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Trump minaccia di espandere gli attacchi in Iran
Punto principale
#BREAKING Il presidente Donald Trump ha avvertito sabato che l'Iran “sarà colpito molto duramente,” minacciando di intensificare il conflitto nella regione ore dopo che il presidente iraniano Masoud Pezeshkian ha detto che l'Iran smetterà di attaccare i paesi vicini che non sono coinvolti nel conflitto.
Fatti chiave
Trump ha detto in un post su Truth Social che sta considerando “distruzione completa e morte certa” di aree e gruppi di persone in Iran che finora non sono stati colpiti dal conflitto, iniziato il 27 febbraio.
In precedenza, sabato, Pezeshkian si è scusato con i paesi vicini attaccati dall'Iran, secondo NPR, ma ha detto che non si arrenderà alle precedenti richieste di Trump: “Quella è un sogno che dovrebbero portare nella loro tomba.”
#BREAKING Il presidente Donald Trump ha avvertito sabato che l'Iran “sarà colpito molto duramente,” minacciando di intensificare il conflitto nella regione ore dopo che il presidente iraniano Masoud Pezeshkian ha detto che l'Iran smetterà di attaccare i paesi vicini che non sono coinvolti nel conflitto.
Fatti chiave
Trump ha detto in un post su Truth Social che sta considerando “distruzione completa e morte certa” di aree e gruppi di persone in Iran che finora non sono stati colpiti dal conflitto, iniziato il 27 febbraio.
In precedenza, sabato, Pezeshkian si è scusato con i paesi vicini attaccati dall'Iran, secondo NPR, ma ha detto che non si arrenderà alle precedenti richieste di Trump: “Quella è un sogno che dovrebbero portare nella loro tomba.”
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Crypto With Country Expands
Cryptocurrency is increasingly being used by sanctioned states to facilitate cross-border trade, finance proxy networks, and move funds outside traditional financial systems, according to recent data examining blockchain activity linked to sanctioned entities.
In 2025 alone, illicit cryptocurrency addresses received around $154 billion, marking a 162% increase from the previous year. Much of this growth was attributed to sanctioned entities, which accounted for $104 billion in value received, a 694% year-over-year surge.
Sanctions Enforcement Expands Across Crypto Networks
Regulators in the United States, Europe, and the United Kingdom increased joint enforcement actions in 2025 targeting cryptocurrency activity linked to sanctions evasion and illicit finance.
Agencies, including the U.S. Office of Foreign Assets Control (OFAC), the European Union, and the U.K.’s Office of Financial Sanctions Implementation, expanded sanctions designations against crypto infrastructure tied to ransomware groups, state-linked networks, and services used to circumvent restrictions.
The European Union also introduced measures targeting Russian cryptocurrency providers and the ruble-backed A7A5 stablecoin. The token processed about $93.3 billion in transactions within 10 months, illustrating how digital assets are being used to settle cross-border transactions outside conventional banking channels.
Legal debates surrounding decentralized technology also impacted enforcement actions. In March 2025, OFAC removed the decentralized mixer Tornado Cash from its Specially Designated Nationals list after a court ruling determined that autonomous smart contracts could not be treated as sanctionable property.
Nation-State Crypto Activity Reaches Billions
Several sanctioned states significantly expanded their cryptocurrency operations in 2025. North Korean-linked actors reportedly stole more than $2 billion in cryptocurrency during the year while continuing cyber operations and global IT worker schemes to generate revenue.
Iran also increased its use of blockchain networks in state-linked financial activities. Addresses associated with networks tied to the Islamic Revolutionary Guard Corps accounted for more than half of the value received by Iranian entities by the fourth quarter of 2025. Those addresses moved over $3 billion during the year to support militia networks, oil-related transactions, and procurement of equipment.
Meanwhile, Russia adopted blockchain-based settlement systems for international trade. Activity surrounding the ruble-backed A7A5 token suggests it was used primarily during weekday business hours, indicating use as a settlement layer for cross-border transactions.
Related: Iran’s Multi-Billion Dollar Cryptocurrency Market Faces New Scrutiny Amid Conflict $ALCX on Bull run $RESOLV $DEGO
In 2025 alone, illicit cryptocurrency addresses received around $154 billion, marking a 162% increase from the previous year. Much of this growth was attributed to sanctioned entities, which accounted for $104 billion in value received, a 694% year-over-year surge.
Sanctions Enforcement Expands Across Crypto Networks
Regulators in the United States, Europe, and the United Kingdom increased joint enforcement actions in 2025 targeting cryptocurrency activity linked to sanctions evasion and illicit finance.
