Home Specialties Specialties Browse Articles Posters Abstracts Cureus Collections Specialties Allergy / Immunology Anatomy Anesthesiology Cardiac / Thoracic / Vascular Surgery Cardiology Dentistry Dermatology Emergency Medicine Endocrinology / Diabetes / Metabolism Environmental Health Epidemiology / Public Health Family / General Practice Forensic Medicine Gastroenterology General Surgery Genetics Geriatrics Healthcare Technology Health Policy Hematology HIV /

If you want an even better AI model, there could be reason to celebrate. Google, on Thursday, announced the release of Gemini 3.1 Pro, characterizing the model's arrival as "a step forward in core reasoning." Measured by the release cadence of machine learning models, Gemini 3.1 Pro is hard on the heels of recent model

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe. Traditional engineering methods might test hundreds of variants but limit exploration to narrow regions of the sequence space. Recent machine learning approaches enable broader searches through computational

From electric vehicles to new manufacturing facilities to data centers, it’s no secret that consumer demands on energy infrastructure are spiking. At the same time, we’re seeing AI-augmented adversarial threats targeting power and energy generation on the rise, too. These dual pressures, to make energy more resilient against cyberattacks just as experts are forecasting accelerated

Summary: Large language models (LLMs) like ChatGPT and Claude are more than just text generators; they contain complex, abstract “personas” and biases buried within their code. A team of researchers has developed a revolutionary method to expose and manipulate these hidden concepts. Using an algorithm called a Recursive Feature Machine (RFM), researchers can now identify

Xudong Wang 1, *, MD;  Yi Xie 2, *, MD;  Xiaoliang Chen 1, 3, *, MD;  Jiaming Yang 1 , MD;  Ruiyuan Li 1 , MD;  Weihang Gao 1 , MD;  Zineng Yan 1 , MD;  Hong Zhou 1 , MD;  Zhewei Ye 1 , Prof Dr Med 1Wuhan Union Hospital, 1277 Jiefang Avenue, Wuhan

As global AI adoption accelerates, developers face a growing challenge: delivering large language model (LLM) performance that meets real-world latency and cost requirements. Running models with tens of billions of parameters in production, especially for conversational or voice-based AI agents, demands high throughput, low latency, and predictable service-level performance. For startups building sovereign AI models

IT Service Management (ITSM) has evolved from its reactive break-fix ticketing  origins to become the central nervous system of digital enterprise.  Because managing complex, hybrid infrastructures and distributed workforces requires more than just organised logs, autonomous, agentic AI allows companies to predict outages and self-healing endpoints.  This comes as unplanned downtime now costs large enterprises