'Before long, the world will wake up'

 

Leopold Aschenbrenner's 'Situational Awareness, the decade ahead Situational Awareness, the decade ahead. June 2024' may turn out to be the most significant publication on AI safety to date. Unlike a lot of theoretical musings from highly intelligent critics of AI systems this one has been written by an engineer, who was until recently employed by Open AI in the now disbanded former Super Alignment team. 

It begins by discussing the rapid advancements in AI technology, particularly focusing on the progression from GPT-2 to GPT-4 models. It highlights that AI capabilities are evolving at an exponential rate, and there are predictions that by 2027, AI models could match or even surpass the work of human AI researchers and engineers. The text underscores the importance of understanding the trendlines in compute, algorithmic efficiencies, and unlocking latent capabilities for future AI development. Additionally, the document mentions the potential risks and challenges associated with the rapid progression of AI technology, such as the need for enhanced security measures, the race for industrial mobilization in AI development, and ensuring alignment of AI systems with human values. It also touches on the implications of superintelligence, including economic and military advantages, as well as the importance of maintaining pre-eminence over authoritarian powers. It points towards a future where AI will play a central role, and the transformative impact it could have on society and national security.

The AI 'Scaling Implications' section discusses the concept of test-time compute overhang in AI models, specifically focusing on GPT-4tokens. The document mentions that GPT-4tokens are capable of thinking about problems but are limited in the number they can effectively use. It introduces a table equating the number of tokens to human-time spent on a problem/project. The text highlights the importance of allowing models to use more tokens for longer periods to improve capabilities significantly.

Furthermore, the document explores the idea of unlocking test-time compute to enhance the intelligence of models. It describes the need to teach models skills for longer-horizon reasoning and error correction to work on projects independently. The text suggests that small algorithmic wins could potentially help models utilise more test-time compute efficiently.

Additionally, the document outlines the potential progression from current AI models like ChatGPT to more advanced models that can function as drop-in remote workers. It discusses the implications of advanced AI models being able to automate cognitive jobs, potentially leading to AGI (Artificial General Intelligence) by 2027.

In conclusion, the text emphasizes the exponential progress in AI capabilities through the effective scaling of compute power and the importance of overcoming limitations to unlock the full potential of AI models. It also touches on the rapid pace of deep learning progress and the possibility of models surpassing human intelligence in the near future.

There is also an excellent YouTube video on Dwarkesh Patel's channel with Leopold, 'Leopold Aschenbrenner - 2027 AGI, China/US Super-Intelligence Race, & The Return of History'

It's four and a half hours long, so you'll need popcorn!

During my time (one year) absent from writing this blog I have spent it upgrading my PC system to a level I can run low scale LLM model experiments and helping develop AI policy documentation. I needed more practical knowledge of the system components: vector databases, RAG, embeddings and GraphRag outputs to name but a few. 

The 'advancements' in AI applications over this last year have appeared incremental, in the consumer space at least, rather than revolutionary. This has led many that are sceptical about AI to suggest we are in another bubble, and just like the big tech hype over Big Data a few years ago, that in reality saw no ROI and many million dollar companies go bust prior to Covid. 

I'd suggest that it's not the same, far from it, and 'before long, the world will wake up'.