Agencies, including the U.S. Office of Foreign Assets Control (OFAC), the European Union, and the U.K.’s Office of Financial Sanctions Implementation, expanded sanctions designations against crypto infrastructure tied to ransomware groups, state-linked networks, and services used to circumvent restrictions.
The European Union also introduced measures targeting Russian cryptocurrency providers and the ruble-backed A7A5 stablecoin. The token processed about $93.3 billion in transactions within 10 months, illustrating how digital assets are being used to settle cross-border transactions outside conventional banking channels.
Legal debates surrounding decentralized technology also impacted enforcement actions. In March 2025, OFAC removed the decentralized mixer Tornado Cash from its Specially Designated Nationals list after a court ruling determined that autonomous smart contracts could not be treated as sanctionable property.
Nation-State Crypto Activity Reaches Billions
Several sanctioned states significantly expanded their cryptocurrency operations in 2025. North Korean-linked actors reportedly stole more than $2 billion in cryptocurrency during the year while continuing cyber operations and global IT worker schemes to generate revenue.
Iran also increased its use of blockchain networks in state-linked financial activities. Addresses associated with networks tied to the Islamic Revolutionary Guard Corps accounted for more than half of the value received by Iranian entities by the fourth quarter of 2025. Those addresses moved over $3 billion during the year to support militia networks, oil-related transactions, and procurement of equipment.
Meanwhile, Russia adopted blockchain-based settlement systems for international trade. Activity surrounding the ruble-backed A7A5 token suggests it was used primarily during weekday business hours, indicating use as a settlement layer for cross-border transactions.
Related: Iran’s Multi-Billion Dollar Cryptocurrency Market Faces New Scrutiny Amid Conflict $ALCX on Bull run $RESOLV $DEGO
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my mean from bitget is to get $BTC again in profit progress but it is opposite hahaha 🤣😂
Spero di resistere con Bull 💪 spero 💪 ma spero di afferrarlo giù 👇 😂😂😂😂😂😂
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100% dip my one is not sure
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your
La Corea del Sud si muove per escludere USDT, USDC dalle regole sugli investimenti aziendali in criptovalute
La Corea del Sud si muove per escludere USDT, USDC dalle regole sugli investimenti aziendali in criptovalute
La Corea del Sud si sta preparando ad aprire il mercato delle criptovalute agli investitori aziendali, ma le stablecoin come USDT e USDC potrebbero essere escluse dal regolamento, secondo un nuovo rapporto di Herald Economy.
L'autorità di vigilanza finanziaria del paese afferma che includere le stablecoin sarebbe in conflitto con le leggi sui cambi esteri esistenti che non le riconoscono come strumenti di pagamento ufficiali. I regolatori sono anche preoccupati per i rischi di mercato nelle fasi iniziali.
La Corea del Sud si sta preparando ad aprire il mercato delle criptovalute agli investitori aziendali, ma le stablecoin come USDT e USDC potrebbero essere escluse dal regolamento, secondo un nuovo rapporto di Herald Economy.
L'autorità di vigilanza finanziaria del paese afferma che includere le stablecoin sarebbe in conflitto con le leggi sui cambi esteri esistenti che non le riconoscono come strumenti di pagamento ufficiali. I regolatori sono anche preoccupati per i rischi di mercato nelle fasi iniziali.
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Accountability by Design: How Mira Network’s Slashing Keeps the Network Safe
Mira Network uses a strong cryptoeconomic accountability system to ensure that validators behave honestly when verifying AI outputs. In the network, node operators must stake $MIRA tokens before they can participate in verifying AI-generated claims. This stake acts as collateral that can be partially or fully slashed (penalized) if the node behaves maliciously or submits incorrect verifications.
When nodes consistently give answers that deviate from the network’s consensus or show patterns of random guessing, the protocol detects these behaviors through statistical analysis and automatically triggers slashing. This makes manipulation, laziness, or low-effort verification economically irrational because the operator risks losing their stake.
At the same time, honest validators are rewarded with network fees and incentives, creating a balanced system of rewards for accuracy and penalties for dishonesty. This mechanism aligns economic incentives with truthful verification, helping the network maintain reliable AI outputs and resist malicious attacks.
In simple terms, slashing turns accountability into code: if a validator tries to cheat, they pay for it, ensuring the integrity and long-term security of the Mira verification network.
#Mira $MIRA @Mira - Trust Layer of AI
Mira Network uses a strong cryptoeconomic accountability system to ensure that validators behave honestly when verifying AI outputs. In the network, node operators must stake $MIRA tokens before they can participate in verifying AI-generated claims. This stake acts as collateral that can be partially or fully slashed (penalized) if the node behaves maliciously or submits incorrect verifications.
