The State of AGI Research at the End of 2023

Advancements in Artificial General Intelligence (AGI) in 2023 have been marked by significant strides, though the goal of achieving AGI, a level of AI that equals or surpasses human intelligence across all domains, remains elusive.

Google's Gemini:

Google introduced Gemini, a generative AI model developed by Google Brain and DeepMind. Unlike existing AI models, Gemini is multimodal from its inception, integrating capabilities across text, images, video, audio, and code. While Gemini has demonstrated impressive capabilities, surpassing ChatGPT in world knowledge and problem-solving on certain benchmarks, it's still debated whether it signifies a step towards AGI. Experts like Yejin Choi from the University of Washington and the Allen Institute for AI (AI2) caution against prematurely claiming AGI achievement based on promotional materials alone​​.

Historical Context and Recent Progress:

The journey towards AGI dates back to the 1940s, starting with simple neural models and evolving over decades with breakthroughs in deep learning and the support of large companies like Google, Microsoft, and Facebook. The advancement of neural networks, which saw significant strides in the 2000s, enabled more complex applications in various fields. For instance, neural networks have surpassed human capabilities in areas like medical diagnostics and artistic creation​​.

Risks and Opportunities:

The rise of AGI presents both risks and opportunities. There are concerns about job displacement in various sectors due to AI's ability to perform tasks traditionally done by humans. However, history shows that technology also creates new job opportunities. Ethical considerations, particularly in scenarios where AI decisions have significant consequences, are also a key area of concern​​​​.

Predictions and Challenges:

Experts have predicted that the singularity, a point where machines match or exceed human intelligence across all activities, could be reached around 2030, based on the exponential growth of AI capabilities. Despite this, current AI models have limitations that need addressing, particularly in safety-critical systems. Issues like unpredictability in novel situations, vulnerability to adversarial attacks, and regulatory challenges might delay the actualization of AGI​​.

OpenAI's Superalignment Team:

OpenAI's superalignment team focuses on ensuring that future AI models, especially those with superhuman capabilities, are aligned with human intentions and safety. They experiment with supervisory techniques where less powerful models like GPT-2 guide more powerful ones like GPT-4. While promising, this approach highlights the challenges in aligning AI models that may possess emergent abilities beyond current understanding​​​​​​.

The pursuit of AGI in 2023 has seen remarkable progress, but challenges in technological advancement, ethical considerations, and safety alignment remain. The field is evolving rapidly, with ongoing research and experimentation shaping the future of AI and its societal impact.