Advanced economic modeling for antitrust and IP damages to strengthen outcomes in pharma, life sciences, and healthcare disputes.

What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...

Cybersecurity researchers have uncovered critical remote code execution vulnerabilities impacting major artificial intelligence (AI) inference engines, including those from Meta, Nvidia, Microsoft, ...

You train the model once, but you run it every day. Making sure your model has business context and guardrails to guarantee reliability is more valuable than fussing over LLMs. We’re years into the ...

Forbes contributors publish independent expert analyses and insights. Victor Dey is an analyst and writer covering AI and emerging tech. As OpenAI, Google, and other tech giants chase ever-larger ...

Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...

Background: Traditional congenital heart surgery quality assessments rely on indirect standardization via regression, which can be complicated by heterogeneity in case-mix, surgical volume, and low ...

Exposure to infections (for example, rubella), toxins (for example, lead, very high levels of alcohol), and certain medications (for example, thalidomide) in the womb adversely affects the developing ...

When you ask an artificial intelligence (AI) system to help you write a snappy social media post, you probably don’t mind if it takes a few seconds. If you want the AI to render an image or do some ...

Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...