The health industry is seeing increased patient disengagement, driving organizations to adopt non-traditional care settings and technology. A blog discusses top healthcare use cases, including improved patient experience through AI chatbots, predictive analytics to avoid unnecessary medication or surgery, dementia detection using an iPhone, and early heart disease detection using AI algorithms and wearable devices.…

Microsoft partnered with AFL-CIO to address concerns about AI’s impact on American workers. The initiative seeks to inform and involve labor leaders and workers in AI development, influence public policy, and prioritize worker skills. Amid AI’s potential to replace jobs, the partnership aims to ensure AI augments and creates more jobs than it replaces.

Recent advancements in 2D picture production have been remarkable, especially in enhancing text-to-image creation. New methods aim to distill 3D knowledge from pre-trained large text-to-image generative models rather than training a large text-to-3D generative model from scratch. The MVControl network has been designed to enable fine-grain controlled text-to-multi-view picture generation and 3D asset production.

Artificial Intelligence (AI) is revolutionizing pain assessment in the medical and veterinary fields, offering solutions to address the limitations of conventional methods. Researchers have developed the Feline Grimace Scale (FGS), a reliable tool for assessing acute pain in cats, integrating deep neural networks and machine learning models for predictive accuracy. This advancement may enhance the…

OpenAI’s ChatGPT-4 model has been deemed ‘lazy’ by users, sparking concerns about the future of AI. Despite OpenAI’s acknowledgment of the issue and speculation about internal safety mechanisms causing the behavior, the setback presents an opportunity for researchers to advance AI development. This highlights the challenges and importance of continuous learning in AI.

The release of smaller, more efficient AI models like Mistral’s Mixtral 8x7B has sparked interest in “Mixture of Experts” (MoE) and “Sparsity.” MoE breaks models into specialized “experts,” reducing training time and enhancing speed. Sparsity involves reducing active elements in a model, leading to less computational intensity and lower storage needs. These concepts are shaping…

LLMs like NexusRaven-V2 can interpret natural language instructions to generate code snippets, including function calls, benefiting developers by providing real-time assistance and guiding correct function invocation. The open-source model outperforms GPT-4 in function calling success rates and offers utility artifacts for seamless integration into software workflows. Nexusflow aims to advance open-source models for copilots and…

Recent advancements in auto-regressive language modeling have propelled conversational AI agents to new heights. Despite the benefits of large language models, caution is advised due to potential dangers. New input-output safeguarding tools, such as Llama Guard, aim to mitigate risks and promote responsible use of generative AI models. Purple Llama project will compile resources and…

Numerical weather prediction (NWP) models have drawbacks, prompting interest in data-driven, deep learning-based weather forecasting methods. Recent advancements include Stormer, a scalable transformer model, developed by researchers from UCLA and CMU. Stormer surpasses current techniques in accuracy for medium-range weather forecasting, outperforming Pangu-Weather and Graphcast, particularly for longer lead times. (Words: 50)

Researchers from Google DeepMind, Stanford University, and University of California, Berkeley have developed Chain of Code (CoC) to enhance code-driven reasoning of language models (LMs). CoC leverages pseudocode to improve reasoning and simulation capabilities, achieving state-of-the-art performance and broader scope of problem-solving. The approach combines advantages of code and LM’s knowledge. [50 words]