When nodes consistently give answers that deviate from the network’s consensus or show patterns of random guessing, the protocol detects these behaviors through statistical analysis and automatically triggers slashing. This makes manipulation, laziness, or low-effort verification economically irrational because the operator risks losing their stake.
At the same time, honest validators are rewarded with network fees and incentives, creating a balanced system of rewards for accuracy and penalties for dishonesty. This mechanism aligns economic incentives with truthful verification, helping the network maintain reliable AI outputs and resist malicious attacks.
In simple terms, slashing turns accountability into code: if a validator tries to cheat, they pay for it, ensuring the integrity and long-term security of the Mira verification network.
#Mira $MIRA @Mira - Trust Layer of AI
Visualizza traduzione
How Mira Network Could Address AI’s Biggest Problem in 2026
Artificial intelligence has become incredibly powerful. It can write reports, analyze data, generate images, and even assist with complex decisions. But despite this rapid progress, AI still suffers from one fundamental problem: trust.
AI models often produce answers that sound confident but may contain errors or fabricated facts — a phenomenon commonly called AI hallucination. As AI becomes more integrated into finance, healthcare, research, and governance, relying on unverified outputs becomes increasingly risky.
This is where Mira Network is trying to change the game.
The Core Problem: AI Is Powerful but Unreliable
Modern AI models operate on probability. They generate responses based on patterns learned from large datasets rather than guaranteed factual reasoning. Because of this:
AI can produce incorrect information with high confidence
Users often cannot verify how the answer was generated
Critical decisions may rely on unverified outputs
As AI systems become more autonomous, the need for reliable verification infrastructure becomes essential.
Mira Network’s Approach: A Verification Layer for AI
Mira Network introduces a new concept: a decentralized verification layer for artificial intelligence.
Instead of trusting a single AI model, Mira uses multiple independent validators and models to check the accuracy of AI-generated claims. The process works roughly like this:
AI generates a response
The response is broken into smaller factual claims
Independent validator nodes analyze those claims
A decentralized consensus determines whether they are accurate
Verified outputs receive a cryptographic proof of validity
This method creates a trustless verification system, where the accuracy of AI results does not depend on a single provider.
Why Decentralized Verification Matters
Traditional AI platforms are centralized. Users must trust the company operating the model.
Mira changes this by introducing blockchain-based consensus and economic incentives. Validators stake tokens to verify claims, which encourages honest behavior because incorrect validations can result in penalties. �
unblockmedia.com
This structure introduces:
Transparency – verification results are publicly auditable
Accountability – validators have economic incentives to be correct
Scalability – verification can occur across many nodes simultaneously
Improving Accuracy and Reducing AI Hallucinations
One of the most interesting aspects of Mira’s design is its potential impact on AI reliability.
By verifying claims through distributed consensus, the system can significantly reduce hallucinations and improve factual accuracy. Some analyses suggest verification layers like Mira’s could improve AI accuracy from roughly 70% to around 96% in certain applications.
For industries where accuracy is critical—such as finance, medicine, and legal analysis—this kind of improvement could be transformative.
Growing Adoption and Ecosystem Development
The network is already gaining traction. Reports indicate that Mira’s ecosystem has reached millions of users and processes billions of tokens daily, demonstrating strong demand for trusted AI infrastructure.
GlobeNewswire
Mira is also collaborating with infrastructure providers and AI platforms to integrate verification into real-world applications.
The Bigger Vision: Trusted Autonomous AI
The long-term goal of Mira Network goes beyond simply checking AI answers.
The project aims to build the trust infrastructure that autonomous AI systems will rely on. As AI agents begin performing tasks independently—such as managing financial operations, running digital services, or coordinating machines—verification becomes essential.
Without a system that can prove whether AI outputs are correct, fully autonomous AI systems cannot safely operate at scale.
#MIRA $MIRA @mira_network
AI models often produce answers that sound confident but may contain errors or fabricated facts — a phenomenon commonly called AI hallucination. As AI becomes more integrated into finance, healthcare, research, and governance, relying on unverified outputs becomes increasingly risky.
This is where Mira Network is trying to change the game.
The Core Problem: AI Is Powerful but Unreliable
Modern AI models operate on probability. They generate responses based on patterns learned from large datasets rather than guaranteed factual reasoning. Because of this:
AI can produce incorrect information with high confidence
Users often cannot verify how the answer was generated
Critical decisions may rely on unverified outputs
As AI systems become more autonomous, the need for reliable verification infrastructure becomes essential.
Mira Network’s Approach: A Verification Layer for AI
Mira Network introduces a new concept: a decentralized verification layer for artificial intelligence.
