LLM-based AGI: 50% on the ARC-AGI?
In the last few weeks, the ARC challenge by the legend Francois Chollet has made quite some noise. It is a challenge that has puzzled a lot of AI researchers, demonstrating the generalization incapabilities of all the AI systems out there. The last SOTA AI on ARC was around 34% and on the same challenge, Mechanical Turks performed around 85%.
But recently, there have been new claims of achieving 50% on this challenge. So, the big question is did we really somehow increase the generalization capabilities of our AI systems, or there is something else happening in the background?
Topics Covered
- How does ARC Define AGI?
- What is ARC-AGI?
- GPT-4o For Solving ARC
- Future Advancements
- Did We Really Solve ARC-AGI?
How does ARC Define AGI?
For computers to make progress toward more intelligent and human-like systems, we need to create systems with appropriate feedback mechanisms. But to do that first we need to define and evaluate intelligence.
These definitions and evaluations turn into benchmarks to measure progress toward systems that can think and invent alongside us.
