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I’ve been using state-of-the-art models to teach small models running on my computer how I work. My personal agent, based on Pi, runs my inbox, my deal pipeline, my blog publishing...
Post-training methods (RLVR, On-policy distillation) are Episode-local Language models are getting better at learning from feedback during post-training. In reinforcement learning...
You don't need a PhD to understand fine-tuning. This article explains how pretrained models learn new skills through fine-tuning.
LayerNorm, residuals, feed-forward blocks, and the encoder-decoder pipeContinue reading on Data Science Collective »
You don’t need 8 GPUs to fine-tune a large model. You need the right 0.1% of parameters,here’s how to find them.Continue reading on Medium »
Today, generating five seconds of video with a strong open model, such as Wan2.1–14B or HunyuanVideo, means waiting minutes. You write a…Continue reading on Medium »
A general language model knows a little about everything. It knows some medicine. Some law. Some code. Some cooking. But it doesn't know your specific domain deeply. It doesn't kn...
Discover three post-hoc methods for closing the gap between confidence and accuracy.
In 2012, AlexNet proved that Deep Learning worked. But it was a messy, hand-tuned architecture that felt more like alchemy than…Continue reading on Medium »
Enabling LLMs to acquire new knowledge after training remains a major hurdle for enterprise AI — current solutions are either too expensive, too slow, or constrained by context win...
Thinking Machines Lab — стартап бывшего технического директора OpenAI Миры Мурати — представил свою первую модель Inkling, к которой компания шла почти полтора года. Inkling — муль...
Image The main learning technique used to train a Large Language Model (LLM) is supervised learning. It is a machine learning technique where a mod...
Large language models continue to struggle with hallucinations, presenting a major roadblock for real-world enterprise applications. Reducing these errors is a messy business, forc...
In this post, we introduce Reverse Direct Preference Optimization (rDPO), the novel unlearning technique behind Amazon Nova Customizable Content Moderation Settings (CCMS), and sho...
Understanding how FPN allows deep learning models detecting small objects and how to implement it from scratch The post FPN Paper Walkthrough: Leveraging the Internal Pyramid appea...
I Came across this article by Kuriko Iwai on KL divergence in the context of LLM fine-tuning and thought it was worth sharing with the…Continue reading on Medium »
Всем привет, с вами Михаил Киселев, ML-разработчик в компании WebRise. И сегодня поговорим о практическом применении ML в образовании.Почему при горе регламентов, инструкций и мето...
Manual annotation is a massive bottleneck for multimodal inference systems in high-velocity production environments. If you want to survive catastrophic distribution shifts, you ha...
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