Instead of trusting a single AI model, Mira uses multiple independent validators and models to check the accuracy of AI-generated claims. The process works roughly like this:
AI generates a response
The response is broken into smaller factual claims
Independent validator nodes analyze those claims
A decentralized consensus determines whether they are accurate
Verified outputs receive a cryptographic proof of validity
This method creates a trustless verification system, where the accuracy of AI results does not depend on a single provider.
Why Decentralized Verification Matters
Traditional AI platforms are centralized. Users must trust the company operating the model.
Mira changes this by introducing blockchain-based consensus and economic incentives. Validators stake tokens to verify claims, which encourages honest behavior because incorrect validations can result in penalties. �
unblockmedia.com
This structure introduces:
Transparency – verification results are publicly auditable
Accountability – validators have economic incentives to be correct
Scalability – verification can occur across many nodes simultaneously
Improving Accuracy and Reducing AI Hallucinations
One of the most interesting aspects of Mira’s design is its potential impact on AI reliability.
By verifying claims through distributed consensus, the system can significantly reduce hallucinations and improve factual accuracy. Some analyses suggest verification layers like Mira’s could improve AI accuracy from roughly 70% to around 96% in certain applications.
For industries where accuracy is critical—such as finance, medicine, and legal analysis—this kind of improvement could be transformative.
Growing Adoption and Ecosystem Development
The network is already gaining traction. Reports indicate that Mira’s ecosystem has reached millions of users and processes billions of tokens daily, demonstrating strong demand for trusted AI infrastructure.
GlobeNewswire
Mira is also collaborating with infrastructure providers and AI platforms to integrate verification into real-world applications.
The Bigger Vision: Trusted Autonomous AI
The long-term goal of Mira Network goes beyond simply checking AI answers.
The project aims to build the trust infrastructure that autonomous AI systems will rely on. As AI agents begin performing tasks independently—such as managing financial operations, running digital services, or coordinating machines—verification becomes essential.
Without a system that can prove whether AI outputs are correct, fully autonomous AI systems cannot safely operate at scale.
#MIRA $MIRA @mira_network
Ciò che mi piace del Fabric Protocol è che non sembra essere stato progettato per gli spettatori.
Sembra progettato per la partecipazione.
Più tempo trascorro a esaminare il sistema, più quella filosofia di design si distingue. Il token ROBO non è posizionato come un asset passivo destinato solo a rimanere in un portafoglio. Si collega direttamente a commissioni, governance e accesso attraverso la rete, il che fa sentire il token operativo piuttosto che simbolico.
Questo potrebbe spiegare perché il progetto ha attirato attenzione così rapidamente dopo il lancio. Il suo debutto a fine febbraio lo ha spinto verso le principali piazze di trading in poco tempo. Ma le stesse quotazioni non sono il segnale più interessante.
Ciò che sto osservando più da vicino ora è come si comporta la struttura degli incentivi man mano che l'attività inizia a scalare. Man mano che più sviluppatori, agenti e sistemi automatizzati interagiscono con la rete, la vera prova sarà se il modello di coordinamento regge effettivamente sotto pressione.
Molti progetti crypto si concentrano pesantemente sul momentum narrativo. Fabric, d'altra parte, sembra più un esperimento infrastrutturale — un tentativo di trasformare la coordinazione tra macchine, agenti e partecipanti in qualcosa di misurabile e verificabile on-chain.
Questo è il motivo per cui sto prestando attenzione.
Non il rumore attorno al lancio, ma lo stress all'interno del design. Se il sistema può mantenere l'allineamento tra incentivi, partecipazione ed esecuzione mentre cresce, potrebbe rivelare qualcosa di molto più importante rispetto all'hype a breve termine.
#ROBO $ROBO @Fabric Foundation
Sembra progettato per la partecipazione.
Più tempo trascorro a esaminare il sistema, più quella filosofia di design si distingue. Il token ROBO non è posizionato come un asset passivo destinato solo a rimanere in un portafoglio. Si collega direttamente a commissioni, governance e accesso attraverso la rete, il che fa sentire il token operativo piuttosto che simbolico.
Questo potrebbe spiegare perché il progetto ha attirato attenzione così rapidamente dopo il lancio. Il suo debutto a fine febbraio lo ha spinto verso le principali piazze di trading in poco tempo. Ma le stesse quotazioni non sono il segnale più interessante.
Ciò che sto osservando più da vicino ora è come si comporta la struttura degli incentivi man mano che l'attività inizia a scalare. Man mano che più sviluppatori, agenti e sistemi automatizzati interagiscono con la rete, la vera prova sarà se il modello di coordinamento regge effettivamente sotto pressione.
