Giuseppe Skyline

GN CT execution is where most value quietly disappears not at entry, not at exit — but in between @dango – orders are collected over short intervals instead of instant matching – cleared through batch auctions at a uniform price – removes first-come priority and reduces latency advantage – limits MEV and front-running opportunities – price discovery reflects combined demand, not fragmented timing this shifts trading from speed competition to structured execution @0G_labs – modular stack separates compute, storage, and data availability – allows heavy AI workloads without bottlenecking the system – execution remains verifiable across distributed nodes – supports fine-tuning with traceable datasets and tasks when systems are designed like this outcomes become easier to trust because they can be proven

📣 Microsoft @Azure and NVIDIA are bringing deep co-engineering to enable AI companies to bring agents to production. This includes: ✅ Microsoft Foundry for AI agents, including leading models such as NVIDIA Nemotron. ✅ New Azure AI infrastructure, with plans to roll out NVIDIA Vera Rubin NVL72 systems into Azure data centers in the next few months. ✅ Microsoft Foundry, Microsoft Fabric, and NVIDIA Omniverse for physical AI. Learn more ➡️ nvda.ws/41XgMoP

Lowkey in this bad market I have been hunting for yield that doesn’t live or die by market direction and I stumbled on @alturax After digging deeper, what stood out wasn’t hype , it’s how they structure their yield: They don’t rely on one play, they run 3 non-directional strategies at the same time which are 1. Delta-neutral market making (capturing spreads) 2. Funding rate & basis arbitrage (works both ways) 3. RWA gold trading (not tied to crypto at all) So when one slows down, capital rotates to the others. With the Current setup you get : 1. ~50% APY, no lockups 2. $11M+ TVL 3. Fully transparent dashboard I’ll be breaking down how each strategy holds up in different market conditions soon follow me and watch out. 👌

Cadence CEO Anirudh Devgan and @nvidia CEO Jensen Huang are back on the #CadenceLIVE stage! Don’t miss their fireside chat on April 15—shaping the future with Design for AI and AI for Design. Register now: ow.ly/9TYH50Yt9Ar

Good Night 🌌 @dango changes how trades actually conclude. Instead of outcomes being decided by who gets in first, activity is grouped into short windows and resolved together, so execution reflects real market conditions rather than timing advantage. It quietly removes the edge that faster actors usually rely on and makes results easier to reason about over time. @0G_labs approaches AI from a structural level. By separating compute, storage, and data availability, it allows each layer to scale without slowing the others down, while keeping execution traceable across nodes. This turns model training and inference into processes that can be followed and verified instead of treated like black boxes. at the end of the day, systems that prove how they work tend to last longer than ones that ask for trust @Permaweb_DAO keeps data from fading it stays accessible, consistent, and usable over time so what gets created doesn’t disappear with the platform

Your guide to building data and AI apps that actually make it to production 👇 As an app developer, you shouldn't have to spend months on DevOps just to get a prototype across the finish line. This ebook shows you how to ship production-ready data and AI apps on the Databricks Platform even faster, using end-to-end examples and code snippets, without learning new infrastructure. You'll learn how to: - Move from notebooks and prototypes to real applications - Serve analytical data and application state through a transactional layer - Build secure, governed apps without custom infrastructure - Deploy and operate using repeatable, production-ready patterns databricks.com/resources/eboo…

Robot Animation attempt #blender #animation #3dmodel @IsThisA3DModel @adultswim