Building better batteries with amorphous materials and machine learning
Lithium-ion batteries power most electronics, but they have limited energy density—they can store only a certain amount of energy per mass or volume of the battery.
I trained my first Qwen LoRA and I’m very surprised by it’s abilities!
LoRA was trained with Diffusion Pipe using the default settings on RunPod. submitted by /u/Hearmeman98 [link] [comments]
How to Choose the Right Gaming Laptop (2025): What You Need to Know
With over a decade of experience in reviewing gaming laptops, here’s my rundown of what to consider before pulling the trigger.
Quantum chips just proved they’re ready for the real world
Diraq has shown that its silicon-based quantum chips can maintain world-class accuracy even when mass-produced in semiconductor foundries. Achieving over 99% fidelity in two-qubit operations, the breakthrough clears a major hurdle toward utility-scale quantum computing. Silicon’s compatibility with existing chipmaking processes means building powerful quantum processors could become both cost-effective and scalable.
This was a satisfying peel
My GPU journey since I started for playing with AI stuff on my old gaming PC. RX5700XT -> 4070 -> 4090 -> 5090 -> this It’s gone from 8 minutes to generate a 512*512 image to <8 minutes to generate a short 1080p video. submitted by /u/legarth [link] [comments]
Factor Protein Plus Meals Review (2025): Filling, Not Fattening
After most of a week air-frying Factor’s delivery high-protein meals, I realize I could probably live like this.
Nano Banana vs QWEN Image Edit 2509 bf16/fp8/lightning
Here’s a comparison of Nano Banana and various versions of QWEN Image Edit 2509. You may be asking why Nano Banana is missing in some of these comparisons. Well, the answer is BLOCKED CONTENT, BLOCKED CONTENT, and BLOCKED CONTENT. I still feel this is a valid comparison as it really highlights how strict Nano Banana …
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Why and When to Use Sentence Embeddings Over Word Embeddings
Choosing the right text representation is a critical first step in any natural language processing (NLP) project.
Scaling Laws for Optimal Data Mixtures
Large foundation models are typically trained on data from multiple domains, with the data mixture—the proportion of each domain used—playing a critical role in model performance. The standard approach to selecting this mixture relies on trial and error, which becomes impractical for large-scale pretraining. We propose a systematic method to determine the optimal data mixture …
Building a Resilient Data Platform with Write-Ahead Log at Netflix
By Prudhviraj Karumanchi, Samuel Fu, Sriram Rangarajan, Vidhya Arvind, Yun Wang, John Lu Introduction Netflix operates at a massive scale, serving hundreds of millions of users with diverse content and features. Behind the scenes, ensuring data consistency, reliability, and efficient operations across various services presents a continuous challenge. At the heart of many critical functions lies …
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