Artificial Intelligence

Olvídate de los frameworks de caja negra. Construye un agente de programación de IA de nivel profesional desde cero en Python puro — en la nube o local, probado con pytest, todo en un solo archivo.

ブラックボックスのフレームワークは不要。純粋なPythonでプロダクションレベルのAIコーディングエージェントをゼロから構築。クラウドでもローカルでも、pytestでテスト済み、すべて1つのファイルに収まります。

Build GPT-2, Llama 3, and DeepSeek from scratch in PyTorch. Every chapter has runnable end-to-end code and loads real pretrained weights. Goes well past where most LLM tutorials stop.

Go behind the scenes of the AI revolution in this definitive biography of OpenAI CEO Sam Altman. From his days as a restless Stanford dropout to the high-stakes boardroom battles that nearly toppled his empire, discover how one man is architecting the future of human intelligence. It is an essential look at the visionary holding the blueprint for the machines of tomorrow.

From a San Jose Denny’s booth to the apex of a three-trillion-dollar empire, witness the high-stakes gamble that transformed a niche graphics company into the indispensable backbone of the AI revolution. Explore the relentless "thirty-day mentality" of Jensen Huang, a leader whose journey through a Kentucky reform school and the "near-death" of his company forged the silicon engine of modern intelligence. This is the definitive chronicle of the architect who bet everything on the idea that the future of computing would be parallel.

Master Claude Code in Minutes

Код стал дешёвым, но сложность разработки никуда не исчезла — она сместилась в управление AI-агентами.

An AI system becomes an architecture problem when it can influence decisions, invoke tools, carry state or change the outside world. This practitioner playbook shows how to design Gen AI and Agentic AI systems that remain reliable, governable and defensible once they reach production.

AI is already your co-pilot. The question is whether you know how to fly with it. Flight Deck Medicine applies the proven safety frameworks of aviation — verification, trust calibration, situational awareness, confident override — to the daily realities of AI-augmented clinical practice. Through real case studies, integrated workbook exercises, and a structured five-phase curriculum, Dr. Rubin Pillay gives clinicians the cognitive tools to work safely, effectively, and defensibly alongside clinical AI. From reading a confidence score to executing an IDAR override to auditing an algorithm for racial bias, this is the definitive practical guide to being the pilot in command of modern medicine.

The fastest practical path to understanding harness-driven development as a complete system. Through clear visual diagrams and a real repository mapped to the book, you will see how a harness guides AI agents, evaluates their work, detects drift, enforces constraints, supports repair, and keeps software evolution visible, verifiable, and under control.

Your agent's dashboard is green. Your evaluators report an 87% pass rate. Then a customer complaint reveals the system has been confidently fabricating regulatory citations for three weeks. The evaluators weren't broken — they were measuring the wrong things. This field guide exists because the gap between "we have evals" and "our evals actually protect us" is larger than most teams realize.

A 1986 text adventure game written inside the Cray I/O Subsystem turns out to be architecturally isomorphic to modern transformer design. This capstone volume uses the playable game and its assembly language source as a case study in constraint-based design, including the bare metal thinking we stopped teaching around 1995.

What if time is not merely a clock, but a filter? What if systems fail not because they lack information, but because correction arrives too late to matter? What if technologies become dominant not because they are best, but because they have already reorganized the future around themselves? And what if Human–LLM collaboration is no longer just a sequence of prompts and answers, but an evolving ecology shaped by its own artifacts? Force–Information–Time: Essays on Structural Evolution is a companion volume to the FIT framework. Rather than restating the core theory, it explores what becomes visible when structural thinking is carried across learning, institutions, science, technology, Human–LLM collaboration, and human life.

Usar IA para programar es fácil. Usarla sin perder el control, no tanto. Spec-Driven Development es el método para convertir tu idea en una spec que la IA ejecuta con precisión — sin loops infinitos, sin código roto, sin empezar de cero.