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0g
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AI x Web3 Just Went From Theory To Reality 🌏
$FET showed how fast autonomous agent systems are scaling across the market. $0G is where that shift is now being built, tested, and deployed in real time by builders.
0G just wrapped a full ecosystem showcase in Hong Kong.
Builders, partners, and industry leaders came together around one idea:
AI × Web3 is no longer theoretical.The signal wasn’t just discussion.
It was execution.
→ 7 live projects already building on 0G
→ Ecosystem teams sharing real deployment plans
→ Industry partners aligning around agent infrastructure
From core insights to live demos, the focus stayed the same.
AI agents need infrastructure to evolve.
That includes:
→ Verifiable compute for decision-making
→ Persistent memory across sessions
→ Coordination between agents
→ Rails for real economic activity
This is what the ecosystem is starting to build.
Not concepts. Working systems.
The Hong Kong event made one thing clear.
The agent era isn’t coming.
It’s already being shipped.
#AI #0G
$FET showed how fast autonomous agent systems are scaling across the market. $0G is where that shift is now being built, tested, and deployed in real time by builders.
0G just wrapped a full ecosystem showcase in Hong Kong.
Builders, partners, and industry leaders came together around one idea:
AI × Web3 is no longer theoretical.The signal wasn’t just discussion.
It was execution.
→ 7 live projects already building on 0G
→ Ecosystem teams sharing real deployment plans
→ Industry partners aligning around agent infrastructure
From core insights to live demos, the focus stayed the same.
AI agents need infrastructure to evolve.
That includes:
→ Verifiable compute for decision-making
→ Persistent memory across sessions
→ Coordination between agents
→ Rails for real economic activity
This is what the ecosystem is starting to build.
Not concepts. Working systems.
The Hong Kong event made one thing clear.
The agent era isn’t coming.
It’s already being shipped.
#AI #0G
hady XXOO:
国人币 就是会画饼，一边画 一边割
Breakout hunters are getting active and liquidity is moving fast 💥
Momentum is building—this could turn into a much bigger continuation run!
$0G
🟢 LIQUIDITY ZONE HIT 🟢
Short liquidation spotted 🧨
$1.1058K cleared at $0.50217
Upside liquidity swept — react NOW or watch the market shift 👀
🎯 TP Targets:
TP1: ~$0.515
TP2: ~$0.532
TP3: ~$0.548
#0g
Momentum is building—this could turn into a much bigger continuation run!
$0G
🟢 LIQUIDITY ZONE HIT 🟢
Short liquidation spotted 🧨
$1.1058K cleared at $0.50217
Upside liquidity swept — react NOW or watch the market shift 👀
🎯 TP Targets:
TP1: ~$0.515
TP2: ~$0.532
TP3: ~$0.548
#0g
AI Inference Just Became Verifiable 🖥
$TAO showed how fast decentralized intelligence is scaling. $RENDER proved the market values AI compute infrastructure once demand becomes real.
0G is now solving the trust layer behind that compute.
0G Private Computer is live.
Developers get chat, vision, speech, and image generation through a single endpoint, with every request verified at the hardware level.
The shift is simple.
Most AI APIs run on trust. 0G runs on proof.
Every request executes inside TEE enclaves:
→ Prompts stay encrypted
→ Outputs are signed inside the enclave
→ Providers cannot see or alter execution
The integration is just as simple.
Swap one line in your OpenAI SDK and route traffic through 0G.
Same workflow.
Different trust model.
The model layer is already live:
→ DeepSeek for reasoning
→ Qwen3.6 for large-context tasks
→ GLM-5 for agent workflows
→ Whisper for speech
→ z-image for generation
All running inside verified compute.
This is where AI infrastructure changes.
From black-box APIs To verifiable execution.
For agents handling capital, keys, and decisions, that difference is everything.
#TAO #render #0G
$TAO showed how fast decentralized intelligence is scaling. $RENDER proved the market values AI compute infrastructure once demand becomes real.
