After King Charles disclosed his recent cancer diagnosis, Buckingham Palace warns it may resort to legal action against the publication of artificial intelligence (AI) generated books on Amazon, which falsely claim insider insight on the king’s health status. These publications not only inaccurately disclose details about his medical condition but also speculate on his treatments.
Midjourney, a frontrunner in AI image-generation, is discussing a full prohibition on AI-generated pictures of Joe Biden and Donald Trump as the 2024 US elections approach. The move seeks to prevent the platform from being used as a medium for disseminating false information ahead of the polls. David Holz, CEO of Midjourney, openly expressed his
The Federal Communications Commission (FCC) has declared the use of AI-generated voices in robocalls to consumers as illegal. This decision follows a recent event where a clone of President Biden’s voice was used in a robocall discouraging individuals from voting in the New Hampshire primaries. Even though an ongoing criminal investigation is in progress regarding
Abu Dhabi-based artificial intelligence company G42 has divested from several Chinese entities, including TikTok’s parent company, ByteDance. This move is aimed at avoiding critique from the United States due to G42’s associations with Chinese businesses. 42XFund, G42’s technology investment branch, has confirmed the full withdrawal of its investments in China, which reportedly amount to around
The scalability of Graph Transformers in graph sequence modeling is hindered by high computational costs: a challenge that existing attention sparsification methods are not fully addressing. While models like Mamba, a state space model (SSM), are successful in long-range sequential data modeling, their application to non-sequential graph data is a complex task. Many sequence models
Large language models (LLMs) have proven beneficial across various tasks and scenarios. However, their evaluation process is riddled with complexities, primarily due to the lack of sufficient benchmarks and the required significant human input. Therefore, researchers urgently need innovative solutions to assess the capabilities of LLMs in all situations accurately. Many techniques primarily lean on
Python project dependency management can often be challenging, especially when working with both Python and non-Python packages. This issue can give rise to confusion and inefficiencies due to the juggling of multiple dependency files. UniDep, a versatile tool, was designed to simplify and streamline Python dependency management. It has proven to be significantly useful for
Recent developments have focused on creating practical and powerful models applicable in different contexts. The narrative primarily revolves around striking a balance between the creation of expansive language models capable of comprehending and generating human language, and the practicality of deploying these models effectively in resource-limited environments. The problem is even more acute when these
Large Vision-Language Models (LVLMs), which interpret visual data and create corresponding text descriptions, represent a significant advancement toward enabling machines to perceive and describe the world like humans do. However, a primary challenge obstructing their widespread use is the occurrence of hallucinations, where there is a disconnect between the visual data and the generated text,
Advancements in large language models (LLMs) are making strides in the field of automated computer code generation in artificial intelligence (AI). These sophisticated models are proficient in creating code snippets from natural language instructions due to extensive training on large datasets of programming languages. However, challenges remain in aligning these models with the intricate needs
Optical flow estimation, a key aspect of computer vision, enables the prediction of per-pixel motion between sequential images. It is used to drive advances in various applications ranging from action recognition and video interpolation, to autonomous navigation and object tracking systems. Traditionally, advancements in this area are driven by more complex models aimed at achieving
Large Language Models (LLMs) like ChatGPT and Llama have performed impressively in numerous Artificial Intelligence (AI) applications, demonstrating proficiency in tasks such as question answering, text summarization, and content generation. Despite their advancements, concerns about their misuse, in propagating false information and abetting illegal activities, persist. To mitigate these, researchers are committed to incorporating alignment