Beyond Aha Moments: Structuring Reasoning in Large Language Models Large Reasoning Models (LRMs) like OpenAI’s o1 and o3, DeepSeek-R1, Grok 3.5, and Gemini 2.5 Pro exhibit strong capabilities in long Chain of Thought (CoT) reasoning. These models often demonstrate advanced behaviors such as self-correction, backtracking, and verification, collectively referred to as “aha moments.” Such behaviors… →
Anthropic Releases Claude Opus 4 and Claude Sonnet 4: A Technical Leap in Reasoning, Coding, and AI Agent Design Anthropic has announced the release of its next-generation language models: Claude Opus 4 and Claude Sonnet 4. This update marks significant technical refinements in the Claude model family, particularly in structured reasoning, software engineering, and autonomous… →
CONCLUSION: Epicardial catheter ablation was associated with a reduction in VF recurrence compared with ICD therapy alone. These findings support the use of epicardial ablation in high-risk BrS patients. →
CONCLUSION: Considering the high eradication success rate and low severity of adverse effects, tailored therapy based on DPO-PCR is preferable to concomitant therapy without resistance testing for the treatment of H. pylori infection. →
BACKGROUND: Seizures are common in patients with brain tumors, impacting daily life and healthcare burden. In contemporary neuro-oncology practice, levetiracetam is the most commonly prescribed anti-seizure medication (ASM). Although the practice is widely variable, levetiracetam is usually used for 2-3 years following surgery to prevent further seizures. However, the incidence of seizures post antitumoral treatment… →
CONCLUSION: The nomogram, based on four objective and easily assessed factors, demonstrates excellent predictive performance for pediatric postoperative pulmonary complications after one-lung ventilation, enabling early risk assessment and targeted interventions to improve patient outcomes. →
Reinforcement learning is a fundamental aspect of adaptive behaviour, since it involves the acquisition and updating of associations between actions and their outcomes based on the rewarding or punishing consequences. Acute experimental manipulations of serotonin have provided compelling evidence for its role in reinforcement learning. However, it remains unknown how more chronic manipulation of serotonin,… →
Technology Innovation Institute TII Releases Falcon-H1: Hybrid Transformer-SSM Language Models for Scalable, Multilingual, and Long-Context Understanding As language models scale, balancing expressivity, efficiency, and adaptability becomes increasingly challenging. Transformer architectures dominate due to their strong performance across a wide range of tasks but are computationally expensive—particularly for long-context scenarios—due to the quadratic complexity of self-attention.… →