Automating deep learning experiments with agentic AI
A practical way to stop babysitting deep learning runs: containerize your training script, add a health-check sidecar, and let an agent handle restarts and hyperparameter tweaks.
Category: AI
Is the AI and Data Job Market actually dying?
Layoffs dominate the headlines, but the data tells a different story: senior hiring keeps growing while roles fragment into analyst, ML engineer, and infrastructure tracks.
Gemini object detection instead of training a custom model
Gemini’s open-vocabulary detection removes the label-thousands-of-images step from a vision pipeline. Notes on structured JSON output with Pydantic, editing detected regions with Nano Banana, and the rate limits that show up in production.
How to define an internal credit risk model modeling scope
Ahmad Wael walks through how to define an internal credit risk model modeling scope: building the (ID x Year) dataset, avoiding temporal overlaps, and meeting ECB standards for PD, EAD, and LGD.
Gradient accumulation before you buy more GPUs
Getting a larger effective batch size out of the GPUs you already have: gradient accumulation in a PyTorch loop, DDP with no_sync(), why the loss has to be scaled, and the bucket size and data loading settings that decide whether scaling stays linear.
Policy matching optimization instead of round-robin
Round-robin lead assignment ignores capacity, licensing and expertise, and a transient counter invites race conditions. A look at running the match as a linear program in PuLP outside WordPress, split into a batch mode and an online mode.
How aliasing in audio breaks your digital signal processing
Aliasing happens when digital sampling can’t keep up with a signal, folding high frequencies into false, lower ones. Covers the Nyquist-Shannon theorem, the “Wagon Wheel” effect, and fixing downsampling with anti-aliasing filters in PHP and FFmpeg.
WordPress AI Assistant is now built into WordPress.com
WordPress.com built its new AI Assistant directly into the block editor and Media Library. It edits blocks and generates images with Google’s Gemini models, though full layout control needs a Block Theme.
Causal reasoning models behind Nvidia’s AlpamayoR1
A read of Nvidia’s AlpamayoR1: the Cosmos-Reason backbone, the joint action-reasoning token space that keeps an explanation tied to the steering, GRPO post-training, and why benchmarks run on Nvidia’s own datasets are hard to trust.
PySpark for Pandas users: getting past the RAM wall
Pandas keeps the whole dataset in RAM and computes as you type. PySpark builds a plan first and runs it across a cluster. Here is what that changes for loading data, window functions, and the shuffle settings nobody tunes.