The article also highlights the industry's goal of achieving artificial general intelligence (AGI), AI demonstrating cognitive abilities on par with humans. While no model has convincingly beaten GPT-4 yet, there is potential for improvement with more parameters and AI processors. However, practical issues and potential limitations of transformers, the neural networks powering these models, may hinder the industry from reaching AGI.
Key takeaways:
- No AI model has convincingly surpassed OpenAI's GPT-4 since its release in March, raising questions about the potential for significant improvements in AI performance.
- Google's Gemini Ultra, an advanced AI model set to release next year, only slightly outperforms GPT-4 on performance benchmarks, and even falls behind on a commonsense reasoning benchmark.
- Transformers, the neural networks powering large language models (LLMs), theoretically perform better with more parameters and data, but practical limitations and potential inherent limitations of transformers may hinder progress towards artificial general intelligence (AGI).
- Technological developments like the world model, which would give transformers some capacity for reasoning, could potentially overcome these limitations, but such solutions are not yet ready for mainstream use.