0G is now solving the trust layer behind that compute.
0G Private Computer is live.
Developers get chat, vision, speech, and image generation through a single endpoint, with every request verified at the hardware level.
The shift is simple.
Most AI APIs run on trust. 0G runs on proof.
Every request executes inside TEE enclaves:
→ Prompts stay encrypted
→ Outputs are signed inside the enclave
→ Providers cannot see or alter execution
The integration is just as simple.
Swap one line in your OpenAI SDK and route traffic through 0G.
Same workflow.
Different trust model.
The model layer is already live:
→ DeepSeek for reasoning
→ Qwen3.6 for large-context tasks
→ GLM-5 for agent workflows
→ Whisper for speech
→ z-image for generation
All running inside verified compute.
This is where AI infrastructure changes.
From black-box APIs To verifiable execution.
For agents handling capital, keys, and decisions, that difference is everything.
#TAO #render #0G
0G App Turns AI Into Something You Actually Own 🧠
$NEAR made building apps simple. $0G takes that same experience and changes the trust layer underneath it.
0G App brings chat, build, and deployment into one place.
GLM-5 runs inside TEE from day one.
Apps generate from a prompt.
Everything syncs to decentralized storage.
The difference shows up in how the system is designed.
Every interaction runs with:
→ Sealed inference inside TEE enclaves
→ No exposure of prompts or outputs
→ Storage backed by a root hash you control
The product flow is simple.
Describe what you want.
Generate a full app with live preview.
Deploy instantly.
Recover everything later using a cryptographic hash.
No accounts.
No centralized storage.
No dependency on a provider holding your data.
GLM-5 runs at 744B parameters with top-tier benchmark performance, while inference costs remain a fraction of centralized alternatives.
This is what AI looks like when the user owns the output.
The tools feel familiar.
The ownership model is completely different.
#Aİ #0G #Near
$NEAR made building apps simple. $0G takes that same experience and changes the trust layer underneath it.
0G App brings chat, build, and deployment into one place.
GLM-5 runs inside TEE from day one.
Apps generate from a prompt.
Everything syncs to decentralized storage.
The difference shows up in how the system is designed.
Every interaction runs with:
→ Sealed inference inside TEE enclaves
→ No exposure of prompts or outputs
→ Storage backed by a root hash you control
The product flow is simple.
Describe what you want.
Generate a full app with live preview.
Deploy instantly.
Recover everything later using a cryptographic hash.
No accounts.
No centralized storage.
No dependency on a provider holding your data.
GLM-5 runs at 744B parameters with top-tier benchmark performance, while inference costs remain a fraction of centralized alternatives.
This is what AI looks like when the user owns the output.
The tools feel familiar.
The ownership model is completely different.
#Aİ #0G #Near
Ms Puiyi:
finally someone gets it. ai locked away is kinda pointless. You have a very interesting perspective, can we follow ea...
357x More Efficient AI Agents Training Is Here 🛠
$FIL showed that when decentralised storage reaches training-grade scale, it changes which infrastructure can actually support frontier AI development.
$GRT proved that data indexing and availability become load-bearing infrastructure the moment AI models start consuming knowledge at a production scale.
0G Labs just completed DiLoCoX-107B, the world's largest decentralised AI model at 107 billion parameters.
→ 357x communication efficiency over standard methods
→ 95% cost reduction versus centralised training
→ Runs on ordinary 1 Gbps internet connections
→ All checkpoints publicly auditable via TEE-backed verification throughout
Training frontier models has historically required centralised data centres and closed infrastructure. DiLoCoX-107B proves it can run on distributed nodes with cryptographic proof at every training step, and at 95% lower cost. Decentralized AI training at frontier scale now has a publicly verifiable proof of concept on the record.
0G also published a full verification framework alongside the model, combining TEEs with economic incentive alignment to generate cryptographic attestations for each step of the training process. Verifiable training and verifiable inference now sit in the same stack, covering the full AI lifecycle.
