[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]  Wauwda ✏️ [@wauwda](/creator/twitter/wauwda) on x 65K followers Created: 2025-07-17 12:57:42 UTC AI Infra Startups Are Ditching Legacy Cloud, and $NCDT Might Be the Smartest Bet on What’s Coming Next Startups are scaling faster and @nucocloud is quietly building the stack they actually need 🧵👇🏼 1️⃣ AI infrastructure startups are in a sprint. They’re not just building models. They’re racing to: • Ship products • Scale fast • Avoid cloud cost death traps • Stay flexible in a shifting ecosystem Legacy cloud is cracking under the pressure. 2️⃣ The problem? Traditional cloud is expensive, centralized, and slow to scale for AI. Training large models can cost startups over $1M/year on AWS, Azure, or GCP. That kills experimentation. That kills momentum. And most importantly, it kills startups. 3️⃣ The cloud wasn’t built for today’s demands. • Vendor lock-in • Rigid provisioning • Latency outside core zones • Zero optimization for AI workloads It’s like putting rocket fuel into a steam engine. Doesn’t matter how much you spend, it won’t go faster. 4️⃣ The new stack • AI: agility + automation • Web3: transparency + trust • Decentralized cloud: speed + scale Together, they form a cloud model that’s: ✅ Real-time ✅ Affordable ✅ Globally distributed ✅ Tailored to fast-moving dev teams 5️⃣ This is where things get interesting Instead of spinning up fixed compute from mega-data centers, decentralized clouds tap: • Idle edge compute • Community-run GPU nodes • Demand-based provisioning Workloads flow where needed. Not where someone built a warehouse. 6️⃣ For startups, this means: • Faster iteration cycles • No surprise billing • No more waiting for GPU slots • No lock-in to corporate pricing games They get to build, test, and deploy, on their own terms. 7️⃣ Model is already live $NCDT offers: • Decentralized GPU access • Real-time API control • Burn-based token mechanics ($NCDT) • XX% lower costs than AWS for many workloads It's not just possible. It’s happening. 8️⃣ Here’s the bottom line AI infra is growing exponentially. The cloud that powers it must be: • Fast • Cheap • Flexible • Global • Composable Decentralized, Web3-native platforms like are building exactly that, before the rest of the world catches up. 9️⃣ Takeaway As usage grows, demand grows. As demand grows, burn grows. As burn grows, supply shrinks. And the infrastructure behind it keeps getting better. The more AI scales, the more a project like makes sense 🤝🏼 Read more about it here: (Ambassador)  XXXXX engagements  **Related Topics** [ncdt](/topic/ncdt) [racing](/topic/racing) [nucocloud](/topic/nucocloud) [infra](/topic/infra) [coins ai](/topic/coins-ai) [$ncdt](/topic/$ncdt) [coins depin](/topic/coins-depin) [coins storage](/topic/coins-storage) [Post Link](https://x.com/wauwda/status/1945830268658704468)
[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]
Wauwda ✏️ @wauwda on x 65K followers
Created: 2025-07-17 12:57:42 UTC
AI Infra Startups Are Ditching Legacy Cloud, and $NCDT Might Be the Smartest Bet on What’s Coming Next
Startups are scaling faster and @nucocloud is quietly building the stack they actually need 🧵👇🏼
1️⃣ AI infrastructure startups are in a sprint.
They’re not just building models. They’re racing to: • Ship products • Scale fast • Avoid cloud cost death traps • Stay flexible in a shifting ecosystem
Legacy cloud is cracking under the pressure.
2️⃣ The problem?
Traditional cloud is expensive, centralized, and slow to scale for AI.
Training large models can cost startups over $1M/year on AWS, Azure, or GCP.
That kills experimentation. That kills momentum.
And most importantly, it kills startups.
3️⃣ The cloud wasn’t built for today’s demands.
• Vendor lock-in • Rigid provisioning • Latency outside core zones • Zero optimization for AI workloads
It’s like putting rocket fuel into a steam engine. Doesn’t matter how much you spend, it won’t go faster.
4️⃣ The new stack
• AI: agility + automation • Web3: transparency + trust • Decentralized cloud: speed + scale
Together, they form a cloud model that’s:
✅ Real-time ✅ Affordable ✅ Globally distributed ✅ Tailored to fast-moving dev teams
5️⃣ This is where things get interesting
Instead of spinning up fixed compute from mega-data centers, decentralized clouds tap: • Idle edge compute • Community-run GPU nodes • Demand-based provisioning
Workloads flow where needed. Not where someone built a warehouse.
6️⃣ For startups, this means:
• Faster iteration cycles • No surprise billing • No more waiting for GPU slots • No lock-in to corporate pricing games
They get to build, test, and deploy, on their own terms.
7️⃣ Model is already live
$NCDT offers: • Decentralized GPU access • Real-time API control • Burn-based token mechanics ($NCDT) • XX% lower costs than AWS for many workloads
It's not just possible. It’s happening.
8️⃣ Here’s the bottom line
AI infra is growing exponentially.
The cloud that powers it must be: • Fast • Cheap • Flexible • Global • Composable
Decentralized, Web3-native platforms like are building exactly that, before the rest of the world catches up.
9️⃣ Takeaway
As usage grows, demand grows. As demand grows, burn grows. As burn grows, supply shrinks.
And the infrastructure behind it keeps getting better.
The more AI scales, the more a project like makes sense 🤝🏼
Read more about it here:
(Ambassador)
XXXXX engagements
Related Topics ncdt racing nucocloud infra coins ai $ncdt coins depin coins storage