The Path to AI Transformation

Conclusion First Giants are pouring $300 million in salaries just to capture your precious last minute of daily attention and clicks. Generative AI pretends to release productivity while secretly creating sellable leisure time. GPU prices have skyrocketed, becoming a new currency, and computing power futures allow bubbles and profits to dance together today. Attention is now exhausted; even sleep, the final bastion, is openly priced beneath the sky by commercial algorithms. If you don’t price...

A Note from the Translator The essence of “Vibe Coding” is rapidly accumulating technical debt at the speed of AI. AI programming is a double-edged sword: it’s a fantastic tool for prototyping, but when used for long-term maintenance of core projects, it can signal the beginning of a disaster. Allowing non-technical individuals to develop core products with AI is akin to giving a child a credit card with no limit—what seems glamorous in the moment can lead to endless debt in the future. The k...

Translator’s Note Model “distillation” is not absolutely safe: seemingly harmless training data might actually convey hidden biases or even malice from the “teacher model.” To prevent AI “subliminal” contamination, the simplest strategy is to use “heterogeneous teaching”: ensure that the “student model”, fine-tuned from different architectures than the “teacher model” generating the data, is utilized. AI safety requires looking beyond surface behavior; it demands an in-depth investigation of ...

Conclusion First The future divide in the workplace won’t be about “using AI” but whether you “control AI” or “are controlled by AI.” The biggest risk of AI is not job loss, but rather the slow “outsourcing” of our cognitive abilities, leading to cognitive decline. Don’t see AI as an “outsourced worker” to get tasks done; view it as a “sparring partner” to stimulate your thinking. Every question should be a deep dialogue you lead. The core competency in the AI era: when faced with AI outputs,...

Introduction 💡 The parameters of large models are like horsepower in a car—sufficient power is the best configuration. 🎯 7B for everyday tasks, 13B for business applications, 70B for specialized needs, and 175B for defining the future. ⚡ A database is like using a dictionary, while a large model is like having a writer at your disposal—these solutions tackle fundamentally different problems. 🔥 In the realm of AI, the most expensive element isn’t computational power; it’s the opportunity co...

Introduction: Embracing the AI Revolution in Content Creation Imagine AI crafting detailed reports in minutes – would you still dedicate hours to manual writing? AI excels at complex tasks, freeing up your valuable time. Would you trust AI to make crucial decisions for you? If AI could identify issues faster and predict outcomes more accurately, would you fully embrace its judgment? How can we transform AI from a vague advisor into a powerful ally? Let’s explore how to truly harness AI’...

A Forward-Thinking Query: AI, Do You Really Have Awareness? Do you believe AI is intelligent enough to replace human decision-making? Does it truly understand the essence of issues, or is it just playing a clever game of semantics? When AI provides a “perfect” answer, have you considered that it might just be a sophisticated reassembly of extensive data? Has AI made your decisions faster and more accurate? Are you perhaps using seemingly objective data to rationalize your subjective biases?...

Introduction Can AI truly distinguish between reality and fiction? Would you feel like crawling into a hole if your AI assistant quoted a fabricated legal precedent during a crucial meeting? Are we ready to bear the consequences of AI’s errors? When an AI “diagnosis” could turn doctors into “killers” in an instant, how much can we trust its advice? Can we completely eliminate AI hallucinations? Could technology advance to a point where human supervision is unnecessary? Or will humans al...

Introduction Have you heard that AI charges by Token? It really consumes a lot of Tokens. My computer ran all night, and it ate up a lot of Tokens — does that feel like losing an apartment? Why use Tokens for billing? I’ve heard that Token charges are two-way. Asking AI a question costs money, and getting an answer does too. Isn’t that a bit excessive? So AI can’t stop rambling, can it? Are Tokens words or letters? How do they bill for Chinese characters? What about Arabic? What differe...