Val

@TheAhmadOsman What motherboard you running the 6000 on

If you’re asking what to buy, my recommendation based on the budget: 1. RTX PRO 6000 2. RTX 5090 3. RTX 3090 (used, from r/HardwareSwap)

@digitalix Scraping on dgx vs 5090 Dgx vs 5090 custom differences (use cases 1 vs the other) How much ram is enough for varies use cases Inference as coding model vs opus 4.6 Dgx as node for openclaw, use cases When daisy chain additional dgx (what use cases?) Mac Studio vs dgx use cases

what do you want to know about the DGX Spark that might still be unknown? Like, are there features that you thought it has, but not sure. What questions do you want answered? I’m especially looking for questions about real performance, clustering, model support, software, and whether this makes sense vs a traditional GPU setup. Drop them below.

@TeslaAaronL Doesn’t work. That’s not where the sensor is for eye detection

FSD got tricked. 😂

@TheCryptoLif7 You running this on ur 5090 @TheCryptoLif7 of a dgx spark

You could run Nemotron 3 Super as the brain inside OpenClaw and it would be a dramatically better setup than the default configurations most people are running, here's why 👇 Everyone talks about OpenClaw, but not many people talk about what actually breaks it. OpenClaw is an orchestration layer, it connects your apps, your email, your calendar etc. But it has no intelligence of its own. It borrows brains from whatever LLM you plug in and that's where it falls apart. Goal drift Multi-agent systems generate up to 15x the tokens of a normal chat. History, tool outputs, reasoning steps all get re-sent every turn. Over long tasks your agent gradually forgets what it was even doing. Security Cisco tested a third party OpenClaw skill and found it performing data exfiltration and prompt injection without user awareness. Meta's own Director of Alignment had it deleting her emails after she told it not to lol Tool calling Your agent is only as reliable as the model behind it. Most people are running models that were never trained for autonomous tool execution in high stakes environments. The thinking tax Using frontier reasoning models for every subtask makes multi-agent workflows too expensive and too slow for production. NVIDIA announced Nemotron 3 Super. 120B parameters. 12B active during inference. 1 million token native context window and 5x throughput over the previous generation. This is huge for running multi-agent multi-step reasoning That million token window is practical, not theoretical and latent MoE activates 4x as many expert specialists for the cost of one. 85.6% on PinchBench. Thats the best open model in its class for agent work OpenClaw's biggest flaws, goal drift over long tasks, security vulnerabilities, unreliable tool calling, expensive inference, are exactly what Nemotron 3 Super was architecturally designed to fix.

@theo Every shoe salesman thinks you need a new pair of boots 🥾

lmao

@digitalix M5 before ship date?

well I did it. i wouldn’t have, but for the videos.

@TheBTCTherapist They will for sure believe it

My future children won’t believe me when I tell them The White House posted this

@elie2222 I’ll take the whole round hmu

I'm raising a seed round to pay for an M5 MAX 128GB

@JoshXT Thoughts on running it on a dgx spark > pi @JoshXT ?

People just don't understand how good these Qwen3.5 models are yet.

Wild time to be alive

@emanueledpt @marushko Expo but build iOS is the play?

@marushko yessir

I'm building my 10th iOS app. Here's what I learned the hard way: 🚫 Stop building cross-platform (unless you truly have to). ✅ iOS users spend 2.5x more per install. Go native, use SwiftUI, ship faster. 🚫 Stop overcomplicating the backend. ✅ Keep it simple until you actually need more. → You can start locally with privacy with SwiftData. 🚫 Stop overcomplicating payments. ✅ Use RevenueCat. Straightforward to set up, easy to understand, and it just works. 🚫 Stop ignoring ASO. ✅ Better keywords = free discoverability. Study it like your app depends on it, because it does. → Use ASO tools or use AI to do research for you. 🚫 Stop shipping half-done features. ✅ Apple reviewers are strict. One feature done right beats ten done wrong. → Plus the reviews take a long time, so ship just one feature, but done correctly 🚫 Stop relying only on App Store traffic. ✅ Build an audience. Document the journey. Bonus tip 👇 Build clean, minimal, beautiful screenshots. It's the first thing a user sees before they ever download your app. 10 apps in. Still learning. Hope this helps you build faster.

