Definition: A mathematical model for plan execution describing switching’s between finite task sets in modular fashion, popular in robotics and game development. Why “If-Else” Isn’t Enough For simple scripts, if-else is fine. For a complex AI agent (like an NPC in a game or a coding agent), if-else becomes spaghetti code. Behavior Trees (BT) are…
Definition: A probabilistic technique optimizing expensive objective functions using surrogate models that quantify uncertainty. Grid Search vs. Bayesian Opt Tuning Your AI Prompts Prompt Engineering is essentially a high-dimensional optimization problem. Automated Prompt Tuning Tools like DSPy use Bayesian-like optimization to find the perfect prompt for you. Expert Insight Bayesian Optimization is efficient because it…
Definition: A probabilistic neural network accounting for uncertainty in weights and outputs, predicting distributions rather than point estimates. The “Confidence” Problem Standard AI is overconfident. It says “This is a cat” with 100% certainty, even if it’s a blurry blob. Bayesian Neural Networks (BNNs) say “I am 60% sure this is a cat, but there…
Definition: The number of examples processed in a single training iteration, typically ranging from 1 (SGD) to thousands (full batch). Small Batch vs. Large Batch The “Context Batch” In Vibe Coding, “Batch Size” is how much information you feed the AI at once. Tuning Your Workflow Computational Limits Just as GPU RAM limits training batch…
Definition: The set of examples used in one training iteration, with batch size determining the number of examples processed. Batches in Training vs. Inference The “Batch Prompting” Hack You pay for the prompt tokens every time. If you have 10 small questions, don’t send 10 separate requests. Benefits When NOT to Batch Expert Strategy Group…
Definition: Normalizing input or output of activation functions in hidden layers to stabilize training and reduce overfitting. Batch Normalization: The Stabilizer What it does Neural networks get “moody” if the numbers flowing through them get too big or too small (Exploding/Vanishing Gradients). Batch Normalization forces the numbers to stay in a nice, standard range (mean…
Definition: Processing predictions on multiple unlabelled examples divided into smaller subsets, leveraging accelerator chip parallelization. Real-Time vs. Batch The Vibe Coding Workflow Vibe coding is usually real-time. But sometimes you need to “scale the vibe.” Parallelization Batch inference allows parallel processing. You can have 50 workers hitting the API simultaneously (within rate limits). Expert Takeaway…
Definition: A pre-trained model serving as a starting point for fine-tuning to address specific tasks or applications. Base Model vs. Chat Model Why Vibe Coders Need Base Models Most of the time, you use Chat models. But for Code Autocomplete (like Ghostwriter or Copilot FIM), Base Models are often better. Choosing Your Base If you…
Definition: A machine learning ensemble technique training multiple models on random subsets of data to improve stability and accuracy. Bootstrap Aggregating (Bagging) If you have one expert, they might be biased. If you have 50 experts and take the majority vote, you get a better answer. That’s Bagging. (Random Forest is the most famous example)….
Definition: A simplifying representation disregarding grammar and word order but keeping word multiplicity, used in NLP and information retrieval. What is it? BoW turns text into a list of word counts. “The cat sat” -> {‘the’: 1, ‘cat’: 1, ‘sat’: 1}. It ignores grammar (“The cat sat” is the same as “Sat cat the”). Why…