Advancements in Language Model Alignment, AI’s Societal Risks, and Innovative Image Editing Techniques

Enhancing language model alignment through reward transformation and multi-objective optimization. OpenAI CEO warns about the dangers of societal misalignments in artificial intelligence. Apple AI research releases MLLM-guided image editing to enhance instruction-based image editing. This AI paper proposes two types of convolution to enhance the representation capacity of convolutional neural networks.

Sources:
https://www.marktechpost.com/2024/02/12/enhancing-language-model-alignment-through-reward-transformation-and-multi-objective-optimization/
https://apnews.com/article/uae-openai-sam-altman-artificial-intelligence-9593a03830c0ef83fdef76c68bb87118
https://www.marktechpost.com/2024/02/12/apple-ai-research-releases-mllm-guided-image-editing-mgie-to-enhance-instruction-based-image-editing-via-learning-to-produce-expressive-instructions/
https://www.marktechpost.com/2024/02/12/this-ai-paper-proposes-two-types-of-convolution-pixel-difference-convolution-pdc-and-binary-pixel-difference-convolution-bi-pdc-to-enhance-the-representation-capacity-of-convolutional-neural-net/

Outline:
(00:00:00) Introduction
(00:00:58) Enhancing Language Model Alignment through Reward Transformation and Multi-Objective Optimization
(00:04:11) OpenAI CEO warns that 'societal misalignments' could make artificial intelligence dangerous
(00:06:31) Apple AI Research Releases MLLM-Guided Image Editing (MGIE) to Enhance Instruction-based Image Editing via Learning to Produce Expressive Instructions
(00:09:54) This AI Paper Proposes Two Types of Convolution, Pixel Difference Convolution (PDC) and Binary Pixel Difference Convolution (Bi-PDC), to Enhance the Representation Capacity of Convolutional Neural Network CNNs