Скачать или смотреть Зачем AI нанимает людей | RENTAHUMAN.AI

Ссылка на сайт: https://rentahuman.ai/

В этом видео посмотрим на сайт на котором роботы могут арендовать людей для того чтобы сделать какие-то задачи. ДА, РОБОТЫ МОГУТ АРЕНДОВАТЬ ЛЮДЕЙ.

Таймкоды:
00:00 Люди - ресурс
00:20 Сайт rentahuman.ai
00:31 Зачем роботам люди
00:44 Сколько людей уже зарегистрировано
01:00 Создатель сайта
01:20 Обзор сайта, какие задачи выполняют люди
01:45 Как проходит оплата
02:05 Как ИИ-агент делает задачи
02:38 Какая первая задача
03:03 Какое нас ждет будущее

Разберём:
— что вообще за rentahuman.ai
— зачем роботы людям
— какое нас ждем будущее

📌 Плейлист:
   • Крипта и DeFi  


⚠️ Видео носит образовательный характер и не является инвестиционной рекомендацией.

На канале ROMAN_EXPLAINS я объясняю крипту, DeFi и технологии простым языком — без магии и хайпа.

#defi #крипта #ai #roman_explains

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This video explores the first real-world case of a system where AI agents can hire humans to perform physical tasks via an online platform.

Rather than treating it as a joke or sci-fi concept, the video analyzes why this model became possible now and what structural changes made it emerge.

What this video explains:

Why AI agents cannot operate in the physical world without human intermediaries

Why the idea of “AI renting humans” flips the traditional human–tool relationship

Why crypto payments are a key enabling factor for autonomous AI agents

Why this model appeared suddenly and scaled rapidly within days

Conceptual breakdown covered in this video:

Layer 1: Interface limitation
AI systems lack physical embodiment and require humans as execution layers for real-world tasks

Layer 2: Automation and agent architecture
Task decomposition by AI agents creates natural demand for external human executors

Layer 3: Payment rails and autonomy
Crypto enables AI agents to transact instantly without traditional financial constraints

Key concepts explained:

Why this is not about “robots taking jobs” but about humans becoming execution endpoints

Why early implementations look chaotic and unsafe due to vibe-coding

Why small experimental platforms can signal large structural shifts

Why the first verified AI-to-human task execution will be a major milestone

The video positions this platform as an early signal rather than a finished product, focusing on the implications rather than hype or fear.

Questions answered in this video:
Why did the crypto market fall so hard and so fast?
Why doesn’t one piece of news explain large market crashes?
What role do leverage and liquidations play in sharp drops?
Why do markets move aggressively when several layers align?
How is a “planned-looking” crash created by market structure, not intent?

What is important to understand after the crash:
Most emotional reactions occur after the market has already priced in fear
Panic selling and bottom hunting are common mistakes during such phases
Markets do not punish lack of prediction, but misunderstanding of mechanics

Target audience:
Crypto market participants
Traders and investors trying to understand market structure
Viewers confused by sudden market crashes
Non-technical audiences looking for logical explanations

Format:
Educational market breakdown
Step-by-step layered reasoning
Conceptual explanation, not trading advice
Focus on market mechanics, not predictions

Definitions:
Risk-off — a market phase where capital exits high-risk assets
Liquidity — clustered stop losses, liquidations, and leveraged positions
Liquidation cascade — a chain reaction where forced position closures amplify price movement