Molti progetti crypto si concentrano pesantemente sul momentum narrativo. Fabric, d'altra parte, sembra più un esperimento infrastrutturale — un tentativo di trasformare la coordinazione tra macchine, agenti e partecipanti in qualcosa di misurabile e verificabile on-chain.
Questo è il motivo per cui sto prestando attenzione.
Non il rumore attorno al lancio, ma lo stress all'interno del design. Se il sistema può mantenere l'allineamento tra incentivi, partecipazione ed esecuzione mentre cresce, potrebbe rivelare qualcosa di molto più importante rispetto all'hype a breve termine.
#ROBO $ROBO @Fabric Foundation
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Goldman Sachs Expects the Fed to Cut Interest Rates Twice This Year: "The Real Issue Is Timing"
#USJobsData Goldman Sachs maintained its expectation regarding Fed interest rate cuts, but stated that the timing of these steps remains uncertain due to global developments and economic data.
Goldman Sachs expects the Fed to cut interest rates twice this year.
Lindsay Rosner, head of multi-asset fixed income investments at Goldman Sachs, said that emerging signals of weakening in the labor market are a significant warning for the Fed. According to Rosner, delaying interest rate cuts could create economic costs. Furthermore, the short-term monetary policy outlook is significantly affected by the uncertainty created by the ongoing conflict in the Middle East.
Rosner stated that developments in Iran and their potential inflationary effects have overshadowed US employment data, further increasing uncertainty about the outlook for monetary policy normalization. Goldman Sachs said it expects the Fed to complete the remaining two normalization cuts in order to ultimately bring interest rates closer to a “neutral” level, but that predicting the precise timing of these steps is difficult in the current climate of uncertainty.
On the other hand, the latest employment data from the US also signaled a slowdown in the economy. Seasonally adjusted non-farm payrolls fell by 92,000 people in February, reaching negative levels for the first time since October 2025. Market expectations were for an increase of 59,000 people.
During the same period, the US unemployment rate also rose. In February, the unemployment rate climbed to 4.4%, reaching its highest level since December 2025 and exceeding market expectations of 4.3%. $BNB
Goldman Sachs expects the Fed to cut interest rates twice this year.
Lindsay Rosner, head of multi-asset fixed income investments at Goldman Sachs, said that emerging signals of weakening in the labor market are a significant warning for the Fed. According to Rosner, delaying interest rate cuts could create economic costs. Furthermore, the short-term monetary policy outlook is significantly affected by the uncertainty created by the ongoing conflict in the Middle East.
Rosner stated that developments in Iran and their potential inflationary effects have overshadowed US employment data, further increasing uncertainty about the outlook for monetary policy normalization. Goldman Sachs said it expects the Fed to complete the remaining two normalization cuts in order to ultimately bring interest rates closer to a “neutral” level, but that predicting the precise timing of these steps is difficult in the current climate of uncertainty.
On the other hand, the latest employment data from the US also signaled a slowdown in the economy. Seasonally adjusted non-farm payrolls fell by 92,000 people in February, reaching negative levels for the first time since October 2025. Market expectations were for an increase of 59,000 people.
During the same period, the US unemployment rate also rose. In February, the unemployment rate climbed to 4.4%, reaching its highest level since December 2025 and exceeding market expectations of 4.3%. $BNB
Analisi del Prezzo di XRP
La sostenibilità del prezzo di XRP sopra il supporto di $1.34 può sostenere gli acquirenti per guidare un aumento del 25% per sfidare a $1.77
Dal luglio 2025, un modello di canale in discesa ha guidato una costante tendenza al ribasso nel prezzo di XRP.
Circa 130 milioni di token XRP sono stati ridistribuiti tra grandi detentori durante questo periodo.
$XRP , la criptovaluta nativa del XRP Ledger, è scesa dell'1.76% durante le ore di mercato statunitensi di giovedì, scambiando a $1.4. Il calo ha coinciso con il rifiuto di Bitcoin da $74,000 mentre l'escalation delle tensioni geopolitiche ha fatto aumentare i prezzi del petrolio in tutto il mercato e ha sollevato sentiment di avversione al rischio. La sostenibilità del prezzo sopra il supporto di $1.34 può sostenere gli acquirenti per guidare un aumento del 25% per sfidare a $1.77
Dal luglio 2025, un modello di canale in discesa ha guidato una costante tendenza al ribasso nel prezzo di XRP.
Circa 130 milioni di token XRP sono stati ridistribuiti tra grandi detentori durante questo periodo.
