Phala ✓

@PhalaNetwork · San Francisco, CA · joined 27 Aug 2019

Empowering 10,000 builders and companies to build scalable, private, and safe intelligence.

141 081Followers

836Following

6 334Posts total

68KViews on collected posts

Ultimi post

Phala ✓@PhalaNetwork4 Sep

Phala Confidential AI: 38.86 billion billed input + output tokens over the past 24 hours. Top models: 1. DeepSeek V4 Flash — 28.59% 2. GLM-5.2 — 13.61% 3. GLM-5.3 — 9.53% Explore #1: https://t.co/HFFGd77pc1 TEE-backed AI infrastructure. https://t.co/LJZU5O8oer 3.5K views · 66 likes · 6 reposts · 4 replies Open on X →

Phala ✓@PhalaNetwork4 Sep

ViMax transforms ideas, novels, or scripts into multi-scene video plans and final generated clips. The Phala template uses a source_verifier runtime. https://t.co/vRJiogOCEI https://t.co/ELlLUmPw2u 3.8K views · 53 likes · 4 reposts · 1 replies Open on X →

Phala ✓@PhalaNetwork1 Sep

39.81 billion tokens powered Confidential AI on Phala over the past 24 hours. Top models: 1. DeepSeek V4 Flash — 29.90% 2. GLM-5.2 — 17.19% 3. Kimi K3 — 14.98% Explore #1: https://t.co/HFFGd77pc1 TEE-backed AI infrastructure. https://t.co/9TzuFhBlgY 6.3K views · 64 likes · 8 reposts · 0 replies Open on X →

Phala ✓@PhalaNetwork31 Aug

Phala Confidential AI network token volume: 42.98 billion billed input + output tokens over the past 24 hours. Top models 1. Kimi K3 — 35.48% 2. DeepSeek V4 Flash — 22.56% 3. Qwen3.5 397B A17B — 8.50% https://t.co/eHSPzOFiwk TEE-backed AI infrastructure. https://t.co/3IiBcsdve 4.9K views · 98 likes · 14 reposts · 6 replies Open on X →

Phala ✓@PhalaNetwork23 Jul

@PhalaNetwork Why aren't these amounts quoted in $PHA? https://t.co/YFigTr3Crf 246 views · 2 likes · 0 reposts · 0 replies Open on X →

Phala ✓@PhalaNetwork25 Jun

For builders, this points to the next bar for private AI infra: scale Kubernetes workloads while preserving hardware-backed identity per Pod. Full writeup: https://t.co/KdtOc2Vo75 1.7K views · 22 likes · 1 reposts · 0 replies Open on X →

Phala ✓@PhalaNetwork25 Jun

The paper introduces dstack-capsule: Pod-level attestation, privilege fuse, multi-layer sandbox, and a Kubernetes implementation on Intel TDX + Sysbox. dstack: https://t.co/bzMCR6DXVw https://t.co/WKxzSCSpQA 2K views · 25 likes · 2 reposts · 1 replies Open on X →

Phala ✓@PhalaNetwork25 Jun

The design uses a two-layer model: • static platform measurements frozen in RTMR[3] • dynamic Pod identity carried in TDX Quote report_data A verifier can check the Pod before it receives secrets, data, or service access. https://t.co/pzlNl8pnxa 1.7K views · 19 likes · 1 reposts · 1 replies Open on X →

Phala ✓@PhalaNetwork25 Jun

What changes at Pod level: attestation moves from “this VM looks right” to “this exact Kubernetes Pod is running the expected image, on measured hardware, with the expected cluster identity.” That is the trust layer cloud-native AI needs. https://t.co/ZQmDVR7Tf2 1.7K views · 23 likes · 2 reposts · 1 replies Open on X →

Phala ✓@PhalaNetwork25 Jun

OPPO × Phala published a joint paper on Kubernetes Pod-level remote attestation for confidential AI. Goal: prove the hardware, container image, and Pod identity before sensitive data enters the workload. https://t.co/jQjC6DFsS0 https://t.co/fX68Ij8ECm 42.1K views · 146 likes · 25 reposts · 16 replies Open on X →

Rispetto ad account della stessa dimensione

4 post degli ultimi 90 giorni, accanto alla fascia di 100K–1M follower. arriva ben oltre il proprio pubblico, e quel pubblico reagisce.

Visualizzazioni mediane4 371questo account5 983mediana per 100K–1M

Copertura, %3.10%questo account1.49%mediana per 100K–1M

Interazione, %1.86%questo account0.93%mediana per 100K–1M

Metrica	Questo account	Mediana per 100K–1M	Rapporto
Visualizzazioni mediane per post	4 371	5 983	0.73×
Copertura (visualizzazioni ÷ follower)	3.10%	1.49%	2.08×
Tasso di interazione	1.86%	0.93%	2.01×

Altri account di questa fascia → Confronta con un altro account → Come sono costruiti questi parametri →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.