Qwen
artificial intelligence chatbot developed by Alibaba Cloud
Episodes
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#5467: Small Models, Big Schemas: When JSON Constraints BackfireSmall models plus strict JSON schemas should be a safe bet. A 15,000-generation study found the opposite. -
#5460: Four Small Models, One Android Phone: Does It Actually Work?A chained on-device dictation pipeline — VAD, ASR, cleanup — and why "it feels smooth" isn't the same as knowing it works. -
#5436: Small Models as Rewriters, Not WritersWhy "don't say X" prompts backfire, and how a tiny grammar-constrained model can scrub a script without breaking its grammar. -
#5411: Fine-Tuning at 4-Bit vs 16-Bit: What It Really CostsQLoRA cuts fine-tuning VRAM 15x and cost up to 85% — but you pay in training time, quality, and safety alignment. -
#5301: Why Talking Robots Are Really a CommitteeThat humanoid chatting while it moves? It's not one brain — it's a stack of separate models glued together. -
#5188: DeepSeek's Point Release That Isn'tDeepSeek shipped a whole new architecture and called it a point release. Here's what actually changed inside the model. -
#5184: AI Is a Number Factory, Not a WordsmithUnder the prose, every AI model is just matrices of floating-point math. So where does the randomness actually come from? -
#5113: Can Rival Labs Poison AI Training Data?A few hundred crafted documents can shift a model's stance. Here's how data poisoning actually works. -
#5830: Serving Your Own Fine-Tuned Model in the CloudYou fine-tuned an open-weight model. Now how does anyone actually talk to it? Dedicated GPUs vs serverless inference, and the math that decides it. -
#5697: Decision Models That Return Probabilities, Not TextA new class of model skips text generation entirely and returns calibrated probabilities in one forward pass. Here's what that changes. -
#5410: Adapters: 102KB That Reshapes a 403GB ModelA 102KB adapter file changes how a 403GB base model behaves — without ever merging into it. Here's how model adapters actually work. -
#5393: Fine-Tuning a Model on 100 Hand-Edited AnswersYou don't need 10,000 examples to make a model sound like you. The real number is closer to 100 — if the edits are opinionated.