$XRP , la criptovaluta nativa del XRP Ledger, è scesa dell'1.76% durante le ore di mercato statunitensi di giovedì, scambiando a $1.4. Il calo ha coinciso con il rifiuto di Bitcoin da $74,000 mentre l'escalation delle tensioni geopolitiche ha fatto aumentare i prezzi del petrolio in tutto il mercato e ha sollevato sentiment di avversione al rischio. La sostenibilità del prezzo sopra il supporto di $1.34 può sostenere gli acquirenti per guidare un aumento del 25% per sfidare a $1.77
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🚨THIS IS VERY CONCERNING $UAI
The US economy might be heading towards stagflation, and the consequences could be disastrous. $BANANAS31
Let me tell you how: $SIGN
Since the US-Iran war has started, oil prices are going through the roof.
In just 5 days, US oil prices have moved from $70 to $82, an 18% increase.
If we use this data since the last CPI data was released, US oil prices are up nearly 32%, or $19.6.
As per some estimates, every $10 increase in oil prices causes a 0.2% rise in inflation and a 0.1% drag on GDP.
Right now, the US CPI is at 2.4%, while last quarter's GDP was at 1.4%.
If accounting for the oil price increase, CPI is now at 2.8%, while the GDP has dropped to 1.2%.
This means inflation is about to run hot again, while economic growth will shrink, a scenario that's called "stagflation."
And this is the worst-case scenario for an economy.
During stagflation, if the Fed:
Does tightening ➙ Inflation will cool down, but economic growth will get worse.
Does easing ➙ Economic growth will get better, but inflation will go up even more.
Now, the only hope here is that the US and Iran reach a negotiation here, which will allow the oil tankers to move easily.
This will result in more supply entering the market, and oil prices will fall, causing future inflation to cool down while economic growth rises.
The US economy might be heading towards stagflation, and the consequences could be disastrous. $BANANAS31
Let me tell you how: $SIGN
Since the US-Iran war has started, oil prices are going through the roof.
In just 5 days, US oil prices have moved from $70 to $82, an 18% increase.
If we use this data since the last CPI data was released, US oil prices are up nearly 32%, or $19.6.
As per some estimates, every $10 increase in oil prices causes a 0.2% rise in inflation and a 0.1% drag on GDP.
Right now, the US CPI is at 2.4%, while last quarter's GDP was at 1.4%.
If accounting for the oil price increase, CPI is now at 2.8%, while the GDP has dropped to 1.2%.
This means inflation is about to run hot again, while economic growth will shrink, a scenario that's called "stagflation."
And this is the worst-case scenario for an economy.
During stagflation, if the Fed:
Does tightening ➙ Inflation will cool down, but economic growth will get worse.
Does easing ➙ Economic growth will get better, but inflation will go up even more.
Now, the only hope here is that the US and Iran reach a negotiation here, which will allow the oil tankers to move easily.
This will result in more supply entering the market, and oil prices will fall, causing future inflation to cool down while economic growth rises.
I Prezzi della Benzina Sono Aumentati Questa Settimana A Causa della Guerra in Iran - Questi Stati Sono Sottoposti a Maggiore Pressione
#BREAKING
I prezzi medi della benzina negli Stati Uniti sono schizzati oltre la soglia di $3 questa settimana dopo che gli Stati Uniti e Israele hanno colpito l'Iran, provocando attacchi di rappresaglia attraverso la regione con i prezzi che hanno registrato i loro aumenti più drammatici nel Midwest e nel Sud nell'ultima settimana.
Fatti Chiave
L'Indiana ha registrato il maggior aumento questa settimana, con il costo di un gallone di benzina che è aumentato di 53 centesimi dal 27 febbraio, raggiungendo una media di $3,36 per gallone nello stato, secondo i dati di GasBuddy.
L'Ohio e la Virginia Occidentale hanno seguito da vicino l'Indiana, con i prezzi che sono aumentati di 51 centesimi per entrambi gli stati nell'ultima settimana.
I prezzi medi della benzina negli Stati Uniti sono schizzati oltre la soglia di $3 questa settimana dopo che gli Stati Uniti e Israele hanno colpito l'Iran, provocando attacchi di rappresaglia attraverso la regione con i prezzi che hanno registrato i loro aumenti più drammatici nel Midwest e nel Sud nell'ultima settimana.
Fatti Chiave
L'Indiana ha registrato il maggior aumento questa settimana, con il costo di un gallone di benzina che è aumentato di 53 centesimi dal 27 febbraio, raggiungendo una media di $3,36 per gallone nello stato, secondo i dati di GasBuddy.
L'Ohio e la Virginia Occidentale hanno seguito da vicino l'Indiana, con i prezzi che sono aumentati di 51 centesimi per entrambi gli stati nell'ultima settimana.
Le azioni di BlackRock crollano di oltre il 7% dopo che la società limita i prelievi dal fondo di credito privato
#BREAKING
BlackRock, il maggiore gestore di attivi al mondo, ha visto le sue azioni scivolare di oltre il 7% venerdì dopo che la società ha limitato i prelievi da uno dei suoi fondi di credito privato, portando il suo titolo a un punto basso non visto dal maggio 2025.
