🔬 Training Transformers to solve 95% failure rate of Cancer Trials — Ron Alfa & Daniel Bear, Noetik
Researchers Ron Alfa and Daniel Bear from Noetik are exploring the use of Transformers to address the high failure rate of cancer trials, which currently stands at 95%. Their work aims to enhance the predictive capabilities of AI in clinical settings, potentially improving the success rates of cancer treatments.
More in Research
Reinforcement fine-tuning with LLM-as-a-judge
AWS just introduced reinforcement fine-tuning using LLMs as judges. This approach enhances model training by leveraging feedback from large language models, improving overall performance and adaptability in various tasks.
Researchers find AI text is making the internet more uniform and weirdly cheerful
A recent study reveals that AI-generated text is contributing to a more uniform and oddly optimistic tone across the internet. Researchers suggest that this trend could impact the diversity of online content and the way information is communicated. The findings highlight the influence of AI on digital communication and its potential implications for creativity and expression.
[AINews] ImageGen is on the Path to AGI
ImageGen is making significant strides towards achieving Artificial General Intelligence (AGI) by enhancing its image generation capabilities. The development focuses on creating more sophisticated and context-aware visual outputs, which could revolutionize various applications in AI. This progress highlights the ongoing efforts in the AI community to bridge the gap between narrow AI and AGI.
Physical AI that Moves the World — Qasar Younis & Peter Ludwig, Applied Intuition
The article discusses the advancements in physical AI technologies as explored by Qasar Younis and Peter Ludwig from Applied Intuition. They emphasize the potential of AI to revolutionize various industries by enabling machines to interact with the physical world more effectively. The conversation highlights the importance of developing robust AI systems that can navigate and manipulate real-world environments.