93 stories
Understanding how words become related in a learned vector space The post How Do Word Embeddings Capture Relationships Between Words? appeared first on Towards Data Science.
Deep learning is not a single library command that turns data into intelligence. A useful model depends on the problem definition, data quality, mathematical assumptions, architecture, training loop, evaluation, deployment and monitoring.
Stop generating labels; read decisions from the model.Continue reading on Towards AI »
From demystifying the online softmax trick to hitting a 41.6x speedup on an NVIDIA RTX 4050 GPU — a beginner’s hands-on journey into hardware-aware deep learning.
A one-line formula for how often an LLM's top token flips, and why identical completions fall apart after about a hundred tokens The post Why Temperature 0 Isn't Deterministic appeared first on Towards Data Science.
I ran the forged New Yorker cartoons through OpenAI’s verification tool. All three carry a second, invisible signature: OpenAI’s.Continue reading on Towards AI »
A diffusion head for probabilistic time series forecasting: why a forecast can get the mean and the variance right and still describe a future that never happens, and how to fix it. The post Your Model's MSE Is Lying to You III: Time Series Diffusion appeared first on Towards Data Science.
I put a physics-informed neural network up against a plain finite-difference solver twice: once in 1D and once in 5D. The winner changed. The post When Do PINNs Beat Classical Numerical Methods? A 1D vs 5D Experiment appeared first on Towards Data Science.
Meta has open-sourced Rebalancer, the C++ and Python library it has used for over 9 years to place shards, servers and traffic. It handles about 40 million assignment problems a day, using local search or MIP solvers like Gurobi, FICO Xpress and HiGHS. It is pip-installable under Apache 2.0.
Google DeepMind's EmbeddingGemma 2 maps 5 input types into one 768d space and ships today under Apache 2.0. The post Google DeepMind Releases EmbeddingGemma 2, a 740M Open Multimodal Embedding Model Built on Gemma 4 appeared first on MarkTechPost.
Cantina Security, with Yeta Labs, has released apex-flash-1, an open-weights model trained specifically for vulnerability research. It is a reinforcement learning fine-tune of Z.ai’s GLM-5.3-Flash, released on Hugging Face under the MIT license. Is it deployable?
A model can recall a fact in the direction it learned it and fail in the other. Here's a toy version of why The post The Reversal Curse: Why a Language Model That Knows “A Is B” Can’t Tell You “B Is A” appeared first on Towards Data Science.
A forger, a detective, and a game that never ends: the full, friendly guide to how two neural networks compete to produce data that never existed before.
A from-scratch PyTorch build that recovers blood flow, viscosity, and wall shear stress in a narrowed artery from 40 noisy velocity readings The post How to Use a PINN for a Navier-Stokes Inverse Problem appeared first on Towards Data Science.
Prime Intellect has launched Prime Inference, an OpenAI-compatible platform for serving frontier open models on NVIDIA Blackwell. Its GLM-5.3 deployment uses Dynamo, vLLM and NVFP4 KV compression to serve 66 sessions per prefill group at 101 tok/s per user.
Convolutional Neural Networks Explained: How AI Understands Images How a network goes from a grid of raw numbers to “that’s a cat”. Introduction So far in this series we’ve worked with …
Why Neural Networks Overfit: Regularization, Dropout, and Early Stopping Explained Why does a model ace its training data and then stumble on anything new? Introduction Neural networks learn patterns …
NVIDIA announced a new 64GB configuration of DGX Spark — from Acer, ASUS, Dell, Gigabyte, HP and MSI — its GB10-powered desktop AI system. It gives developers a way to start with one system for local models and agents, then cluster two 64GB units for 128GB of memory across the cluster and more…
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