The 100 billion parameter barrier in decentralised AI training has been crossed with a publicly verifiable framework behind it, opening frontier-scale models to AI agents and builders without centralised compute.
#0G #fil #AI
$FIL showed that when decentralised storage reaches training-grade scale, it changes which infrastructure can actually support frontier AI development.
$GRT proved that data indexing and availability become load-bearing infrastructure the moment AI models start consuming knowledge at a production scale.
0G Labs just completed DiLoCoX-107B, the world's largest decentralised AI model at 107 billion parameters.
→ 357x communication efficiency over standard methods
→ 95% cost reduction versus centralised training
→ Runs on ordinary 1 Gbps internet connections
→ All checkpoints publicly auditable via TEE-backed verification throughout
Training frontier models has historically required centralised data centres and closed infrastructure. DiLoCoX-107B proves it can run on distributed nodes with cryptographic proof at every training step, and at 95% lower cost. Decentralized AI training at frontier scale now has a publicly verifiable proof of concept on the record.
0G also published a full verification framework alongside the model, combining TEEs with economic incentive alignment to generate cryptographic attestations for each step of the training process. Verifiable training and verifiable inference now sit in the same stack, covering the full AI lifecycle.
The 100 billion parameter barrier in decentralised AI training has been crossed with a publicly verifiable framework behind it, opening frontier-scale models to AI agents and builders without centralised compute.
#0G #fil #AI
Aon Jaffir :
Please help🙏🏻....give some funds😕
binance uid
1019573700
🚨 $0G is no longer just another AI narrative…
It’s becoming the infrastructure layer where AI agents actually LIVE, EXECUTE & MONETIZE. 🤖⚡
300+ ecosystem partners.
10,000+ target agents by Q4 2026.
$100M annualized revenue ambition.
$1B TVL target.
This is scaling FAST. 👀🔥
While most projects are still talking about AI…
0G is building the full modular stack powering the next autonomous economy:
⚡ Chain
⚡ Compute
⚡ Storage
⚡ Data Availability
⚡ Trusted AI execution
Privacy-safe execution changes everything.
Without trust layers, autonomous agents can’t handle real-world high-value workflows securely.
That’s why the market could be massively underpricing this infrastructure play.
Even beside $TAO & $FET …
0G feels positioned for a much bigger infrastructure narrative. 📈
🎯 EP: $0.42 – $0.46
💰 TP: $0.78 / $1.10 / $1.60
🛑 SL: $0.34
AI-agent economies are coming.
0G wants to be the foundation layer underneath all of it.
B U L L I S H 🥂🔥
#0G #AI #AIAgents #Crypto
It’s becoming the infrastructure layer where AI agents actually LIVE, EXECUTE & MONETIZE. 🤖⚡
300+ ecosystem partners.
10,000+ target agents by Q4 2026.
$100M annualized revenue ambition.
$1B TVL target.
This is scaling FAST. 👀🔥
While most projects are still talking about AI…
0G is building the full modular stack powering the next autonomous economy:
⚡ Chain
⚡ Compute
⚡ Storage
⚡ Data Availability
⚡ Trusted AI execution
Privacy-safe execution changes everything.
Without trust layers, autonomous agents can’t handle real-world high-value workflows securely.
That’s why the market could be massively underpricing this infrastructure play.
Even beside $TAO & $FET …
0G feels positioned for a much bigger infrastructure narrative. 📈
🎯 EP: $0.42 – $0.46
💰 TP: $0.78 / $1.10 / $1.60
🛑 SL: $0.34
AI-agent economies are coming.
0G wants to be the foundation layer underneath all of it.
B U L L I S H 🥂🔥
#0G #AI #AIAgents #Crypto
AI Infrastructure Is Becoming An Asset Class 🧠
$TAO showed decentralized AI can attract real demand. $0G is pushing the next question forward.
As AI scales, who actually captures the value?
Decentralized AI sits around a ~$16–17B market today. It’s still early, but growing fast enough to attract institutional capital.
