The paper also explores the idea that effective data compression could be a form of general intelligence, as both involve identifying patterns and making sense of complexity. The researchers argue that a good compression algorithm could be used to generate new data based on what it has learned during the compression process. While this theory is still a matter of debate, the paper provides an interesting perspective on potential new applications for large language models.
Key takeaways:
- DeepMind's large language model, Chinchilla 70B, has been found to perform effective lossless compression on image and audio data, often outperforming algorithms specifically designed for those tasks.
- Some computer scientists propose that the ability to compress data effectively is akin to a form of general intelligence, as it involves identifying patterns and making sense of complexity.
- The Hutter Prize, which rewards effective compression of a fixed set of English text, is seen as a demonstration of this idea, suggesting that a machine capable of such compression may exhibit a form of general intelligence.
- DeepMind researchers suggest that a good compression algorithm can be used to generate new, original data based on what it has learned during the compression process, further linking the concepts of compression and intelligence.