Manos Koukoumidis (@Koukoumidis) profile picture

CEO @ https://xitter.twitterapi.xyz/t.co/FHoWf8TCnl

Joined June 2009
Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)Photo by Manos Koukoumidis (@Koukoumidis)
Manos Koukoumidis retweeted
Building an agent is easy. Making it reliable is hard. When your agent fails, it can happen in multiple facets: improper tool use, poor harness orchestration, or even using the wrong model under the hood. On November 4, Oumi is launching a way to build agents and train the models behind them in one workflow. Build in Oumi or bring your own harness. Oumi.ai handles the AI engineering loop. oumi.ai/events/fall26?utm_so…
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Manos Koukoumidis retweeted
We were able to fine tune an open weight model (Qwen3.5-9B) on proprietary internal data at @coinbase, and it out performed frontier models, at much lower cost and speed, for a specialized task (fraud prevention in this case). I think we'll see more of this pattern inside companies. The frontier models are amazing generalists. But increasingly you'll see specialist models out perform on more narrow tasks, either working on teams, or by themselves. We're making it easy to fine tune models internally for our employees. We even have a skill for it in our internal harness that makes it easy to spin these up and start training them: "/fine-tune-and-serve-llm I want to fine-tune Qwen for payments risk review. help me get started" I imagine we'll have some backend services that could be replaced entirely by this new architecture.
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Open-weight models put American AI innovation directly into the hands of developers, researchers, and startups. This is exactly the kind of leadership @POTUS's AI Action Plan calls for, and we're excited to see labs across the U.S. ecosystem continuing to invest in open, accessible AI.
Today we're also opening the weights for Muse Glimmer, a great 30B parameter dense model that can run locally. Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model. Meta is a strong supporter of open source and I'm proud of these releases. Congrats to @alexandr_wang and the MSL team for all your great work on these models.
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Manos Koukoumidis retweeted
Why should you own AI rather than rent it? This Wednesday, July 1, @stefan_webb is giving a live webinar not to be missed! There'll be 2 live model building demos plus a bonus interview with @MuraliMinnah from @wiredinfo, who put an SLM for word-sense disambiguation built with @Oumi_PBC into production, slashing costs, latency, while improving accuracy and other metrics!
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Manos Koukoumidis retweeted
Η startup του @Koukoumidis βοήθησε τους New York Times να εντοπίσουν τα τυφλά σημεία των AI Overviews της Google. Ήταν πολλά περισσότερα απ’ότι φανταζόμαστε. Όμως το μεγαλύτερο στοίχημα της Oumi βρίσκεται αλλού: στην αυτοματοποίηση της ίδιας της μηχανικής της τεχνητής νοημοσύνης με στόχο πιο ακριβή, πιο οικονομικά και πιο προσαρμοσμένα μοντέλα για κάθε οργανισμό. Legendary stuff από έναν από τους κορυφαίους έλληνες στο ΑΙ σήμερα. wired.com.gr/article/oumi-to…
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Manos Koukoumidis retweeted
Replying to @oumi_ai
@Oumi_PBC OSS just dropped a local MCP for building custom ML workflows in minutes!
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Manos Koukoumidis retweeted
Just had a PR merged to @oumi_ai! Multi-turn data synthesis support is now in the codebase. This enables programmatic generation of full conversational dialogues. Here's what's coming and why researchers will care 🧵 github.com/oumi-ai/oumi/pull…
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Manos Koukoumidis retweeted
Enterprises are constrained by large, off-the-shelf AI models that are costly, slow, and hard to control, while custom models promise better performance but traditionally take months to build. Today, Oumi and Lambda announced a partnership that changes this, enabling enterprises to build and deploy high-performance custom AI models in hours, not months. The result: up to 70% cost reduction, faster iteration, and full control over data, privacy, and infrastructure. Read more here: blog.oumi.ai/p/lambda-and-ou…
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Manos Koukoumidis retweeted
It’s here. AI Agents Assemble, the biggest WeMakeDevs hackathon so far. $20,000 (₹18 lakh) in cash prizes 💰 Winners get job interview opportunities. Everyone who participates gets Google Summer of Code mentorship ☀️ First place alone wins $10,000 cash 🥇 Powered by some of the biggest names in tech: @cline, @kestra_io, @vercel, @Oumi_PBC, @coderabbitai and @togethercompute! You’ll learn a lot, build with real AI tools and meet incredible people from the community. All skill levels are welcome. If you’ve ever wanted to level up, this is the perfect place to do it. 👉 Register: wemakedevs.org/hackathons/as… 🗓️ December 8 - 14, 2025 Tag someone you want to build with or someone who should take part 👇
🤝 Paid partnership
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Manos Koukoumidis retweeted
Airbnb CEO Brian Chesky: “We’re relying a lot on Alibaba’s Qwen model. It’s very good. It’s also fast and cheap... We use OpenAI’s latest models, but we typically don’t use them that much in production because there are faster and cheaper models.” The valley is built on Qwen?
