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Destra Edge — $DSYNC From Idea to Reality Yesterday, we introduced Destra Edge. Today, we show you what it means. For too long, AI has lived in data centers. Expensive. Centralized. Controlled by a few. Meanwhile, billions of smartphones sit idle. Powerful GPUs. Doing nothing. That doesn’t make sense....

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Destra Network

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20,249 views • 7 months ago •via X (Twitter)

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2,024,039 views • 11 months ago

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41,855 views • 1 year ago

🔼 Autonomys—Under the Hood | The Architecture of the Foundation Layer for AI3.0 Blockchains are abundant, but true decentralization? That’s rare. Understanding what sets a network apart is essential—whether you’re building, contributing, or seeking AI-ready infrastructure. In this video, we break down the Autonomys Network, powered by the Subspace Protocol, and explore the core components that make it the foundation layer for AI3.0.
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🔼 Autonomys—Under the Hood | The Architecture of the Foundation Layer for AI3.0 Blockchains are abundant, but true decentralization? That’s rare. Understanding what sets a network apart is essential—whether you’re building, contributing, or seeking AI-ready infrastructure. In this video, we break down the Autonomys Network, powered by the Subspace Protocol, and explore the core components that make it the foundation layer for AI3.0.

Autonomys | AI3.0

237,465 views • 1 year ago

Finally. After 18 months of patience, FSD is officially approved and live in the Netherlands. I’ve been driving with it for 2 days now. And the experience is on another level. It feels like the future unfolding in real time. The precision. The intelligence. The confidence of the system. This is not incremental progress. This is a clear step forward in how mobility works. Huge thanks to Elon Musk and the entire AI team at Tesla. From a professional perspective, this shows what is possible when software, data, and real-world deployment come together at scale. The question is no longer if this will take over. The question is how fast it will expand. This is a turning point. Elon Musk
1:57

Finally. After 18 months of patience, FSD is officially approved and live in the Netherlands. I’ve been driving with it for 2 days now. And the experience is on another level. It feels like the future unfolding in real time. The precision. The intelligence. The confidence of the system. This is not incremental progress. This is a clear step forward in how mobility works. Huge thanks to Elon Musk and the entire AI team at Tesla. From a professional perspective, this shows what is possible when software, data, and real-world deployment come together at scale. The question is no longer if this will take over. The question is how fast it will expand. This is a turning point. Elon Musk

NL F$D Inside

25,130,344 views • 4 months ago

🚨 I DON'T KNOW WHAT PEOPLE ARE WAITING FOR! This guy just deployed a full GPU compute farm in a data center Not renting cloud instances, not paying per-token, just racks of consumer GPUs on warehouse shelving doing AI inference 24/7 The setup is wild: open-frame rigs with rows of white fans, PCIe riser cables, server-grade PSUs, and a PDU for power distribution. All mounted on red industrial shelving with raised-floor cooling underneath. It looks like a crypto mining op, because it probably was one Here's what's actually happening: > Ex-mining rigs are being redeployed for AI inference at scale > Each rig runs 6-8 GPUs on PCIe risers connected to a single motherboard > Fans pull cold air from the raised floor through the open frames > A PDU on each rack handles power distribution across all rigs > The whole thing runs in a colocation facility with cheap power rates The economics make sense: cloud GPU pricing runs $2-4/hr per card. Own the hardware, colocate it for $0.08-0.12/kWh, and you're printing compute at a fraction of the cost The crypto-to-AI pipeline is real. Same hardware, same facilities, same power contracts, completely different revenue model Bookmark this!
0:53

🚨 I DON'T KNOW WHAT PEOPLE ARE WAITING FOR! This guy just deployed a full GPU compute farm in a data center Not renting cloud instances, not paying per-token, just racks of consumer GPUs on warehouse shelving doing AI inference 24/7 The setup is wild: open-frame rigs with rows of white fans, PCIe riser cables, server-grade PSUs, and a PDU for power distribution. All mounted on red industrial shelving with raised-floor cooling underneath. It looks like a crypto mining op, because it probably was one Here's what's actually happening: > Ex-mining rigs are being redeployed for AI inference at scale > Each rig runs 6-8 GPUs on PCIe risers connected to a single motherboard > Fans pull cold air from the raised floor through the open frames > A PDU on each rack handles power distribution across all rigs > The whole thing runs in a colocation facility with cheap power rates The economics make sense: cloud GPU pricing runs $2-4/hr per card. Own the hardware, colocate it for $0.08-0.12/kWh, and you're printing compute at a fraction of the cost The crypto-to-AI pipeline is real. Same hardware, same facilities, same power contracts, completely different revenue model Bookmark this!

