EmpathyZeroed

Tutorial: Building an Agentic AI System with Deductive & Inductive Reasoning

1. Introduction

Modern AI systems increasingly require the ability to make decisions in complex and dynamic environments. One promising approach is to create an agentic AI system that combines:

Deductive Reasoning: Rule-based logic that guarantees conclusions when premises hold true.
Inductive Reasoning: Data-driven inference that generalizes from specific cases to handle uncertainty.

By integrating these two methods, often referred to as neuro-symbolic AI, an agent can provide transparent, explainable decisions while also adapting to new data. This tutorial explains the concepts behind this approach and shows you how to build an edge-deployable ReAct agent using Deno.

DeepSeek R1 Distill: Complete Tutorial for Deployment & Fine-Tuning

This guide shows how to deploy an uncensored DeepSeek R1 Distill model to Google Cloud Run with GPU support and how to perform a basic, functional fine-tuning process. The tutorial is split into:

Environment Setup
FastAPI Inference Server
Docker Configuration
Google Cloud Run Deployment
Fine-Tuning Pipeline (Cold Start, Reasoning RL, Data Collection, Final RL Phase)

	# SPARC Agentic Development Rules

	Core Philosophy

	1. Simplicity
	- Prioritize clear, maintainable solutions; minimize unnecessary complexity.

	2. Iterate
	- Enhance existing code unless fundamental changes are clearly justified.

	#ifndef PATCHLESS_AMSI_H
	#define PATCHLESS_AMSI_H

	#include <windows.h>

	static const int AMSI_RESULT_CLEAN = 0;

	PVOID g_amsiScanBufferPtr = nullptr;

	unsigned long long setBits(unsigned long long dw, int lowBit, int bits, unsigned long long newValue) {