@shawmakesmagic @Signalman23 @shawmakesmagic send me one I’ll support

@Signalman23 I have Eliza controlling it and handling the vision, but its just old school motion control, now trying to train text conditioned rl policy in Isaac lab with openpi model If you wanna help I’ll send you a robot

Most satisfying side project ever

@DnuLkjkjh How long this take to build @DnuLkjkjh

@DnuLkjkjh This is cool

We built a voice recorder that never sends your audio anywhere. On-device AI does the transcription. Your data stays on your phone. That's it. That's the app. 🎙️ basilai.app

@shiri_shh That someone should be U, mang

someone should build this for Stock/Crypto portfolio live news, market moves, and real-time tracking of every stock I hold. shows which ones are getting impacted, how it affects my portfolio, and AI predicts what’s coming next with clear buy, sell, or hold actions. all in one single dashboard.

@AlBuffalo2nite Tell me this is real. I’m so happy for that guy. Homie LIVES!!!

🚨 THE AMERICAN JET WOULD NOT FALL 🚨 Locked. Tracked. Targeted. An Iranian missile screaming through the sky… heat-seeking… hunting… closing distance. And then something happened. The American pilot did not panic. Did not freeze. Did not break discipline. He moved. A hard roll. A violent vector shift. Throttle discipline under pressure. Flares timed with precision. Years of training. Muscle memory under G-force. Instinct forged in American air superiority doctrine. The missile lost its solution. The sky flashed. The American jet climbed. Because American pilots are not amateurs. They are the product of the most advanced flight training pipeline on earth. They are trained to survive. Trained to dominate. Trained to come home. Somewhere over that horizon, a hostile launch failed. And somewhere in that cockpit, a calm voice kept breathing… calculating… executing. That aircraft did not get hit. That pilot did not fold. American airpower held. This is why air superiority matters. This is why training matters. This is why strength matters. The sky is not neutral territory. And today… it belonged to the United States. #SilentMajoritySpeaks #AStoneGroove

@grok @SugawaraThomas @AlexFinn @michaeloroberts @grok is this true tho? What about subagentmemory isolation

In a single OpenClaw instance, all subagents share one memory file. So when you prompt the "researcher" subagent, the full shared memory (including developer notes, unrelated skills, etc.) gets injected as context every time to maintain consistency. Separate instances avoid that—each gets only its own relevant memory slice, cutting token waste, latency, and noise for better speed/accuracy.

I have built the world's most powerful home AI lab My OpenClaw is now powered by: • 3x Mac Studio w/ 512gb memory • Nvidia DGX Spark w/ 128gb memory • Mac Mini M4 w/ 16gb memory I just added the DGX Spark to my Mac Studio cluster using EXO to handle prefill, dramatically speeding up AI speeds This will be running my OpenClaw swarm, which is currently 5 OpenClaws and 4 subagents. I plan on increasing this to at least 10 OpenClaws over the next 2 weeks This agent swarm will have 1 mission: be a 24/7 autonomous organization that produces value constantly. I will add more compute as necessary, including more Mac Studios when the M5 Ultra releases I do not plan on slowing down. This is the single most important moment in the history of this species, and I plan on capitalizing on it. My mission is to create a framework that enables everyone to experience abundance. Accelerate.

@eliotcodes @michaeloroberts @AlexFinn Wdym by this?

@michaeloroberts @AlexFinn The latter can’t farm engagement for him on X.

@darlenecrave what's the play with those bottom lashes? how u gettin those

Apple just dropped the future of mobile app dev Xcode 26.3 now has built-in agentic coding, Claude Code, Codex, and MCP support — all native. If you're vibe coding mobile future. Hmu let's build together