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Documentation Index

Fetch the complete documentation index at: https://docs.nyc-ai.app/llms.txt

Use this file to discover all available pages before exploring further.

Empire AI is framed around “AI for the public good,” so the best way to understand the platform is to look at the kinds of projects it supports. The source materials you provided span healthcare, climate, education, neuroscience, and model safety.

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Healthcare and biomedical research

Empire AI is already being used for several medically significant workloads:
  • Drug and molecular discovery: The planning brief highlights work led by Dr. Thomas Grant on computational chemistry and drug-development workflows that would otherwise take much longer to iterate.
  • Malaria and immunology: Prof. Rabindra K. Mandal at CUNY is using large-scale genomic and biological datasets to study how the gut microbiome shapes immune response to malaria.
  • Lung cancer detection: Ge Wang and collaborators at RPI are building multitask AI systems that combine CT scans with clinical records to improve early detection and risk assessment.
  • Prostate cancer subtype detection: Ekta Khurana at Weill Cornell Medicine is training models on pathology imagery to identify aggressive and treatment-resistant prostate cancer subtypes earlier.
  • AI-generated radiology fraud detection: The planning brief also cites work by Tanvi Ranga, Nalini Ratha, and Arjun Ramesh Kaushik on models that detect synthetic or manipulated radiology reports.
  • HIV and antibody mapping: The broader research portfolio includes viral protein and antibody-focused work intended to improve adaptive treatment strategies.

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Climate, energy, and environmental modeling

The project portfolio is not limited to medicine. The planning materials describe climate-oriented workloads such as:
  • physics-informed AI for hyper-local weather prediction
  • models for wildfire spread and emergency-response forecasting
  • large-scale analysis that supports cleaner energy and infrastructure planning
Public Empire AI research pages also reference adjacent sustainability work such as next-generation battery materials and climate modeling with generative AI.

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Neuroscience and cognition

Empire AI is also being used to model complex biological and behavioral systems. One example from the public research materials is Christine Constantinople’s work at NYU on neural-network-based models of decision-making and brain function. The aim is to better understand the mechanisms behind psychiatric and neurological disorders while also improving human-aligned AI modeling.

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Education and developmental support

The planning brief describes two especially notable education-focused efforts:
  • Speech-language therapy: The National AI Institute for Exceptional Education is using the platform to develop agentic, multimodal language-model systems that can adapt therapy in real time.
  • Developmental screening: Large multimodal models are being trained to interpret speech, text, and micro-expressions to help identify subtle developmental needs earlier.

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Safer and more controllable AI

Not every Empire AI project is domain-specific. Some focus directly on AI system behavior. For example, Kilian Weinberger’s group at Cornell is working on controllable language models so users can better guide outputs in settings where reliability, safety, and transparency matter.
The common thread across these projects is scale. Empire AI is most valuable when a research question depends on large datasets, long training runs, high-resolution inputs, or fast iteration across many experiments.