SIMA 2: A Gemini-Powered AI Agent for 3D Virtual Worlds - Google DeepMind
<a href="https://news.google.com/rss/articles/CBMiqAFBVV95cUxPNUFPX2NVSk5Hc3hDdVVORGFvdnNUR29BMzd6a3JqUFY0cy1WTVRXZkNrNlpIc0s0VGZPazNCbUFDbkQwNW5URTkyUUNnRDV3OVVkMElxOEZPTk44V1VtRUJtellVM0pjbkplT1hFOWlPN29nLTQ0V2U2cGNObjJmUWl4QzA3VFlzb25RUkdoejJFTkg0REhWUk00Z1RLdmt4TDJ0M2JvWHk?oc=5" target="_blank">SIMA 2: A Gemini-Powered AI Agent for 3D Virtual Worlds</a> <font color="#6f6f6f">Google DeepMind</font>
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FOR ME, Qwen3.5-27B is better than Gemini 3.1 Pro and GPT-5.3 Codex
<!-- SC_OFF --><div class="md"><p>There's something I hate about the big SOTA proprietary models. In order to make them better for people who don't know how to program, they're optimized to solve problems entirely autonomously. Yeah, this makes people over on <a href="/r/ChatGPT">/r/ChatGPT</a> soypog when it writes a 7z parser in Python because the binary is missing, however, for me, this makes them suck. If something isn't matching up, Qwen3.5-27B will just give up. If you're trying to vibecode some slop this is annoying, but for me this is much, much better. I'm forced to use GitHub Copilot in university, and whenever there's a problem, it goes completely off the rails and does some absolute hogwash. Like, for example, it was struggling to write to a file that had some broken permission
Celebrando la Excelencia: Premios Globales de Emparejar de MongoDB 2025
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Training mRNA Language Models Across 25 Species for $165
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s912ur/training_mrna_language_models_across_25_species/"> <img src="https://external-preview.redd.it/nVu8HcAwsZ22nurNc_vAW-R_2drotHTdQavTOwGgmi4.png?width=640&crop=smart&auto=webp&s=00c766290f7df67dcd9c20ff789b8f25a14b886b" alt="Training mRNA Language Models Across 25 Species for $165" title="Training mRNA Language Models Across 25 Species for $165" /> </a> </td><td> <!-- SC_OFF --><div class="md"><p>We built an end-to-end protein AI pipeline covering structure prediction, sequence design, and codon optimization. After comparing multiple transformer architectures for codon-level language modeling, CodonRoBERTa-large-v2 emerged as the clear winner with a perplexity of 4.10 and a Spearman CAI correlation of 0
You guys seen this? 1-bit model with an MMLU-R of 65.7, 8B params
<!-- SC_OFF --><div class="md"><p>This is nuts.</p> <p><a href="https://huggingface.co/prism-ml/Bonsai-8B-gguf">prism-ml/Bonsai-8B-gguf · Hugging Face</a></p> <p>has anyone tested this thing?</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/OmarBessa"> /u/OmarBessa </a> <br/> <span><a href="https://www.reddit.com/r/LocalLLaMA/comments/1s91jxl/you_guys_seen_this_1bit_model_with_an_mmlur_of/">[link]</a></span>   <span><a href="https://www.reddit.com/r/LocalLLaMA/comments/1s91jxl/you_guys_seen_this_1bit_model_with_an_mmlur_of/">[comments]</a></span>
[P] Looking for people who have had training runs fail unexpectedly to beta test a stability monitor. Free, takes 5 minutes to add to your existing loop. DM me.
<!-- SC_OFF --><div class="md"><p>Anyone actively training models want to try a stability monitor on a real run? Trying to get real world validation outside my own benchmarks.</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/Turbulent-Tap6723"> /u/Turbulent-Tap6723 </a> <br/> <span><a href="https://www.reddit.com/r/MachineLearning/comments/1s93kzm/p_looking_for_people_who_have_had_training_runs/">[link]</a></span>   <span><a href="https://www.reddit.com/r/MachineLearning/comments/1s93kzm/p_looking_for_people_who_have_had_training_runs/">[comments]</a></span>
FOR ME, Qwen3.5-27B is better than Gemini 3.1 Pro and GPT-5.3 Codex
<!-- SC_OFF --><div class="md"><p>There's something I hate about the big SOTA proprietary models. In order to make them better for people who don't know how to program, they're optimized to solve problems entirely autonomously. Yeah, this makes people over on <a href="/r/ChatGPT">/r/ChatGPT</a> soypog when it writes a 7z parser in Python because the binary is missing, however, for me, this makes them suck. If something isn't matching up, Qwen3.5-27B will just give up. If you're trying to vibecode some slop this is annoying, but for me this is much, much better. I'm forced to use GitHub Copilot in university, and whenever there's a problem, it goes completely off the rails and does some absolute hogwash. Like, for example, it was struggling to write to a file that had some broken permission
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