L1mbo ./
@l1mbo_forest
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the ability to rl models, build and personalize them as your own is one of the best developments towards more productive AI. design models around your focuses, tasks, & goals. let it learn in different environments and evolve with collaboration through distributed systems. the
the era of living inference is here. thanks to rl, models aren't just predicting patterns. they are reasoning. thinking time is the new scaling law. it demands compute density that distributed systems can handle elegantly. for parallax, serving tokens is too basic. we are
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the era of living inference is here. thanks to rl, models aren't just predicting patterns. they are reasoning. thinking time is the new scaling law. it demands compute density that distributed systems can handle elegantly. for parallax, serving tokens is too basic. we are
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Looks like 2026 is gearing up to be the next generation of Agentic Intelligence. This past week we’ve seen Nvidia & Xiaomi release extraordinary Open Models. Nemotron 3 Nano by Nvidia is designed with Hybrid Mamba Transformer MoE, with 31.6B total params (~3.6B active/token), 52
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Symphony: Orchestrating AI Without a Conductor We’ve seen multi-agent frameworks like AutoGen, MetaGPT and CrewAI achieve incredible things. But they all share one fatal flaw: Centralization. They rely on a "master node" to route every task, creating bottlenecks, single points
Symphony’s collaborative intelligence with multi agents delivers with robustness. In effectiveness Symphony leads with: - On BBH: Symphony improved 6.5–41.6% over Direct Solving and up to 29.1% over AutoGen (biggest gains on weaker models like Mistral). - On AMC: Smaller but
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./ GRADMAS ART CONTEST 🎄 Create a Capybara Christmas w/ Gradient. Open to all formats such as traditional, digital or experimental! Whether it’s drawing or video show your creation and give us a few lines about your Capybara Christmas w/ Gradient! 🗓️ Deadline Dec 23 @ 4:59PM
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Huge congrats to the winners of the Parallax competition! We were blown away by the creativity and technical depth of the submissions. From massive local clusters to distributed AI apps, you pushed Parallax in ways we didn’t expect. Here are the 8 winning projects. 🧵
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from the view of credit default swap, it doesn’t seem like institutions are too confident in the fulfillment of these commitments. capex at this level is unsustainable (in oracles case 500% debt to equity). we once again see companies trying to strong arm resources with extreme
REPORT: Oracle $ORCL now has $248 Billion of AI/cloud data center lease commitments. This is up $150 Billion from the $99 Billion in commitments reported at the end of August.
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AI memory is broken. We’re fixing it with "Living Memory". Most AI agents today face a critical choice: "digital amnesia" (forgetting everything) or "data gluttony" (remembering too much noise). SEDM (Scalable Self-Evolving Distributed Memory) from @Gradient_HQ turns memory
To advance more usable intelligence, adaptation and learning from unique experiences are essential for applying it effectively. SEDM addresses the current challenges of agents being clogged by low value information that raises retrieval cost, redundancy, and locked contexts. It
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To advance more usable intelligence, adaptation and learning from unique experiences are essential for applying it effectively. SEDM addresses the current challenges of agents being clogged by low value information that raises retrieval cost, redundancy, and locked contexts. It
Gradient on the ground at NeurIPS. Research. Build. Scale. Repeat.
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Open mic with builders, judges, and Parallax core devs Let's talk local AI. Dec 15 • 7:45pm PT
hi, it’s christmas season! just a heads-up: we’re sending out gifts today. we’ll be demoing some cool local ai showcases and giving away awards on parallax x account's space in dec 15th 19:45pt. we’ll also have parallax core devs joining for an AMA, discussing any tech details
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🧩@Gradient_HQ Puzzle Mastermind! Join us Now til Dec 12th 10am EST! 🏆 Top 10 Participants will receive Quiz Mastermind on Discord! Rules: - username must match DC username - play as many times & anytime you want during event duration ./ puzzle here: https://t.co/ddExozH0Xa
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Information Sovereignty: The Next Frontier of Freedom Notice a pattern: everything big that has happened in history starts with centralization and ends with distribution. The telegraph became the internet. Banks faced Bitcoin. And now, AI is leaving the mainframe era. Bitcoin
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Showcasing Localized Machine Madness, where we used numerous machines on Parallax by @Gradient_HQ to pilot different frontier models. First let’s pilot Z AI’s GLM 4.5 Air with 8 Nvidia RTX A6000 GPUs:
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The first week of Gradcember is coming to an end, and today is the final day to submit for the "Build Your Own AI Lab" challenge by @Gradient_HQ 🤖 Stand a chance for winning a DGX Spark (1st place) or Mac Minis (2nd-8th) by: - Showcasing your sovereign AI setups powered by
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In DeAI, @Gradient_HQ is innovating with Open Intelligence Stack (OIS). Whether it’s creation, collaboration or development of intelligence it should be open. ./ the shift from closed to open is clear.
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anonymity is a joke. 20+ million chatlogs of sensitive data is being exposed. your privacy can be violated at any given point you can now store, build, process and operate intelligence on your machines time to restore your own privacy ./ run locally with Parallax @Gradient_HQ
PRIVACY? Judge Ona Wang just ordered OpenAI to hand 20M private chat logs to the New York Times. Your health, financial, and personal chats could soon be in NYT hands. In a deeply troubling ruling, magistrate judge Ona T Wang ordered OpenAI to turn over more than 20 million
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Gradvember for @Gradient_HQ Overview 🍁 November has been a huge month for our mission towards Open Intelligence: - Parallax Eco Track - Parallax #1 on Product Hunt - Kimi K2 Thinking Available - Z AI Partnership - Build Your AI Lab - DSD Framework ./ THINK OPEN 🧵
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Turning Waiting Time into Winning Time: How DSD Solves the Latency Bottleneck In decentralized AI inference, network latency is the silent killer of performance. When running models across distributed nodes, systems often spend more time waiting for data to travel between
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