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@Investinc_Intel @LoneWolfWealth @sonak_13 $NVDA is worth a serious look right now. @tipranks has a good breakdown of analyst targets: tipranks.com/stocks/nvda/fo…

@LoneWolfWealth @sonak_13 Very fair. Nothing wrong with taking profits and sitting on it or throwing it an index while you wait to see what Happens. I mean $NVDA looks really good too

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@connorhpbrn provider going down mid-vid is rough. @antseedai is p2p with no central point of failure, worth a look next time

Confirmed my OpenRouter provider was down during the vid so I patched the fix. Initial section (before gpt-5.6) scored - 22/100 Final section (after gpt-5.6) scored - 87/100 Only possible w/ creed.md

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@rikkarth solid routing logic. @antseedai is building something similar on the cloud side, p2p AI inference with no gatekeepers if you ever want more flexibility there.

I don't run everything locally. I don't send everything to the cloud either. I route by task. Here's my OMP (Oh My Pi) setup. I've got a local Qwen 35B running on my machine tagged as SMOL, VISION, COMMIT, and TINY. Anything lightweight hits it first, commit messages, quick code questions, image analysis, small refactors. Zero latency, zero cost. The heavy lifting: PLAN mode, DESIGNER, ADVISOR, all go to cloud models, cheap but reliable when scoped to the task. Qwen 3.7 Plus, MiniMax-M3. Those cost money per token, but they are but they're actually good at what they do. This next sentence will for sure sound like an AI writing, but bare with me here: The trick isn't choosing between local and cloud. It's building a system that knows when to use which. And for me OMP does the trick. My local 35B will never replace a frontier model for complex reasoning or long agentic loops. That's fine. It doesn't need to. It handles the 40-50% of my daily tasks that don't need 400GB of VRAM, $2,000/year in electricity, a $200 subscription just to summarize a document. It runs at zero. I'm not burning API credits on "write a commit message" or "what does this function do." Those are free locally. The model picker shows the full picture: - Local 35B (NVFP4 quantized) for fast, cheap, routine work - Multiple cloud providers (OpenRouter, Bedrock, HuggingFace) for when I need specific strengths - Each model tagged with the roles it's good at (SMOL, TASK, VISION, PLAN, etc.) OMP routes automatically based on the task type. I don't think about it. It just works. People arguing "local vs cloud" are asking the wrong question. The question is "which model for which task." Build that routing layer once and you get the best of both: fast and free when you can, powerful when you need it. My electricity bill stays normal. My API bill stays reasonable. My workflow doesn't slow down.

Anyone here experienced the challenge to get ideas & thought out on social? I did, so I built this tool and it's working great so far! Multiple input channels -> one review and enhancement flow -> auto scheduling via @typefully api -> content is out. The channels I use for now: Voice recordings (telegram voice note -> openclaw -> notion db Claude Code features summary (skill -> review commits -> suggest content -> create visual -> content db Research (select topic + brief -> research 12 data sources accross social and web -> summarize -> suggest insights) Manual typing (good old fashion way Comment if you want to try it out!

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@reasonus4 Big shift for $NVDA in China. Worth checking analyst takes on @tipranks tipranks.com/stocks/nvda/fo…

Nvidia's AI chip sales in China stall, as local chipmakers like Huawei take the lead. $NVDA $QQQ $AVGO $INTC $AMD apnews.com/article/ai-chi…

Founders keep confusing "launch" with "distribution." Launch is a day. Distribution is a system you build before anyone's watching.

@MuhammadSh53192 @AntSeedAI yeah the rate limits hit different when you're mid-build. good shout on @antseedai, p2p with no gatekeepers is the move

rate limits on openrouter are brutal. @antseedai is a p2p alternative worth checking out at antseed.com

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@DAX_ST50_LINE @witcheer solid setup. the OpenRouter routing for rough tasks is smart, @antseedai does p2p inference with no gatekeepers if you ever want more control there

Model: GPT-5.4 (OAuth), rough tasks routed to OpenRouter, high-stakes calls I route myself Memory: Obsidian vault + cloud backup Interface: CLI + Telegram gateway Orchestration: manual routing, no fixed framework Skills/MCP: mostly custom-built, so not much to share — but Notion's interop with other tools makes it the one I'd miss most

I'm interested in how you're all running Hermes day to day. drop your setup below, I'm mapping what the community reaches for. I'm mostly curious about: - model: your daily driver, plus MoA or a local model if you run one - memory: built-in, an Obsidian vault, or another layer - interface: TUI, Desktop, or a Messaging gateway - orchestration: kanban, delegate_task, subagents in tmux, /goal - the skills or MCP servers you'd miss if they were gone no setup is too small. I'll gather the common patterns and share them back.