the National Payment Card System (NSPK).
• FPS (Faster Payments System): The domestic instant mobile transfer architecture managed by the central bank. [1, 2, 3, 4, 5, 6]

🌐 Other Major National Systems Around the World

Widely used domestic mobile payment system built around six-digit unique codes. 🛠️ Interoperability Initiatives Driven by geopolitical shifts and the desire to bypass Western networks, the broader BRICS alliance is actively building BRICS Pay. Rather than building one centralized global ledger, this project acts as an open, decentralized payment bridge designed to link these highly sophisticated individual national switches (like Pix, UPI, and CIPS) directly together. [1, 2, 3]

IDF uses AI to predict casualties and deaths in Gaza when planning an attack.

 Yes, investigative reports and whistleblowers have revealed that the Israel Defense Forces (IDF) utilize automated AI software to predict and factor in civilian casualties when planning airstrikes in Gaza. [1, 2]

While the IDF maintains that these tools are strictly "decision-support systems" verified by human analysts to ensure international law compliance, investigative documentaries and intelligence sources paint a picture of industrial-scale automation where high numbers of civilian deaths were systematically permitted. [1, 2, 3, 4, 5]

The specific mechanics of how the IDF maps out casualties involve a combination of distinct AI systems and calculated thresholds:

1. The Casualty Prediction Tool ("Naza")

According to testimonies from Israeli intelligence officers in the 2026 documentary NAZA (a Hebrew military term for expected "collateral casualties"), the military uses a data-mining system that calculates potential non-combatant deaths for any given strike. [1, 2]

• Data Ingestion: The software utilizes mass surveillance, analyzing drone footage via image recognition tools and tracking smartphone locations via cell towers to tally exactly how many people are currently inside a structure. [1]
• The "Click" System: Intelligence officers stated they could click on any house in the database to instantly see an automated estimate of how many civilians would be wounded or killed if the building were bombed. [1]

2. Pre-Authorized Kill Thresholds

Rather than using AI to prevent casualties, whistleblowers allege the technology was used to quickly verify whether a strike fell within pre-calculated, human-authorized civilian death limits. [1, 2]

• Low-ranking targets: During the early stages of the conflict, the military reportedly tolerated a collateral damage threshold of 15 to 20 civilians for a single low-ranking Hamas or Palestinian Islamic Jihad fighter. [1]
• High-ranking targets: For high-ranking commanders, the accepted threshold was expanded to over 100 civilian casualties. In extreme cases, former soldiers testified that approval was given to kill up to 500 civilians to eliminate one high-value human target. [1, 2]

3. Integration with Target-Generation Engines

The casualty prediction software works alongside two other primary AI engines: [1]

• Lavender & The Gospel: These systems process massive datasets (social media, intercepted communication, location data) to automatically generate "kill lists" of tens of thousands of suspected militants far faster than humanly possible. [1, 2, 3]
• "Where's Daddy?": This system specifically tracked targets and alerted the military when they entered their private family residences. Strikes were often intentionally executed when the target was home with family, meaning the automated casualty estimates were factoring in wives, children, and neighbors. [1, 2, 3]

The Official IDF Response

The IDF has strongly rejected these characterizations, calling the reporting inaccurate and stating it lacks fundamental military understanding. The military asserts that it strictly adheres to international humanitarian law and proportionality. They emphasize that artificial intelligence does not authorize strikes; rather, final decisions and target verifications are performed exclusively by human personnel who use the technology to minimize civilian harm. [1, 2]