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Machine Learning

Small Language Models (SLMs): The Future of Efficient AI

Discover why Small Language Models (SLMs) are revolutionizing AI with their efficiency, sustainability, and real-world applications. Learn how models like Qwen and Phi are outperforming larger counterparts while reducing costs and environmental impact.

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Machine Learning

Predictive Mental Health: AI Models Forecasting Outcomes

Predictive mental-health diagnostics use machine learning to forecast treatment outcomes and detect conditions like depression early. This post examines the algorithms, research results, applications and ethical considerations.

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Quantum Computing

Quantum Machine Learning: Hybrid Algorithms Powering the Next AI Leap

Explore hybrid quantum‑classical algorithms that combine classical pre‑training with quantum subroutines to power new AI models, reducing energy use while enabling applications across manufacturing, drug discovery, finance and logistics.

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Quantum Computing

Quantum Chemistry Simulations: Molecules on Quantum Computers

Quantum chemistry simulations use hybrid algorithms like AFQMC to model molecular forces accurately. This post explores IonQ’s 2‑million‑qubit roadmap, error mitigation, and applications in drug discovery and carbon capture.

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Quantum Computing

Quantum Sensors and Biomedical Innovation: Measuring the Invisible

Quantum sensors like optically pumped magnetometers and NV centres detect magnetic fields and temperatures at unprecedented resolution, enabling wearable MEG and cellular magnetometry while raising ethical questions about neural data.

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Machine Learning

Wearable Mental Health Monitoring: Passive Sensing & AI

Discover how passive sensing with wearables monitors heart rate, movement and sleep, enabling AI models to detect depression and anxiety with over 92% accuracy while raising privacy concerns.

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