Johnny Devriese

The Big Three Trap: Why Open Weights Are Squeezing Closed AI Labs The competitive landscape in AI is changing faster than many expected.

RoPE Is Just a Clock with a Thousand Hands *A visual guide to Rotary Position Embeddings.

The Functional Analysis of DeepSeek-V4: Bounding Operators at 1.6 Trillion Parameters When DeepSeek-V4 dropped, most of the attention went to the replacement of Multi-head Latent Attention (MLA) with sequence-level compression.

The Selection Effect _On benchmarks, compression, and what counts as a principle_ --- Rich Sutton's _Bitter Lesson_ is routinely cited as the organizing truth of modern AI — seventy years of history distilled into a single directive, presented as something

Building Enterprise Agents That Actually Work Over the past year our team built an agentic system for enterprise financial workflows — invoice extraction, lease parsing, payment matching, analytics.

Prompting vs.

The GenAI Inversion: Building the Map After You Have the Engine In traditional data science, the workflow is linear.

Deconstructing DeepSeek's Engine: A Physicist's Guide to GRPO The release of DeepSeek-R1-Zero energized the AI community, demonstrating that massive reasoning capabilities can be unlocked using pure reinforcement learning—without the crutch of sophisticat…

Understanding Large Language Models: A Mental Model for Software Engineers The fundamental insight An LLM is a machine that reads text and predicts what comes next.

Glucose Buddy: Turning an AI Agent into a Real Product Last year I wrote about building an AI agent for glucose tracking.

The Shannon Problem: Why We Need a Mathematics of Neural Networks In 1937, Claude Shannon was a master's student at MIT working on a theoretical problem that seemed narrow and academic: could you describe electrical circuits using algebra?

The Librarian in the Machine: Retrieval, Generation, and the Search for Truth An LLM can sound like it has read everything while still failing to remember anything specific.

The Loop Unwound: How Deep Networks Are Just Optimized Algorithms in Disguise Hey there, fellow travelers on the AI frontier!

Building an AI Agent for Glucose Tracking The Promise of Agentic AI in Healthcare AI agents are useful when a model needs to do more than produce text.

Learning curves are plots that show how model performance changes as you add more training data.

Adaptive Bayesian Scanning Algorithms for AESA Radar Systems **Author:** Johnny Devriese --- Abstract Traditional Active Electronically Scanned Array (AESA) radar systems often employ linear or predetermined scanning patterns that, while effective in many…

My macOS Setup This is my current macOS development setup that I've refined over the years to maximize productivity and maintain a clean workflow.

Decision Trees (CART) Decision trees are defined by recursively partitioning the input space, and defining a local model in each resulting region of input space.

Computation graphs MLPs are a simple kind of DNN in which each layer feeds directly into the next, forming a chain structure, as shown in Figure 13.10.

Mathematics of Deep Neural Nets Neural Nets are defined by a **learning function** $F(x,v)$ where the **weights** are $x$ and the **training data** are $v$.

Searching for the Higgs Boson # The Standard Model is a theory in particle physics that describes some of the most basic forces of nature.

Introduction and Setup This notebook utilizes a CycleGAN architecture to add Monet-style to photos.

TPU or GPU detection Competition data access TPUs read data directly from Google Cloud Storage (GCS).

var3: nationality of the customer Add feature that counts the number of zeros in a row num_var4 : number of bank products Var38 var38 is important according to XGBOOST see https://www.kaggle.com/cast42/santander-customer-satisfaction/xgboost-with-early-st…

We need a separation of concerns when building an API.

Introduction The old way of doing authentication is for you to manage an authentication server that issues credentials for your partners.

I was looking into the often posed question of how to solve the Fibonacci sequence in .

PostgreSQL is like therapy after trying to wrangle Cassandra for years!

What is a data lake and why is everyone talking about it?

I've spent a load of time learning about botht the internals of Spark as well as learning about Pyspark for analytics.

Learning about components and managing state with redux.

very good answer: https://stackoverflow.com/questions/286141/remove-blank-attributes-from-an-object-in-javascript Need to think about this one that uses recursion.

Sometimes you might just want to merge and accept the master branch (or whomevers) changes because you know they will overrule you no matter what.

You should probably be a normal human being and use the SDK, but one day I was tasked with figuring this out.

Pretty slick, for JS.

This is some half baked code that we copy/pasted the variables around.

This takes a placeholder image in src tag and then we replace it with the actual data-src.

Getting a taste of the power of Functional Programming.

Interesting thoughts from /u/drawkbox that sort of remind me of the 'The Zen of Python'. --- "Programmers with lots of hours of maintaining code eventually evolve to return early, sorting exit conditions at top and meat of the methods at the bottom.

"With jQuery, you can chain together actions/methods.

This will only work on more modern browsers!

Avoid the callback triangle of doom with three simple rules: 1. keep your code shallow 2. modularize 3. handle every single error example:

Coming From Python this felt a little funny since Python has so many nice features for looking up keys and setting defaults etc.

You need to be careful becasue if in your pathURL argument you have a relative path (something like ../..

Despite the directions in the google drive they don't actually work because wants a file which doesn't get created when we do: .

Turns out it's not good to instantiate an array by using: .

**Problem**: json_encode() returns FALSE.

Training a Tiger is no simple task.