Safeguarding the ethics and safety of large language models (LLMs) is key to ensuring their use doesn't result in harmful or offensive content. In examining why these models sometimes generate unacceptable text, researchers have discovered that they lack reliable refusal capabilities. Consequently, this paper explores ways in which LLMs can deny certain content types and…
Factory AI has unveiled Code Droid, a major innovation in artificial intelligence (AI) designed to streamline and expedite software development processes. As an autonomous AI tool, Code Droid is created to handle a multitude of coding duties based on natural language instructions, assimilating insights from multiple fields, including robotics, machine learning, and cognitive science.
The key…
Factory AI has launched its state-of-the-art innovation, Code Droid. This artificial intelligence (AI) tool is designed to revolutionize software development by mechanizing and quickening the processes involved. Code Droid is essentially an autonomous system which carries out multiple coding tasks dependent on natural language directions. Its main objective is to automatize mundane programming operations, thus…
The rise of vast data systems has made information retrieval a vital process for numerous platforms, including search engines and recommender systems. This is achieved by finding documents based on their content, a task that presents challenges related to relevance assessment, document ranking, and efficiency. A new Python library named BM25S aims to overcome the…
In the digital era where data is vast, the importance of information retrieval cannot be overstated, particularly for search engines, recommender systems, and applications that find documents based on their content. Information retrieval involves three fundamental challenges - relevance assessment, document ranking, and efficiency. BM25S is a recently introduced Python library that tackles these challenges…
Long-Context Language Models (LCLMs) have emerged as a new frontier in artificial intelligence with the potential to handle complex tasks and applications without needing intricate pipelines that were traditionally used due to the limitations of context length. Unfortunately, their evaluation and development have been fraught with challenges. Most evaluations rely on synthetic tasks with fixed-length…
Advancements in vision-language models (VLMs) have enabled the possibility of developing a fully autonomous Artificial Intelligence (AI) assistant that can perform daily computer tasks through natural language. However, just having the reasoning and common-sense abilities doesn't always lead to intelligent assistant behavior. Thus, a method to translate pre-training abilities into practical AI agents is crucial.…
Policymakers usually depend on coarse-resolution global climate models to assess a community's risk of extreme weather. By looking decades and even centuries into the future, these models can predict large-scale weather patterns but struggle to provide specific data for smaller locations. To estimate the risk of an area such as Boston experiencing extreme weather events…
Large Language Models (LLMs) have revolutionized natural language processing, with considerable performance across various benchmarks and practical applications. However, these models also have their own sets of challenges, primarily due to the autoregressive training paradigm which they rely upon. The sequential nature of autoregressive token generation can drastically slow down processing speeds, limiting their practicality…
Researchers from the OATML group at the University of Oxford have developed a statistical method to improve the reliability of large language models (LLMs) such as ChatGPT and Gemini. This method looks to mitigate the issues of "hallucinations," wherein the model generates false or unsupported information, and "confabulations," where the model provides arbitrary or incorrect…