Justin Dao

[Justin Dao @DaongPP]

@Ryker_Crypto 882k$

[Justin Dao @DaongPP]

@quanm2831 Fake

[Justin Dao @DaongPP]

@grass

[Justin Dao @DaongPP]

@devrelius I'm very excited to see the other types of tasks coming up

[Justin Dao @DaongPP]

@TriMaiMS Ngày 0.6$ thôi bro

[Justin Dao @DaongPP]

@pussycattech Really like the vibe

[Justin Dao @DaongPP]

@pussycattech Redeem

[Justin Dao @DaongPP]

@dawninternet Bullish

[Justin Dao @DaongPP]

@davidbnb68 Ông Tuấn này hình như trước cũng chỉnh ảnh lụm to airdrop zk, nhưng vẫn để lộ đuôi ví bị cộng đồng check ra là fake sau lên bài xin lỗi thì phải =))

[Justin Dao @DaongPP]

@ManticMarket Mantic

[Justin Dao @DaongPP]

@officialcaex Giao diện website trông vibecode thế nhỉ =))

[Justin Dao @DaongPP]

@KT_BTC @grvt_io @trdEverything Cày sao để được nhiều volumn vậy bác?

[Justin Dao @DaongPP]

@carte_gg We are early
https://t.co/DhQAjNmrb6

[Justin Dao @DaongPP]

@dawninternet @neilc_dawn @LoganJastremski 👀👀👀

[Justin Dao @DaongPP]

@nguyen0xhieu Mình cũng rời thị trường với một khoản nợ lớn. Giờ cũng đang chạy grab. Trung bình 1 tuần được khoảng 3tr gì đó, ngày ra đường khoảng 10 tiếng, tính cả giờ nghỉ ngơi. Nói chung là lấy ngắn nuôi dài, cố lên bác ơi.

[Justin Dao @DaongPP]

@YungDOC351081 ok Muse from Nirgeria!

[Justin Dao @DaongPP]

@ptaanhh699 Andrew rẻ rách quá nhỉ =))

[Justin Dao @DaongPP]

@davidz9 @Gradient_HQ ./Echo-2: more chances to fail, learn, and iterate.

[Justin Dao @DaongPP]

@0xEricYang @supercyclepod Great talk Eric!

[Justin Dao @DaongPP]

@Gradient_HQ https://t.co/bKAR7HOdKo

[Justin Dao @DaongPP]

Most people don’t realize how broken real-world AI inference still is. Latency spikes, fragmented data sources, and siloed compute make “real-time intelligence” feel more like a buzzword than reality. Whether it’s agents reacting to live markets, autonomous robotics, or real-time copilots — the bottleneck is always the same: inference isn’t built for a dynamic world.

That’s exactly the gap Gradient is trying to solve with Parallax, a world inference engine. Instead of treating inference like a static API call, Parallax is designed to model the world as a constantly shifting state. It pulls signals from distributed sources, processes them across decentralized compute, and delivers context-aware intelligence that evolves in real time.

In practice, this matters more than people think. Today, traders rely on fragmented dashboards, AI agents hallucinate due to stale context, and real-time apps break under scale. A system like Parallax reframes inference as a living layer closer to how humans reason: continuously updating, contextual, and adaptive.

If Echo is about scaling how models learn, then Parallax is about scaling how models understand the world. And in a future where AI agents operate autonomously across finance, robotics, and the open internet, the real edge won’t just be better models it’ll be better inference layers.

@Gradient_HQ isn’t just building models. They’re rebuilding the intelligence stack.