So I’ve been really doubling down on LoRA training lately, I find it fascinating and I’m currently training a realism LoRA for Qwen Image and I’m looking for some feedback. Happy to hear any feedback you might have *Consistent characters that appear in this gallery are generated with a character LoRA in the mix. submitted …
Companies hate to admit it, but the road to production-level AI deployment is littered with proof of concepts (PoCs) that go nowhere, or failed projects that never deliver on their goals. In certain domains, there’s little tolerance for iteration, especially in something like life sciences, when the AI application is facilitating new treatments to markets …
Read more “6 proven lessons from the AI projects that broke before they scaled”
Craving carb-y comfort? We picked our favorite outdoor ovens for backyards, countertops, or camping.
https://huggingface.co/vafipas663/Qwen-Edit-2509-Upscale-LoRA Long story short, I was waiting for someone to make a proper upscaler, because Magnific sucks in 2025; SUPIR was the worst invention ever; Flux is wonky, and Wan takes too much effort for me. I was looking for something that would give me crisp results, while preserving the image structure. Since nobody’s done …
AI coding, vibe coding and agentic swarm have made a dramatic and astonishing recent market entrance, with the AI Code Tools market valued at $4.8 billion and expected to grow at a 23% annual rate. Enterprises are grappling with AI coding agents and what do about expensive human coders. They don’t lack for advice. OpenAI’s …
Read more “What could possibly go wrong if an enterprise replaces all its engineers with AI?”
An experimental gene-editing therapy developed by Crispr Therapeutics is showing promise for treating heart disease.
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When we ask ourselves the question, ” what is inside machine learning systems? “, many of us picture frameworks and models that make predictions or perform tasks.
In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer. Unlike traditional methods, this algorithm is not based on temporal difference (TD) learning (which has scalability challenges), and scales well to long-horizon tasks. We can do Reinforcement Learning (RL) based on divide and conquer, instead of temporal …
What exactly does word2vec learn, and how? Answering this question amounts to understanding representation learning in a minimal yet interesting language modeling task. Despite the fact that word2vec is a well-known precursor to modern language models, for many years, researchers lacked a quantitative and predictive theory describing its learning process. In our new paper, we …