Every year, we have a new iPhone that claims to be faster and better in every way. And yes, these new computer vision models and new image sensors can exercise the phone as hard as they can. However, ...
Similar Articles (10 found)
π 69.6% similar
How We Cut Inference Costs from $46K to $7.5K Fine-Tuning Qwen-Image-Edit
Running quality inference at scale is something we think about a lot at Oxen...
π 66.3% similar
Deep Neural Nets: 33 years ago and 33 years from now
The Yann LeCun et al. (1989) paper Backpropagation Applied to Handwritten Zip Code Recognition is...
π 66.3% similar
Nano Banana Pro aka gemini-3-pro-image-preview is the best available image generation model
20th November 2025
Hot on the heels of Tuesdayβs Gemini 3 ...
π 65.3% similar
Writing an LLM from scratch, part 22 -- finally training our LLM!
This post wraps up my notes on chapter 5 of Sebastian Raschka's book "Build a Large ...
π 63.9% similar
https://medium.com/@mustafaakin/indexing-icloud-photos-with-ai-using-llava-and-pgvector-fd58182febf6
Indexing iCloud Photos with AI Using LLaVA and pgvector
A straightforward idea, gluing stuff together until it works, but itβs a glimpse of whatβs pos...
π 63.7% similar
Why DeepSeek is cheap at scale but expensive to run locally
Why is DeepSeek-V3 supposedly fast and cheap to serve at scale, but too slow and expensive...
π 63.1% similar
For some reason they focus on the inference, which is the computationally cheap part. If you're working on ML (as opposed to deploying someone else's ...
π 62.9% similar
I want everything local β no cloud, no remote code execution.
Thatβs what a friend said. That one-line requirement, albeit simple, would need multiple...
π 62.8% similar
Techniques for training large neural networks
Large neural networks are at the core of many recent advances in AI, but training them is a difficult en...
π 62.8% similar
Claude Opus 4.5, and why evaluating new LLMs is increasingly difficult
24th November 2025
Anthropic released Claude Opus 4.5 this morning, which they ...