The shift is already visible. AI infrastructure is no longer just something developers use. It’s starting to look like something that can generate returns.
This change comes from how AI itself is evolving. Most systems today assist humans. The next generation acts independently.
When agents start executing:
→ Capital can be deployed autonomously
→ Strategies can adjust in real time
→ Systems begin participating directly in markets
That introduces a new kind of economic activity, where value comes from continuous execution rather than static ownership.
$0G is building for this layer with verifiable compute, persistent memory, and native rails for agent-driven transactions.
The market is still early, but the direction is clear. As activity scales, infrastructure stops behaving like a cost layer and starts functioning as a source of returns.
#Aİ #0G
$TAO showed decentralized AI can attract real demand. $0G is pushing the next question forward.
As AI scales, who actually captures the value?
Decentralized AI sits around a ~$16–17B market today. It’s still early, but growing fast enough to attract institutional capital.
The shift is already visible. AI infrastructure is no longer just something developers use. It’s starting to look like something that can generate returns.
This change comes from how AI itself is evolving. Most systems today assist humans. The next generation acts independently.
When agents start executing:
→ Capital can be deployed autonomously
→ Strategies can adjust in real time
→ Systems begin participating directly in markets
That introduces a new kind of economic activity, where value comes from continuous execution rather than static ownership.
$0G is building for this layer with verifiable compute, persistent memory, and native rails for agent-driven transactions.
The market is still early, but the direction is clear. As activity scales, infrastructure stops behaving like a cost layer and starts functioning as a source of returns.
#Aİ #0G
Avatar222:
next move 0.688
$0G
is building the infrastructure layer AI agents were missing.
300+ ecosystem partners.
10,000+ target agents by Q4 2026.
$100M annualized net revenue ambition.
$1B TVL confidence target.
This is getting massive fast.
The new 0G app changes everything:
Faster onboarding
Sub1-minute deployment positioning
Privacy-safe AI execution
Creator monetization rails
Trusted autonomous workflows
Full modular stack across Chain, Compute, Storage, and DA
Most projects talk about AI.
0G is building where AI agents actually live, execute, deploy, and monetize securely.
That’s the difference.
Even next to $TAO and $FET the positioning here feels bigger on infrastructure scale.
0G combines:
AI-native modular infrastructure
Trusted execution
Sovereign AI workflows
Agent identity standards
Deployment speed
Real builder onboarding
The market still hasn’t fully priced how important trusted AI execution becomes once autonomous systems scale.
Without privacy-safe execution, agents can’t handle higher-value workflows securely.
0G is directly solving that.
Feels like the ecosystem is moving from experimentation real AI-agent economies.
And 0G wants to be the foundation powering it.
0G looks like one of the strongest AI infrastructure narratives developing right now.
B U L L I S H
#0G #AI #AIAgents #USPPISurge #NakamotoQ1Revenue500PercentGrowth
is building the infrastructure layer AI agents were missing.
300+ ecosystem partners.
10,000+ target agents by Q4 2026.
$100M annualized net revenue ambition.
$1B TVL confidence target.
This is getting massive fast.
The new 0G app changes everything:
Faster onboarding
Sub1-minute deployment positioning
Privacy-safe AI execution
Creator monetization rails
Trusted autonomous workflows
Full modular stack across Chain, Compute, Storage, and DA
Most projects talk about AI.
0G is building where AI agents actually live, execute, deploy, and monetize securely.
That’s the difference.
Even next to $TAO and $FET the positioning here feels bigger on infrastructure scale.
0G combines:
AI-native modular infrastructure
Trusted execution
Sovereign AI workflows
Agent identity standards
Deployment speed
Real builder onboarding
The market still hasn’t fully priced how important trusted AI execution becomes once autonomous systems scale.
Without privacy-safe execution, agents can’t handle higher-value workflows securely.
0G is directly solving that.
Feels like the ecosystem is moving from experimentation real AI-agent economies.
And 0G wants to be the foundation powering it.
0G looks like one of the strongest AI infrastructure narratives developing right now.
