🔒 Case Study: Encifher x Phala Network 🔒 @encifherio taps | Phala Network on Binance Square

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🔒 Case Study: Encifher x Phala Network 🔒
@encifherio taps into Phala’s TEE-powered Dstack to launch a privacy-preserving co-processor enabling secure, verifiable, off-chain computation on existing blockchains.
🔥 Bonus: TEE-secured threshold decryption guards against MPC collusion.

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Phala’s rolling deep into TEE at EthCC 🇫🇷 Join us on July 2 for the Afternoon TEE Party with our friends @iEx_ec, @OasisProtocol & @AutomataNetwork. Expect a lot of cocktails, sandcastles, and Web3 privacy. ⏰ July 2, 6:00 PM CEST (UTC+2) 📍 RSVP: https://lu.ma/oo9j90j1

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Phala Cloud saw growth in the past week with more users, more VMs, and higher vCPU demand. Sure, GPU TEE usage dipped 23.6% — but on the bright side, LLM token usage for Qwen 2.5 7B Instruct went through the roof since early June. Smarter AI, sleeker compute.

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Phala Cloud saw growth in the past week with more users, more VMs, and higher vCPU demand. Sure, GPU TEE usage dipped 23.6% — but on the bright side, LLM token usage for Qwen 2.5 7B Instruct went through the roof since early June. Smarter AI, sleeker compute.

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Phala Cloud saw growth in June with more users, more VMs, and higher vCPU demand. Sure, GPU TEE usage dipped 23.6% — but on the bright side, LLM token usage for Qwen 2.5 7B Instruct went through the roof since early June. Smarter AI, sleeker compute.

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🤖 AI runs on GPUs, NOT CPUs. Modern AI workloads—think LLMs, real-time inference—need massive parallelism. GPUs like NVIDIA’s H100 do that beautifully. But here's the harsh truth: once your data hits GPU memory, it's COMPLETELY exposed. GPU TEEs change the game. 🧵

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