Machine Learning

How Do I Make Sure My Math Work Is Not Eaten By AI

How Do I Make Sure My Math Work Is Not Eaten By AI

someone at work brings up a version of this question: will AI take my job? I will admit that I…
25 years of the invention of visual search

25 years of the invention of visual search

Both updates build on 25 years of innovation to make the world's visual information more quickly accessible and usable. To…
A Gentle Introduction to Autoencoders & Hidden Space

A Gentle Introduction to Autoencoders & Hidden Space

Hard computation is a well-known problem in various ML algorithms today, especially when generative AI is applied to text, images,…
Kubiza Malini Ngempela Ukuqalisa I-LLM Yasendaweni? (Ama-Euro ngeMillion Tokens, Kukaliwe)

Kubiza Malini Ngempela Ukuqalisa I-LLM Yasendaweni? (Ama-Euro ngeMillion Tokens, Kukaliwe)

ngakho empeleni kumahhala.” Sengikushilo lokho, mhlawumbe ukushilo lokho, futhi wuhlobo lwesimangalo oluzwakala luyiqiniso kuze kube yilapho umuntu esilinganisa. Ngakho ngayilinganisa.…
Pydantic + OpenAI: The Cleanest Way to Get Systematic Results from LLMs

Pydantic + OpenAI: The Cleanest Way to Get Systematic Results from LLMs

In my latest post on edited output, there are three main ways to get machine-readable answers in LLM. Those are…
Agent RAG: Let Agent Search

Agent RAG: Let Agent Search

the constructive application is the RAG application. The recipe is simple: chunk, embed, extract, and turn. It looks clean on…
Context Rot: Why Claude Code Sessions Decay, and How to Govern Them

Context Rot: Why Claude Code Sessions Decay, and How to Govern Them

The context window is a core feature of every frontier model. Measured in tokens, it is typically made up of…
Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

Two response variables that look identical and aren’t , the thing I was trying to predict was a survey answer:…
The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices

The Three Dimensions of Custom Agentic Alignment: Purpose, Principles and Practices

are rapidly moving from experimental prototypes to embedded actors across industries, government operations, and everyday digital workflows. Their accelerating capabilities,…
Back to top button