Unlock the True Power of Data! 💰📊 @juliensimonfr

Uploaded August 2024 | Updated September 2026, 2 weeks ago

Diving deep into the often-overlooked treasure trove of data, this enlightening discussion reveals how improving your data sets can yield immeasurable returns compared to the constant race for the newest AI models. Discover the long-term investment strategies that could elevate your projects, maximize efficiency, and supercharge performance. Why chase the shiny object when a powerful foundation is just a tweak away? Transform your approach and watch your ROI soar! #DataInvestment #AI #MachineLearning #DataScience #LongTermGrowth #Efficiency #BusinessStrategy #ROI #DataManagement #TechTrends #AIModels #InvestmentStrategy

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$Trinity Large: An Open 400B MoE Model I built a code review app powered by @ArceeAIs new Trinity Large model and deployed it to a @HuggingFace Space. ⭐️⭐️⭐️ More content on Substack at https://julsimon.substack.com ⭐️⭐️⭐️ In this video, I walk through a live demo — paste a GitHub PR URL, hit review, and watch it catch real issues: security flaws, logic bugs, missing edge cases. Its fast, free to try, and the 512K context window lets it process entire files without chunking. Code Review App (HF Space): https://huggingface.co/spaces/juliensimon/trinity-code-reviewer Trinity Large is a 400B parameter Mixture-of-Experts model trained in 33 days for $20M — a fraction of what frontier labs spend. It has 256 experts but activates only 4 per token, so only 13B active parameters do the work. That translates to 2-3x faster inference than anything in its weight class, which you can feel in the demo when reviews come back in seconds. In this video: - 🔴 Live demo: code review app catching real issues on real PRs - 🏗️ How I built the app — stack, prompting strategy, handling large diffs - 🧠 Architecture deep dive: 256 experts, 4 active, extreme sparsity - 📦 Why three checkpoints exist: Preview, Base, and TrueBase - ⚡ Why MoE makes this practical to actually deploy and run at scale Try the app yourself and let me know what it catches in your code. Hugging Face model page: https://huggingface.co/arcee-ai/Trinity-Large-Preview OpenRouter model page: https://openrouter.ai/arcee-ai/trinity-large-preview Arcee AI blog post: https://www.arcee.ai/blog/trinity-large Arcee AI technical report: https://github.com/arcee-ai/trinity-large-tech-report VentureBeat article: https://venturebeat.com/technology/arcees-u-s-made-open-source-trinity-large-and-10t-checkpoint-offer-rare-look$

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