Artificial Intelligence
Artificial Intelligence in Healthcare Artificial intelligence (AI) is revolutionizing healthcare by leveraging advanced computational techniques for diagnostics and treatment planning. Large language models (LLMs) are emerging as powerful tools for parsing complex medical data, promising to transform patient care and research. Research in Healthcare AI Existing research includes models like Meditron 70B, MedAlpaca, BioGPT, and…
Boston Dynamics Electric Atlas: Revolutionizing Industrial Automation A Decade of Innovation Boston Dynamics has been a leader in robotics for over a decade, and the new electric Atlas robot represents a major advancement in the field. With a strong partnership with Hyundai, the electric Atlas is set to transform real-world applications across industries. Enhanced Capabilities…
Practical AI Solution: Gradformer Integrating Graph Transformers with Inductive Bias Gradformer, a novel method, integrates Graph Transformers (GTs) with inductive bias by applying an exponential decay mask to the attention matrix. This innovative approach effectively guides the learning process within the self-attention framework, leading to state-of-the-art results on various datasets. Key Achievements of Gradformer Achieved…
Introducing the ‘gpt2-chatbot’: A New Era in AI Artificial intelligence is evolving rapidly, with the emergence of the cutting-edge AI model, ‘gpt2-chatbot’, causing a stir in the AI community. This large language model (LLM) has garnered attention for its impressive reasoning abilities and proficiency in handling complex questions. Early reports suggest that ‘gpt2-chatbot’ has surpassed…
OpenBioLLM-Llama3-70B & 8B: Revolutionizing Medical AI Discover the groundbreaking OpenBioLLM-Llama3-70B & 8B models, which are transforming medical natural language processing (NLP) with their state-of-the-art Large Language Models (LLMs). Key Advancements The release of these models sets new standards for functionality and performance in the biomedical field, outperforming existing models in biomedical tasks and demonstrating superior…
“Sleep staging for diagnosing sleep disorders is crucial but challenging to scale due to the need for clinical expertise. Deep learning models can help, but require large labeled datasets. Self-supervised learning (SSL) can reduce this need, but recent studies indicate performance plateaus after training with data from only tens of subjects, falling short of larger…
Neural knowledge-to-text generation models sometimes struggle to accurately describe input facts, leading to contradictions or adding false information. To combat this, a new decoding method called TWEAK (Think While Effectively Articulating Knowledge) has been proposed. TWEAK treats generated sequences as hypotheses and ranks them based on how well they support input facts using a Hypothesis…