AI research

Here's how we get to superhuman AI, according to Meta's Yann LeCun

Matthias Bastian
An advanced 16:9 illustration, showing a super-intelligent AI system (AGI) that is warm, helpful, and inclusive towards all people, with a touch of sophistication. The AI should appear advanced but not overly business-like, maintaining a friendly and approachable demeanor. The design should be sleek and high-tech, with a subtle glitch effect to add character, but not too much to overpower the warmth and approachability of the AI. The interaction between the AI and diverse humans should be depicted as collaborative and positive, with the AI presented through a modern interface or hologram in an inviting and inclusive setting.

DALL-E 3 prompted by THE DECODER

Meta AI chief scientist Yann LeCun outlines a step-by-step approach to achieving general AI. According to LeCun, the development of superhuman AI will not be a sudden event, but a gradual process with several phases.

Phase 1: Learning how the world works

LeCun believes that the first step toward AGI will be to create systems that can learn how the world works, much like baby animals. These systems should be able to observe and learn from their environment, which will lay the foundation for more advanced AI capabilities.

LeCun is working on a new brain-like AI architecture that aims to overcome the limitations of current systems, such as hallucinations and logical weaknesses, by grounding them more firmly in the real world.

He sees this as a necessary step in the evolution of AI. Today's language models like GPT-4 or Gemini and their focus on textual data aren't enough, LeCun has said in the past. OpenAI CEO Sam Altman recently echoed that sentiment.

Phase 2: Objective-driven systems with guardrails

According to LeCun, the next stage of AI development will be machines that are driven by goals and operate within certain guard rails. These guard rails will ensure that AI systems remain safe and controllable while pursuing their goals.

Phase 3: Planning and reasoning

As AI systems mature, they develop the ability to plan and reason to achieve their goals and adhere to defined guardrails. This enables AI systems to make more informed decisions and take appropriate actions based on their understanding of the world.

Phase 4: Hierarchical planning

LeCun envisions that future AI systems will be able to plan hierarchically, further improving their decision-making capabilities. This should enable AI systems to handle complex tasks and problems more efficiently.

Phase 5: Increasing machine intelligence

Initially, AI systems will have an intelligence comparable to that of a mouse or a rat. However, as AI evolves, these systems will be scaled up to an intelligence level equivalent to that of a dog or a crow. During this process, guardrails will be adjusted to ensure that AI systems remain controllable and safe.

Phase 6: More training and fine-tuning

Once AI systems have reached a certain level of intelligence, they are trained in different environments and tasks. This makes them more versatile and able to handle different challenges. After this training, they are fine-tuned to excel at specific tasks.

Stage 7: Superhuman AI is here

LeCun believes that one day we will realize that the AI systems we develop are smarter than humans in almost all areas.

This does not mean that these systems will have feelings or consciousness. But they will be able to do their tasks better than humans. LeCun recently estimated that this "clearly" won't happen in the next five years.

These advanced AI systems must remain under human control, even if they are intellectually superior to humans, LeCun says.

He also recently provided a plausible argument for why this might work: AI does not have the natural drive to dominate that humans do.

Without this dominance drive, AI might willingly serve a class that is intellectually inferior to it. According to LeCun, intelligence and dominance drive have nothing to do with each other.

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