B U L L I S H
#0G #AI #AIAgents #USPPISurge #NakamotoQ1Revenue500PercentGrowth
Segue minhas principais moedas com investimentos constante para esse ciclo de alteseason:
$BTC , #bitcoin , 🚀
$ETH ,#ETH 🚀
$SOL ,#solana 🚀
$0G, #0G 🚀
$DOGE, #DOGE 🚀
$LINK,#LINK🚀
$AAVE, #AAVE🚀
$ICP, #ICP 🚀
$SUI, #SUI🚀
$ATOM, #ATOM🚀
$XRP, #XRP🚀
$AVAX, #AVAX🚀
$SEI,#SEI🚀
$ADA, #ADA🚀
$XAUT, #XAUT🚀
$SAGA, # SAGA🚀
Me sigam para mais atualizações 👊💪🚀🚀🚀
$BTC , #bitcoin , 🚀
$ETH ,#ETH 🚀
$SOL ,#solana 🚀
$0G, #0G 🚀
$DOGE, #DOGE 🚀
$LINK,#LINK🚀
$AAVE, #AAVE🚀
$ICP, #ICP 🚀
$SUI, #SUI🚀
$ATOM, #ATOM🚀
$XRP, #XRP🚀
$AVAX, #AVAX🚀
$SEI,#SEI🚀
$ADA, #ADA🚀
$XAUT, #XAUT🚀
$SAGA, # SAGA🚀
Me sigam para mais atualizações 👊💪🚀🚀🚀
#0G
0G launches first proprietary AI model trained on its own network: 0G has deployed its first proprietary AI model, 0GM 1.0 35B-A3B, fully trained on its own decentralized network, marking a key milestone in the deAIOS ecosystem. The announcement coincided with a 2.7% price drop, indicating profit-taking or market-wide pressure. #0G
$0G
0G launches first proprietary AI model trained on its own network: 0G has deployed its first proprietary AI model, 0GM 1.0 35B-A3B, fully trained on its own decentralized network, marking a key milestone in the deAIOS ecosystem. The announcement coincided with a 2.7% price drop, indicating profit-taking or market-wide pressure. #0G
$0G
🧠 الذكاء الاصطناعي والبنية التحتية بدأت تتحول إلى فئة أصول استثمارية جديدة.
أثبت $TAO أن الذكاء الاصطناعي اللامركزي قادر على جذب طلب حقيقي، بين$G يفتح الباب لسؤال أعمق: من يلتقط القيمة الفعلية مع توسّع الذكاء الاصطناعي؟
اليوم، سوق AI اللامركزي يُقدّر بحوالي 16–17 مليار دولار، وما زال في مراحله المبكرة، لكنه ينمو بسرعة كافية لجذب رؤوس أموال مؤسسية.
🔄 التحول بدأ بالفعل:
البنية التحتية للذكاء الاصطناعي لم تعد مجرد أدوات يستخدمها المطورون، بل بدأت تتحول إلى منظومة يمكنها توليد عوائد اقتصادية.
هذا التحول يأتي من تطور طبيعة الذكاء الاصطناعي نفسه:
معظم الأنظمة اليوم تساعد البشر، لكن الجيل القادم سيكون أكثر استقلالية وتنفيذًا.
🤖 عندما تبدأ الوكلاء (Agents) في التنفيذ:
→ سيتم نشر رأس المال بشكل تلقائي
→ ستتغير الاستراتيجيات لحظيًا
→ وستدخل الأنظمة مباشرة في الأسواق
وهذا يخلق نوعًا جديدًا من النشاط الاقتصادي، حيث تأتي القيمة من التنفيذ المستمر بدل الملكية الثابتة.
$0G يبني هذا المستوى من البنية التحتية عبر:
🔹 حوسبة قابلة للتحقق
🔹 ذاكرة دائمة
🔹 مسارات أصلية للمعاملات المدفوعة بالوكلاء
السوق ما زال في بدايته، لكن الاتجاه واضح:
مع توسّع النشاط، تتحول البنية التحتية من “تكلفة تشغيل” إلى “مصدر عوائد”.
