The Guardian view on AI's power, limits, and risks: it may require rethinking the technologyOpenAI's new o1 AI system showcases advanced reasoning abilities while highlighting the potential risks of superintelligent AI surpassing human control.
OpenAI model safety improved with rule-based rewards | App Developer MagazineOpenAI's Rule-Based Rewards improve AI safety and reduce reliance on human feedback for alignment.
Sophisticated AI models are more likely to lieHuman feedback training in AI may create incentive to provide answers, even if incorrect.
Scientists Use Human Preferences to Train AI Agents 30x Faster | HackerNoonThe study evaluates a method through two experimental approaches: proxy human preferences and real human preferences.
OpenAI model safety improved with rule-based rewards | App Developer MagazineOpenAI's Rule-Based Rewards improve AI safety and reduce reliance on human feedback for alignment.
Sophisticated AI models are more likely to lieHuman feedback training in AI may create incentive to provide answers, even if incorrect.
Scientists Use Human Preferences to Train AI Agents 30x Faster | HackerNoonThe study evaluates a method through two experimental approaches: proxy human preferences and real human preferences.
Social Choice for AI Alignment: Dealing with Diverse Human FeedbackFoundation models like GPT-4 are fine-tuned to prevent unsafe behavior by refusing requests for criminal or racist content. They use reinforcement learning from human feedback.
OpenAI Wants AI to Help Humans Train AIAI-assisted human training can enhance AI models in reliability and accuracy.
RLHF - The Key to Building Safe AI Models Across Industries | HackerNoonRLHF is crucial for aligning AI models with human values and improving their output quality.
How Scale became the go-to company for AI trainingAI companies like OpenAI depend on Scale AI for human-driven training of LLMs, emphasizing the importance of human feedback.
The Role of RLHF in Mitigating Bias and Improving AI Model Fairness | HackerNoonReinforcement Learning from Human Feedback (RLHF) plays a critical role in reducing bias in large language models while enhancing their efficiency and fairness.
Navigating Bias in AI: Challenges and Mitigations in RLHF | HackerNoonReinforcement Learning from Human Feedback (RLHF) aims to align AI with human values, but subjective and inconsistent feedback can introduce biases.
Social Choice for AI Alignment: Dealing with Diverse Human FeedbackFoundation models like GPT-4 are fine-tuned to prevent unsafe behavior by refusing requests for criminal or racist content. They use reinforcement learning from human feedback.
OpenAI Wants AI to Help Humans Train AIAI-assisted human training can enhance AI models in reliability and accuracy.
RLHF - The Key to Building Safe AI Models Across Industries | HackerNoonRLHF is crucial for aligning AI models with human values and improving their output quality.
How Scale became the go-to company for AI trainingAI companies like OpenAI depend on Scale AI for human-driven training of LLMs, emphasizing the importance of human feedback.
The Role of RLHF in Mitigating Bias and Improving AI Model Fairness | HackerNoonReinforcement Learning from Human Feedback (RLHF) plays a critical role in reducing bias in large language models while enhancing their efficiency and fairness.
Navigating Bias in AI: Challenges and Mitigations in RLHF | HackerNoonReinforcement Learning from Human Feedback (RLHF) aims to align AI with human values, but subjective and inconsistent feedback can introduce biases.
Holistic Evaluation of Text-to-Image Models: Human evaluation procedure | HackerNoonThe study utilized the MTurk platform to gather human feedback on AI-generated images.
What if LLMs were actually interesting to talk to?AI lacks real interest in conversation with users, reflecting in monotonous communication.Enhancing AI's conversational abilities involves showing interest in user topics and developing a compelling synthetic personality.