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🚀 Exciting news! Falcon-H1 & Falcon-E are now on Oumi — the open-source platform for training, fine-tuning (SFT, LoRA, QLoRA), and deploying LLMs anywhere: laptops, cloud, or clusters. Start building: github.com/oumi-ai/oumi/tree… #FalconH1 #FalconE #OpenSourceAI #LLM
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Falcon-H1 & Falcon-E are now on Oumi — train, fine-tune (SFT, LoRA, QLoRA) & deploy LLMs with ease! Quickstart: oumi.ai/docs/en/latest/get_s…
Tutorials: oumi.ai/docs/en/latest/get_s…
Falcon-H1: github.com/oumi-ai/oumi/tree…
Falcon-E: github.com/oumi-ai/oumi/tree… #FalconH1 #FalconE #LLM #Oumi
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Manos Koukoumidis retweeted
So excited to announce the DCVLR (Data Curation for Vision-Language Reasoning) competition at NeurIPS 2025, led by @Oumi_PBC and sponsored by @LambdaAPI! 🌟open-data 🌟 🤖 open-models 🤖 💻 open-source 💻 💪anyone can compete for free 💪 dcvlr-neurips.github.io/ 🧵 1 / n
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Manos Koukoumidis retweeted
Our view on test-time scaling has been to train models to discover algos that enable them to solve harder problems. @setlur_amrith & @matthewyryang's new work e3 shows how RL done with this view produces best <2B LLM on math that extrapolates beyond training budget. 🧵⬇️ Website: matthewyryang.com/e3/ Paper: arxiv.org/abs/2506.09026
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Manos Koukoumidis retweeted
(1/5) We’ve never enjoyed watching people chop Llamas into tiny pieces. So, we’re excited to be releasing our Low-Latency-Llama Megakernel! We run the whole forward pass in single kernel. Megakernels are faster & more humane. Here’s how to treat your Llamas ethically: (Joint with @jordanjuravsky, @stuart_sul, @OwenDugan, @dylan__lim, @realDanFu, @simran_s_arora, and @HazyResearch)
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Manos Koukoumidis retweeted
🆕 Oumi Labs champions truly transparent AI development by opening not just model weights but training data, code, and collaborative processes - @Koukoumidis 👉 gradientflow.substack.com/p/…
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Manos Koukoumidis retweeted
We're launching our first-ever Builders in Residence Program for practical, application-driven AI researchers (PhDs, recent grads, industry). Fully remote (EU, US, CA), ~3-month fellowship starting June 2025. Learn more & Apply here: job-boards.greenhouse.io/moz…
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Manos Koukoumidis retweeted
Another week, another conference! @PersonsMatthew , @kaisopos , and @wizeng23 are  heading to Meta's LlamaCon 2025 tomorrow. 🦙 We can’t wait to see you there!
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Manos Koukoumidis retweeted
🦙 Interested in fine-tuning Llama 4, but don’t know where to start? 👀 Take a look at our quick walkthrough on how to fine-tune Llama 4 with Oumi! @JeremyGreerOumi will get you started in just a few lines of code. 🎥 youtube.com/watch?v=Rsorf8H8…
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