Fatti Chiave
Le azioni della società hanno chiuso in calo del 7,2% venerdì a $955,45, continuando una serie di perdite iniziata la settimana scorsa.
Questa è una storia in sviluppo. Controlla per aggiornamenti. $BANANAS31 $FLOW $RESOLV
BlackRock, il maggiore gestore di attivi al mondo, ha visto le sue azioni scivolare di oltre il 7% venerdì dopo che la società ha limitato i prelievi da uno dei suoi fondi di credito privato, portando il suo titolo a un punto basso non visto dal maggio 2025.
Fatti Chiave
Le azioni della società hanno chiuso in calo del 7,2% venerdì a $955,45, continuando una serie di perdite iniziata la settimana scorsa.
Questa è una storia in sviluppo. Controlla per aggiornamenti. $BANANAS31 $FLOW $RESOLV
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Why the Future of Machines May Depend on Fabric Foundation’s Digital Soul Concept
As artificial intelligence and robotics rapidly evolve, machines are moving beyond simple tools and becoming autonomous agents capable of learning, acting, and making decisions in the physical world. But this transformation raises a fundamental question: How can machines operate responsibly and participate in human economies without identity, accountability, or governance?
This is where the concept often described as a “digital soul” becomes important—an idea closely related to the infrastructure being developed by the Fabric Foundation.
The Problem: Machines Without Identity
Today’s robots and AI systems are powerful but limited by a basic structural issue. Most machines operate inside closed corporate systems, controlled by centralized operators. They cannot:
Own a financial account
Sign contracts
Receive payments directly
Build a verifiable reputation
In other words, machines lack economic identity. Human systems—passports, bank accounts, signatures—were designed only for biological participants.
Fabric Foundation
Without identity and accountability, robots remain isolated tools rather than independent contributors to global systems.
The “Digital Soul” Idea
The “digital soul” metaphor refers to a persistent, verifiable identity and memory for machines. Instead of being anonymous hardware, a robot could have:
A cryptographic identity
A historical record of actions
A reputation based on past performance
The ability to hold and transfer digital assets
In the Fabric ecosystem, this identity is created through on-chain cryptographic credentials and blockchain wallets, enabling machines to interact economically and transparently.
This transforms a robot from a device into a network participant.
How Fabric Foundation Is Building This System
Fabric’s architecture introduces several layers that together form the “digital soul” of machines:
1. Identity Layer
Each robot generates a unique cryptographic identity recorded on a blockchain.
This allows the network to verify:
What machine it is
Who controls it
What permissions it has
Its past task performance
2. Economic Layer
Machines receive blockchain wallets so they can:
Receive payments
Pay for maintenance or compute resources
Participate in autonomous contracts.
Fabric Foundation
3. Coordination Layer
Tasks are distributed and verified through decentralized protocols.
Robots can collaborate, complete work, and receive rewards without a centralized operator.
Together these layers create an open operating system for the robot economy.
Why This Could Reshape the Global Economy
The world is entering a period where robots will increasingly handle tasks in:
Manufacturing
Healthcare
Logistics
Environmental cleanup
Infrastructure maintenance.
Fabric Foundation
However, scaling robotic labor globally requires trust and coordination systems similar to those humans use today.
Fabric’s approach enables:
Transparent machine behavior
Verifiable work records
Decentralized governance
Machine-to-machine payments.
In this model, robots can operate as autonomous economic participants, not just company-owned tools.
Aligning Humans and Machines
Another reason the “digital soul” concept matters is alignment.
If machines are making decisions and performing work in society, their actions must be:
Observable
Accountable
Governed by shared rules.
Fabric aims to build infrastructure that allows humans, developers, and machines to participate in a transparent coordination network, ensuring machines remain aligned with human values and oversight.
Fabric Foundation
The Road Ahead
The robot economy is still in its early stages. Real-world deployment will require partnerships, regulation, and operational maturity. Yet the foundations are already forming.
If robots are to become independent workers in a global economy, they will need something similar to what humans already possess:
identity
memory
reputation
financial capability.
The infrastructure being developed by the Fabric ecosystem attempts to give machines exactly that—a digital soul that makes trust possible in a world of autonomous systems.@FabricFND
This is where the concept often described as a “digital soul” becomes important—an idea closely related to the infrastructure being developed by the Fabric Foundation.