#AI #0G
أثبت $TAO أن الذكاء الاصطناعي اللامركزي قادر على جذب طلب حقيقي، بين$G يفتح الباب لسؤال أعمق: من يلتقط القيمة الفعلية مع توسّع الذكاء الاصطناعي؟
اليوم، سوق AI اللامركزي يُقدّر بحوالي 16–17 مليار دولار، وما زال في مراحله المبكرة، لكنه ينمو بسرعة كافية لجذب رؤوس أموال مؤسسية.
🔄 التحول بدأ بالفعل:
البنية التحتية للذكاء الاصطناعي لم تعد مجرد أدوات يستخدمها المطورون، بل بدأت تتحول إلى منظومة يمكنها توليد عوائد اقتصادية.
هذا التحول يأتي من تطور طبيعة الذكاء الاصطناعي نفسه:
معظم الأنظمة اليوم تساعد البشر، لكن الجيل القادم سيكون أكثر استقلالية وتنفيذًا.
🤖 عندما تبدأ الوكلاء (Agents) في التنفيذ:
→ سيتم نشر رأس المال بشكل تلقائي
→ ستتغير الاستراتيجيات لحظيًا
→ وستدخل الأنظمة مباشرة في الأسواق
وهذا يخلق نوعًا جديدًا من النشاط الاقتصادي، حيث تأتي القيمة من التنفيذ المستمر بدل الملكية الثابتة.
$0G يبني هذا المستوى من البنية التحتية عبر:
🔹 حوسبة قابلة للتحقق
🔹 ذاكرة دائمة
🔹 مسارات أصلية للمعاملات المدفوعة بالوكلاء
السوق ما زال في بدايته، لكن الاتجاه واضح:
مع توسّع النشاط، تتحول البنية التحتية من “تكلفة تشغيل” إلى “مصدر عوائد”.
#AI #0G
DISTRIBUTION CONFIRMED on $0G
Sellers are aggressively distributing at these peak resistance levels. The current MOMENTUM suggests a primary trend exhaustion. Expecting a sweep of the lower support clusters and demand zones.
🎯 $0G PRO SHORT SETUP
🔹 Entry Price: 0.5480
🔹 🎯 Target 1: 0.5346
🔹 🎯 Target 2: 0.5231
🔹 🎯 Target 3: 0.5096
🔹 🛑 Invalidation (SL): 0.5691
#0G
Sellers are aggressively distributing at these peak resistance levels. The current MOMENTUM suggests a primary trend exhaustion. Expecting a sweep of the lower support clusters and demand zones.
🎯 $0G PRO SHORT SETUP
🔹 Entry Price: 0.5480
🔹 🎯 Target 1: 0.5346
🔹 🎯 Target 2: 0.5231
🔹 🎯 Target 3: 0.5096
🔹 🛑 Invalidation (SL): 0.5691
#0G
🚨 DISTRIBUTION CONFIRMED on $0G
Sellers are aggressively distributing at these peak resistance levels. The current MOMENTUM suggests a primary trend exhaustion. Expecting a sweep of the lower support clusters and demand zones.
🎯 $0G PRO SHORT SETUP
🔹 Entry Price: 0.5480
🔹 🎯 Target 1: 0.5346
🔹 🎯 Target 2: 0.5231
🔹 🎯 Target 3: 0.5096
🔹 🛑 Invalidation (SL): 0.5691
#0G
Sellers are aggressively distributing at these peak resistance levels. The current MOMENTUM suggests a primary trend exhaustion. Expecting a sweep of the lower support clusters and demand zones.
🎯 $0G PRO SHORT SETUP
🔹 Entry Price: 0.5480
🔹 🎯 Target 1: 0.5346
🔹 🎯 Target 2: 0.5231
🔹 🎯 Target 3: 0.5096
🔹 🛑 Invalidation (SL): 0.5691
#0G
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