January 2026

Author(s): Shashwata Bhattacharjee Originally published on Towards AI. The headline writes itself: AI defeats human doctors in medical diagnosis, delivering results in under two seconds versus 13 minutes. But beneath this dramatic 390x speed differential lies a far more nuanced story about specialized model architecture, the evolving role of clinical decision support systems, and the critical distinction between diagnostic speed and comprehensive patient care. The Technical Architecture Behind the Victory Shanghai AI Lab’s Gastrointestinal Multimodal AI represents a […]

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Improving the reasoning abilities of Large Language Models (LLMs) has been a continuous topic recently. But most relevant works are based on outcome rewards at the trajectory level, missing fine-grained supervision during the reasoning process. Other existing training frameworks that try to combine process signals together to optimize LLMs also rely heavily on tedious additional steps like MCTS, training a separate reward model, etc., doing harm to the training efficiency. Moreover, the intuition behind the process signals design […]

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My problem is such: I have to use the cpu to train my agent , so running 1600 steps per episode on bipedalwalker, half cheetah etc is out of the question. Are 200 steps fine as a starter point ( assuming the agent can get a score 300 for 1600 steps, that would set the score at 37.5 for 200 steps) so if the agent is able to get to 40 score then for testing I could just […]

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Climate prediction is a challenge due to the intricate spatiotemporal patterns within Earth systems. Global climate indices, such as the El Niño Southern Oscillation, are standard input features for long-term rainfall prediction. However, a significant gap persists regarding local-scale indices capable of improving predictive accuracy in specific regions of Thailand. This paper introduces a novel NorthEast monsoon climate index calculated from sea surface temperature to reflect the climatology of the boreal winter monsoon. To optimise the calculated areas […]

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Climate prediction is a challenge due to the intricate spatiotemporal patterns within Earth systems. Global climate indices, such as the El Niño Southern Oscillation, are standard input features for long-term rainfall prediction. However, a significant gap persists regarding local-scale indices capable of improving predictive accuracy in specific regions of Thailand. This paper introduces a novel NorthEast monsoon climate index calculated from sea surface temperature to reflect the climatology of the boreal winter monsoon. To optimise the calculated areas […]

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The effectiveness of contrastive learning methods has been widely recognized in the field of graph learning, especially in contexts where graph data often lack labels or are difficult to label. However, the application of these methods to node classification tasks still faces a number of challenges. First, existing data enhancement techniques may lead to significant differences from the original view when generating new views, which may weaken the relevance of the view and affect the efficiency of model […]

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The cost of downtime isn’t just lost revenue. For most companies, it’s a combination of cloud spend spikes, engineering time, customer trust, and contractual fallout—all hitting at once. That’s why CFOs increasingly look at outages through two complementary lenses: business risk preparedness and global employee continuity. Joe Cronin, President of International Citizens Insurance, notes that resilience is not only an infrastructure conversation—especially for globally distributed companies. “For global teams, resilience isn’t just infrastructure; it’s people. If key employees […]

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