The Problem: Machines Without Identity
Today’s robots and AI systems are powerful but limited by a basic structural issue. Most machines operate inside closed corporate systems, controlled by centralized operators. They cannot:
Own a financial account
Sign contracts
Receive payments directly
Build a verifiable reputation
In other words, machines lack economic identity. Human systems—passports, bank accounts, signatures—were designed only for biological participants.
Fabric Foundation
Without identity and accountability, robots remain isolated tools rather than independent contributors to global systems.
The “Digital Soul” Idea
The “digital soul” metaphor refers to a persistent, verifiable identity and memory for machines. Instead of being anonymous hardware, a robot could have:
A cryptographic identity
A historical record of actions
A reputation based on past performance
The ability to hold and transfer digital assets
In the Fabric ecosystem, this identity is created through on-chain cryptographic credentials and blockchain wallets, enabling machines to interact economically and transparently.
This transforms a robot from a device into a network participant.
How Fabric Foundation Is Building This System
Fabric’s architecture introduces several layers that together form the “digital soul” of machines:
1. Identity Layer
Each robot generates a unique cryptographic identity recorded on a blockchain.
This allows the network to verify:
What machine it is
Who controls it
What permissions it has
Its past task performance
2. Economic Layer
Machines receive blockchain wallets so they can:
Receive payments
Pay for maintenance or compute resources
Participate in autonomous contracts.
Fabric Foundation
3. Coordination Layer
Tasks are distributed and verified through decentralized protocols.
Robots can collaborate, complete work, and receive rewards without a centralized operator.
Together these layers create an open operating system for the robot economy.
Why This Could Reshape the Global Economy
The world is entering a period where robots will increasingly handle tasks in:
Manufacturing
Healthcare
Logistics
Environmental cleanup
Infrastructure maintenance.
Fabric Foundation
However, scaling robotic labor globally requires trust and coordination systems similar to those humans use today.
Fabric’s approach enables:
Transparent machine behavior
Verifiable work records
Decentralized governance
Machine-to-machine payments.
In this model, robots can operate as autonomous economic participants, not just company-owned tools.
Aligning Humans and Machines
Another reason the “digital soul” concept matters is alignment.
If machines are making decisions and performing work in society, their actions must be:
Observable
Accountable
Governed by shared rules.
Fabric aims to build infrastructure that allows humans, developers, and machines to participate in a transparent coordination network, ensuring machines remain aligned with human values and oversight.
Fabric Foundation
The Road Ahead
The robot economy is still in its early stages. Real-world deployment will require partnerships, regulation, and operational maturity. Yet the foundations are already forming.
If robots are to become independent workers in a global economy, they will need something similar to what humans already possess:
identity
memory
reputation
financial capability.
The infrastructure being developed by the Fabric ecosystem attempts to give machines exactly that—a digital soul that makes trust possible in a world of autonomous systems.@FabricFND
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#mira $MIRA Mira and the Branch That Executed Before the Proof
In many AI-powered systems, decisions are often executed the moment a model produces an answer. The system assumes the output is correct and moves forward. But this approach creates a critical risk: actions may occur before the result is actually verified.
This is where Mira Network introduces an important shift in design. Instead of treating AI outputs as immediate truth, Mira separates execution from verification. A task may produce a result, but the network still requires independent verification before that result becomes trusted.
The idea behind “the branch that executed before the proof” highlights a common problem in AI workflows. Systems can move ahead on a decision branch even when the underlying reasoning hasn’t been validated. Over time, this can compound errors, especially in automated environments.
Mira’s verification layer works to prevent this scenario. Multiple verifiers review model outputs and confirm whether the reasoning holds. Only after consensus does the system treat the result as reliable.
In a future where AI agents automate more decisions, the challenge will not just be intelligence—it will be provable correctness. Mira’s architecture reflects a simple principle: execution should follow proof, not the other way around.@Mira - Trust Layer of AI
In many AI-powered systems, decisions are often executed the moment a model produces an answer. The system assumes the output is correct and moves forward. But this approach creates a critical risk: actions may occur before the result is actually verified.
This is where Mira Network introduces an important shift in design. Instead of treating AI outputs as immediate truth, Mira separates execution from verification. A task may produce a result, but the network still requires independent verification before that result becomes trusted.
The idea behind “the branch that executed before the proof” highlights a common problem in AI workflows. Systems can move ahead on a decision branch even when the underlying reasoning hasn’t been validated. Over time, this can compound errors, especially in automated environments.
Mira’s verification layer works to prevent this scenario. Multiple verifiers review model outputs and confirm whether the reasoning holds. Only after consensus does the system treat the result as reliable.
In a future where AI agents automate more decisions, the challenge will not just be intelligence—it will be provable correctness. Mira’s architecture reflects a simple principle: execution should follow proof, not the other way around.@Mira - Trust Layer of AI
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