Understanding social interactions in complex real-world settings requires deep mental reasoning to infer the underlying mental states driving these interactions, known as the Theory of Mind (ToM). Social interactions are often multi-modal, involving actions, conversations, and past behaviors. For AI to effectively engage in human environments, it must grasp these mental states and their interrelations.…
Artificial intelligence (AI) has increasingly relied on vast and diverse datasets to train models. However, a major issue has arisen regarding these datasets’ transparency and legal compliance. Researchers and developers often use large-scale data without fully understanding its origins, proper attribution, or licensing terms. As AI continues to expand, these data transparency and licensing gaps…
Artificial intelligence, particularly the development of large language models (LLMs), has been rapidly advancing, focusing on improving these models’ reasoning capabilities. As AI systems are increasingly tasked with complex problem-solving, it is crucial that they not only generate accurate solutions but also possess the ability to evaluate and refine their outputs critically. This enhancement in…
Artificial intelligence (AI) has witnessed rapid advancements over the past decade, with significant strides in NLP, machine learning, and deep learning. Among the latest and most notable developments is the release of Llama-3.1-Storm-8B by Ashvini Kumar Jindal and team. This new AI model represents a considerable leap forward in language model capabilities, setting new benchmarks…
CausalLM has released miniG, a groundbreaking language model designed to bridge the gap between performance & efficiency. This innovative model stands out for its powerful capabilities and compact design, making advanced AI technology more accessible to a wider audience. As industries increasingly seek cost-effective and scalable AI solutions, miniG emerges as a transformative tool, setting…
The success of ANNs stems from mimicking simplified brain structures. Neuroscience reveals that neurons interact through various connectivity patterns, known as circuit motifs, which are crucial for processing information. However, most ANNs only model one or two such motifs, limiting their performance across different tasks—early ANNs, like multi-layer perceptrons, organized neurons into layers resembling synapses.…
Large Language Models (LLMs) have gained significant prominence in recent years, driving the need for efficient GPU utilization in machine learning tasks. However, researchers face a critical challenge in accurately assessing GPU performance. The commonly used metric, GPU Utilization, accessed through nvidia-smi or integrated observability tools, has proven to be an unreliable indicator of actual…