I’m watching @0G_labs compress the DeAI stack into a single fabric: compute, storage, and data availability stitched so AI workloads scale, verify, and plug into onchain rails
What’s shipping:
→ 0G Hub redesign: claim testnet tokens instantly, swap seamlessly, track positions in real time → Modular data pipelines that kill bottlenecks for training/inference → Docs evolving with community feedback so newcomers onboard fast → TGE slated for Q3 with community allocation on seasonal unlocks; 20% at TGE, 48 months to full → Leaderboards, roles, and reputation loops to spotlight consistent builders
And the architecture direction points to a world where “blocks” feel obsolete as parallel proofs push finality to the foreground
When agents need verifiable compute and low-latency DA, adoption becomes reflexive: more builders → tighter tooling → more users → stronger signal
If you’re shipping AI-native apps, hit the hub, spin the testnet, claim your lane now
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GM builders,
I’m watching @0G_labs compress the DeAI stack into a single fabric: compute, storage, and data availability stitched so AI workloads scale, verify, and plug into onchain rails
What’s shipping:
→ 0G Hub redesign: claim testnet tokens instantly, swap seamlessly, track positions in real time
→ Modular data pipelines that kill bottlenecks for training/inference
→ Docs evolving with community feedback so newcomers onboard fast
→ TGE slated for Q3 with community allocation on seasonal unlocks; 20% at TGE, 48 months to full
→ Leaderboards, roles, and reputation loops to spotlight consistent builders
And the architecture direction points to a world where “blocks” feel obsolete as parallel proofs push finality to the foreground
When agents need verifiable compute and low-latency DA, adoption becomes reflexive: more builders → tighter tooling → more users → stronger signal
If you’re shipping AI-native apps, hit the hub, spin the testnet, claim your lane now
#0g 0g_Labs #Starboard Galxe