Stability is open-sourcing Stable Video Diffusion and an image-to-video model, for research purposes.
Comprehensive benchmarks show Orca 2 significantly outperforming other models of equivalent size on metrics related to language understanding, common sense reasoning, multi-step math problems, reading comprehension, summarization, and more.
Building on their prior work in image and video generation, these models showcase impressive capabilities in high-quality, diffusion-based text-to-video generation and controlled image editing using text instructions.
NVIDIA researchers customized LLaMA by training it on 24 billion tokens derived from internal documents, code, and other textual data related to chip design.
New research shows that even though these models may know what's factual, they may still produce responses that appease user beliefs, sometimes at the expense of accuracy.
The breakthroughs aim to enable real-world collaborative robots and augmented reality assistants.
What sets SteerLM apart is the user's ability to adjust attributes at the time of inference allowing for real-time tailoring to specific needs, not just predetermined ones.
Batch Calibration refines in-context learning, and effectively tackles many of its biases while delivering state-of-the-art performance and unprecedented robustness.
The model achieved up to 72% accuracy in a zero-shot evaluation on the United States Medical Licensing Examination (USMLE), and outperforms OpenAI's ChatGPT 3.5.
The system offers a novel approach to training machine learning models that power various accessibility, testing, and design tools for app developers.
The Llama Impact Grants program seeks to identify and support compelling applications of Llama 2 that provide social benefits across the globe.
A diverse research ecosystem is essential to realizing the promise of AI. AFMR aims to expand access to powerful models, engaging academics outside of computer science to pursue a broad range of important opportunities.
In a recently published paper in Science, it was revealed that AlphaMissense had classified a staggering 89% of all possible missense variants — illuminating the pathogenic or benign nature of these mutations.
The innovative approach, called Diffusion Policy, allows robots to acquire new dexterous behaviors, such as peeling vegetables or flipping pancakes, in just a few hours.
The high-performance computing cluster will feature over 1,000 Graphics Processing Units to facilitate the development of AI and large language models for biomedicine at an unprecedented scale.
Applications include turning still images into seamlessly looping dynamic videos, or allowing users to realistically interact with objects in photos.
The model offers a promising concept for developing adaptable, generalist vision models. By mimicking how humans process images, it points towards more universal and flexible AI to handle diverse vision challenges.
It outperforms Llama 2, demonstrates abilities on par with closed models like PaLM 2 Large (despite being just half its size), and ranks just below GPT-4.
BELEBELE represents the largest parallel multilingual benchmark ever created specifically for reading comprehension.
By opening up DINOv2 under a more permissive license and introducing FACET for fairness benchmarking, Meta is setting a positive example for responsible AI development.
Not only does the implant use Ann's brain signals to generate speech, but it also animates a digital avatar with facial expressions, mimicking the natural nuances of human communication.
This study could herald a new era in robotics, enabling anyone to easily teach robots an array of new skills simply by explaining it to them.
The project represents Meta's endeavor to create a unified multilingual system capable of catering to all language translation needs.
Dolma is significantly larger than other open datasets and is released under AI2’s impact license, which was designed to balance ease of access with mitigation of potential risk in distributing large datasets.