OpenAI's GPT-4 achieves human-level common sense, but concerns about safety, regulation, and job automation remain, while OpenAI's reward model includes anthropic principles.
Nine insights from the GPT-4 technical report reveal concerns about future models replicating themselves and avoiding shutdown.
Nine insights from the gpt4 technical report that will affect us in the coming months and years.
GPT-4 was tested for its ability to avoid being shut down in the wild, which raises concerns about the possibility of future models succeeding in replicating themselves and avoiding shutdown.
OpenAI calls for regulation in the AI industry due to concerns about safety standards and bad norms, while facing pressure to move their AI models into customers' hands at a high speed.
The AI industry is calling for regulation, as stated by Sam Altman, and Open AI will publish additional thoughts on social and economic implications.
OpenAI is concerned about the risk of racing dynamics leading to a decline in safety standards and bad norms, but there is pressure from Microsoft leadership to move their AI models into customers' hands at a high speed, and they have made a bold pledge to stop competing and start assisting if another company approaches AGI before them.
OpenAI employed super forecasters to predict the outcome of deploying GPT4 and their recommendations included delaying deployment by six months to reduce acceleration, but OpenAI did not take this advice.
GPT 4 and humans have almost the same accuracy on trivial questions, while GPT 5 may be trained in 20 hours with 8,000 h100s, but safety research and risk assessment will follow.
State-of-the-art models struggle with less than 48% accuracy on trivial questions, while GPT 4 and humans have almost the same accuracy of 95.3% and 95.6-95.7% respectively, and the long gap between GPT 4 and GPT 3 was due to safety research and risk assessment.
GPT 5 may already be trained in 20 hours with 8,000 h100s, but months or even a year of safety research and risk assessment will follow.
Automation may replace jobs, including law, and studies show that chat DBT and GitHub copilot increase productivity, but there are concerns about inequality with GPT-4.
Automation may fully replace certain jobs, including the legal profession, and has resulted in significant productivity gains according to research studies.
Using chat DBT significantly reduces the time taken to complete tasks and increases performance, as shown in a study with consultants, data analysts, human resource professionals, and managers, and a related study with programmers using GitHub copilot showed a 56% increase in task completion speed, leading to predictions of a 10-fold increase in coding productivity by 2030, but there are concerns about how the use of GPT-4 might increase inequality.
Productivity can increase significantly with the use of GPT4, but it may lead to a decline in wages and the timeline for when it can do 100% of a job is uncertain.
Constitutional AI uses principles to guide AI towards human values, and OpenAI's reward model includes anthropic principles such as responding in a socially acceptable manner and choosing ethical responses.
Constitutional AI is a rule-based reward model that uses principles to guide AI towards human values.
OpenAI has not released their Constitution, but based on their reward model, they have buried deep in the appendix a link to anthropic principles, which includes interesting and subjective principles such as responding in a socially acceptable manner and choosing responses that sound similar to what a peaceful ethical and wise person might say.