Levels/Types of Artificial Intelligence

If an AGI learns to change its own goals, is it still under our control?

Bible is 100% true. Then Jesus is 100% Lord.

Should AGI learn ethics from philosophers… or from humanity’s behavior online? Think about that for a second.

In history ?

Multi-agent systems are training grounds for AGI. When AIs negotiate, plan, and coordinate — that’s intelligence emerging through interaction.

“Reviewing Artificial General Intelligence (AGI): Implications for the Workforce Key takeaway: In a rapidly evolving AI landscape, adaptability and continual learning are not optional 🔗 https://t.co/9flP4HWuo2”

AGI = Multi-Modal + Memory + Autonomy To reach AGI, models need 3 things: 🧠 Long-term memory 👁️ Multi-modal understanding ⚙️ Autonomous reasoning loops We’re getting closer.

AGI = Understanding, Not Just Output GPT can generate text. AGI would truly comprehend it. That’s the line we’re still trying to cross.

AI is evolving fast, and each level changes everything: 1️⃣ Narrow AI — task specialists 2️⃣ Human-Level AI — human-like learning and reasoning 3️⃣ Superintelligence — exceeding human capability

AI vs AGI — Know the Difference Most AIs today are narrow: they master one skill. AGI would understand, reason, and adapt across domains — like a human mind.

Every trade is a move in a global game of incentives. Game theory explains why markets behave like living organisms—strategic, reactive, and unpredictable. Add Quantum AI to that, and you get algorithms that can think in many possible futures at once.

Imagine backtesting years of market data… in seconds. Quantum Trading AI could make ultra-fast scenario testing and portfolio optimization a reality. This tech won’t replace traders — it will redefine them.

Classical computers read one market path at a time. Quantum computers can analyze thousands simultaneously. That’s why Quantum AI could outperform even the most advanced trading bots — it doesn’t just calculate, it entangles probabilities.

Quantum + AI = Next-Gen Trading We’re entering an era where algorithms don’t just predict—they superposition possibilities. Quantum Trading AI blends physics, data, and machine learning to simulate multiple market realities at once.

Which LLM is the best trader? Well, this is being put to the test in Alpha Arena — a competition running until November 3. Watch live here: https://t.co/S9FWcmHoOZ

Concerns about machines eliminating jobs are centuries old... The story is never simple: Machines take over some human tasks but they also make us more productive, more employable, and help companies grow profits to pay higher wages. Progress is a paradox. 🤖💼

The goal of Google DeepMind is quite shocking: “First, solve AI. Then use AI to solve everything else.” - Demis Hassabis A simple sentence yet it carries world-changing ambition. 🌍🤖

The main professional societies for AI are: 1️⃣ AAAI 2️⃣ SIGAI 3️⃣ AISB Anyone knows what these abbreviations stand for? 👇

A comprehensive history of AI is given by Nils Nilsson (2009), one of the early pioneers of the field. Pedro Domingos (2015) and Melanie Mitchell (2019) give overviews of machine learning for a general audience, and Kai-Fu Lee (2018) describes the race for international race.