Contents# Introduction# 1. Lovable# 2. v0 by Vercel# 3. Replit# 4. OpenAI Codex# 5. MiniMax Code# Final Thoughts # Introduction  Have you ever thought, “If I had programming skills, I could launch my own startup or build the app idea I have been thinking about”? For many non-technical founders, creators, and professionals, the hardest part is not coming up with ideas. It …

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Limitations: Omni offers 10-second video generations currently, with longer durations coming soon. Uploading audio references and scene extension is not yet supported in the Gemini API for this model. Video references up to 3 seconds in duration are accepted by the API schema but are not correctly processed by the model at this time. Character …

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is a good way to test NLP models because it focuses not only on what a sentence says, but also on how it is written. Kaggle’s Spooky Author Identification competition is a compact version of this challenge: given a single sentence from gothic or horror fiction, the model has to predict whether it was written by Edgar Allan Poe (EAP), Mary Wollstonecraft Shelley …

How Far Can Classical NLP Go? From Bag-of-Words to Stacking on Spooky Author Identification Read More »

  Contents# Introduction# Prerequisites# Workflow 1: Automated Exploratory Data Analysis Agent# Workflow 2: Agentic Feature Engineering and Selection# Workflow 3: Agentic Hyperparameter Optimization# Workflow 4: Automated Model Monitoring and Drift Detection Agent# Workflow 5: Agentic Pipeline Orchestration and Self-Healing# Wrapping Up # Introduction  The average data scientist spends roughly 45% of their working time on data preparation and cleaning, not on modeling, not on …

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cut their AI inference bill by more than half last quarter. Eight weeks of clean engineering work. It was the win the engineering team had been chasing all year. It was also the wrong optimization. Three months later, customer satisfaction was dropping, churn was ticking up, and the cost savings were structurally tied to the …

We Built a Routing Layer to Cut Our AI Costs. It Broke the Product. Read More »

  Contents# Fine-Tuning Language Models on Apple Silicon with MLX# Understanding Why MLX Suits Apple Silicon# Setting Up Your Environment# Preparing Your Dataset# Training Your First LoRA Adapter# Choosing a Base Model and Adapter Settings# Reducing Memory Use with Quantization# Testing and Generating with Your Adapter# Fusing and Serving the Model# Wrapping Up # Fine-Tuning Language Models on Apple Silicon with MLX  Fine-tuning a language model …

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Making computer use safe in 3.5 Flash To mitigate some of the prompt injection risks for agents operating in live environments, we use targeted adversarial training for computer use in Gemini 3.5 Flash. We’re also releasing two optional enterprise safeguard systems that enable enterprises to: Require explicit user confirmation for sensitive or irreversible actions. Automatically …

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All code used in this article is available on GitHub. The business logic and modeling functions are located in the src/selection directory, specifically in the following file: src/modeling/score_computation.py The corresponding analysis and results are documented in: 09_score_computation.qmd The images, tables, and charts were generated with the help of the Codex coding assistant. , your credit score follows you …

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  Contents# Introduction# 1. Qwen3.6 27B MTP# 2. Gemma 4 31B IT QAT# 3. DiffusionGemma 26B A4B# 4. Nemotron Cascade 2 30B A3B# 5. Qwen3.5 9B MTP# 6. EXAONE 4.5 33B# 7. North Mini Code 1.0# Final Thoughts # Introduction  Local coding models are finally getting serious. I have been a big fan of this new wave of local large language models (LLMs), especially the …

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my series on Outlier Detection. In this article, we look at working with categorical data.  Generally when performing outlier detection with tabular data, we start by converting the data so that it is either entirely categorical or entirely numeric. There are some exceptions, but for the most part this is necessary: most outlier detection algorithms …

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