cristal

16,305 views • 2 months ago

AI shouldn’t be controlled by a single company or person, and the reason why most AI tools are "free" is because you are the product. Your data is more valuable to them, than the tool itself. That's why Action Model is different. We use tokens so: • Every AI action has a real cost • That cost is transparent • Value flows back to contributors, not one corporation The token represents a fractional stake in the AI itself; economic rights, governance rights, and participation in its growth. And that’s how you run AI without centralized control.
0:42

AI shouldn’t be controlled by a single company or person, and the reason why most AI tools are "free" is because you are the product. Your data is more valuable to them, than the tool itself. That's why Action Model is different. We use tokens so: • Every AI action has a real cost • That cost is transparent • Value flows back to contributors, not one corporation The token represents a fractional stake in the AI itself; economic rights, governance rights, and participation in its growth. And that’s how you run AI without centralized control.

Action Model

47,461 views • 6 months ago

The biggest factor that will lead to the death of many companies is AI costs that sneak in Every startup in 2026 wants to build the hottest automations available in the markets They’re all spending tokens like it means nothing That is where the problem is I’ll try to explain this through an example:- Let’s say you are a relatively smart company and use Okta You map Okta groups to model access, block certain providers, and set routing rules so a support ticket never goes to the expensive frontier model. This saves cost. But guess what happens when the laptop is outside the corporate network or the employee simply opens Claude / Codex / Cursor directly? You’re losing money again I’ve been recommending this tool to my entrepreneur friends. it solves the complete layer by rewriting the local harness, routing every request through their gateway by default, This has cut inference spend dramatically while keeping performance comparable on most workloads. This is less about one more governance checkbox and more about where the real leverage is shifting. The model wars will keep producing better weights. The inference and control plane is where the durable enterprise value is being built Worth watching how quickly this becomes table stakes!
0:23

The biggest factor that will lead to the death of many companies is AI costs that sneak in Every startup in 2026 wants to build the hottest automations available in the markets They’re all spending tokens like it means nothing That is where the problem is I’ll try to explain this through an example:- Let’s say you are a relatively smart company and use Okta You map Okta groups to model access, block certain providers, and set routing rules so a support ticket never goes to the expensive frontier model. This saves cost. But guess what happens when the laptop is outside the corporate network or the employee simply opens Claude / Codex / Cursor directly? You’re losing money again I’ve been recommending this tool to my entrepreneur friends. it solves the complete layer by rewriting the local harness, routing every request through their gateway by default, This has cut inference spend dramatically while keeping performance comparable on most workloads. This is less about one more governance checkbox and more about where the real leverage is shifting. The model wars will keep producing better weights. The inference and control plane is where the durable enterprise value is being built Worth watching how quickly this becomes table stakes!

Jaymin Shah

44,159 views • 6 days ago

$OGPU token is no longer waiting for utility. It is live. Most people still haven’t understood what this means. $OGPU is now connected to some of the most powerful AI models in the world. Claude. GPT. DeepSeek. Kling 3.0. Gemini And more. Top up Relay with $OGPU and unlock up to +20% extra AI credits. That means more Claude usage for the same spend than going direct. Not vaporware. Not a future promise. Live token utility. Once people actually use it, the power of $OGPU token becomes very hard to ignore. $OGPU = AI credits = model usage = real demand Powered by OpenGPU.
0:34

$OGPU token is no longer waiting for utility. It is live. Most people still haven’t understood what this means. $OGPU is now connected to some of the most powerful AI models in the world. Claude. GPT. DeepSeek. Kling 3.0. Gemini And more. Top up Relay with $OGPU and unlock up to +20% extra AI credits. That means more Claude usage for the same spend than going direct. Not vaporware. Not a future promise. Live token utility. Once people actually use it, the power of $OGPU token becomes very hard to ignore. $OGPU = AI credits = model usage = real demand Powered by OpenGPU.

OpenGPU Network

1,705,347 views • 3 months ago