Skip to content Skip to sidebar Skip to footer

Author page: admin

NVIDIA AI Releases Describe Anything 3B: A Multimodal LLM for Fine-Grained Image and Video Captioning

Challenges in Localized Captioning for Vision-Language Models Describing specific regions within images or videos remains a persistent challenge in vision-language modeling. While general-purpose vision-language models (VLMs) perform well at generating global captions, they often fall short in producing detailed, region-specific descriptions. These limitations are amplified in video data, where models must account for temporal…

Read More

Researchers at Physical Intelligence Introduce π-0.5: A New AI Framework for Real-Time Adaptive Intelligence in Physical Systems

Designing intelligent systems that function reliably in dynamic physical environments remains one of the more difficult frontiers in AI. While significant advances have been made in perception and planning within simulated or controlled contexts, the real world is noisy, unpredictable, and resistant to abstraction. Traditional AI systems often rely on high-level representations detached from their…

Read More

Government Funding Graph RAG

In this article, I present my latest open-source project — Government Funding Graph. The inspiration for this project came from a desire to make better tooling for grant writing, namely to suggest research topics, funding bodies, research institutions, and researchers. I have made Innovate UK grant applications in the past, so I have had an interest in…

Read More

Meta AI Released the Perception Language Model (PLM): An Open and Reproducible Vision-Language Model to Tackle Challenging Visual Recognition Tasks

Despite rapid advances in vision-language modeling, much of the progress in this field has been shaped by models trained on proprietary datasets, often relying on distillation from closed-source systems. This reliance creates barriers to scientific transparency and reproducibility, particularly for tasks involving fine-grained image and video understanding. Benchmark performance may reflect the training data and…

Read More

This AI Paper Introduces an LLM+FOON Framework: A Graph-Validated Approach for Robotic Cooking Task Planning from Video Instructions

Robots are increasingly being developed for home environments, specifically to enable them to perform daily activities like cooking. These tasks involve a combination of visual interpretation, manipulation, and decision-making across a series of actions. Cooking, in particular, is complex for robots due to the diversity in utensils, varying visual perspectives, and frequent omissions of intermediate…

Read More