A practitioner's test of SimpleDesign 1.0 found the joint protein sequence-and-structure model fails when its sequence and structure latent spaces are not aligned, producing physically impossible "hal…
Shrijith Venkatramana, an engineer building LiveReview, explains how the Adam and AdamW optimizers became essential to modern LLM training. The post details how Adam, introduced in 2014 by Diederik Ki…
CMA-ES, invented by Nikolaus Hansen and Andreas Ostermeier and refined over three decades, is a standard black-box optimizer for problems where gradients do not exist, suffer from severe noise, or cos…
Researchers in the Philippines developed QHAdamW, a modified optimizer combining Quasi-Hyperbolic Momentum (QHAdam) and Adam with decoupled weight decay (AdamW), to train an artificial neural network …
A new open-source PyTorch optimizer, the Riemannian Thermodynamic Optimizer, outperforms Adam on non-linear benchmarks by treating loss landscapes as physical topologies with Landauer dissipation and …
In a technical explainer, the author demonstrates that L2 regularization and weight decay, equivalent in plain SGD, diverge under the Adam optimizer because Adam's adaptive step rescales the L2 penalt…
A developer built a tiny language model in pure Node.js with no dependencies, implementing tokenization, embeddings, causal Transformer blocks, and backpropagation from scratch. The model trains on si…
A guide explains that a neuron is a weighted sum followed by a non-linear activation, without which a deep network would be a linear regression. The training workflow consists of forward pass, loss ca…
A technical blog post explains that AdamW with warmup and cosine decay is the optimizer almost everyone uses today to train large language models, tracing the evolution from vanilla SGD through moment…
A new study on arXiv (2607.13246v1) finds that Muon, an optimizer that reshapes gradient updates through approximate orthogonalization and has outperformed Adam and AdamW in large language model train…
A new neural network optimization method using a symmetric-exponential weight reparameterization achieved up to 30% faster training on transformers, reaching equivalent validation loss in 1.32 to 1.49…
A researcher developed a physics-informed AI method that integrates a PDE residual into the training loop of a language model by using a differentiable numerical head, enabling the model to learn phys…
Researchers introduce Depth-wise Gradient Augmentation, a new optimization paradigm that transforms layer-wise updates to exploit structured relationships across deep neural network layers. Their inst…
A developer completed building an LSTM cell using PyTorch and Lightning AI, implementing the forward pass and optimizer. The LSTM unit processes stock price inputs over four days, updating long-term a…
A detailed breakdown of the PyTorch training loop reveals common placement errors that silently break training, such as moving the model to a device after optimizer creation or calling gradient clippi…
A developer implemented an LSTM from scratch using PyTorch and Lightning AI, detailing the initialization of weights and biases for the forget, input, cell candidate, and output gates. The tutorial us…
A new study on arXiv presents an experimental analysis of neural network-based image classification on the CIFAR-10 dataset, comparing fully connected and convolutional architectures. The convolutiona…
Adam, a YC W25 startup, launched CADAM, an open-source text-to-CAD web application that runs entirely in the browser. It uses LLMs to generate parametric OpenSCAD code, compiled via WebAssembly and re…
Adam, a Y Combinator W25 startup, launched CADAM, an open-source AI-powered CAD tool that generates parametric 3D models from natural language or images in a browser. The tool exports to STL, SCAD, an…
Developer Adam launched MangaBuilder, a new AI-powered tool for manga creators that maintains character and location consistency across panels. The tool integrates reference images directly into the p…