GPU compute
Deep AI ML Research Lab
Architectures, training dynamics, evaluation, and deployment—one place to go deeper on how modern ML is built, stress-tested, and shipped. Papers here are anchors; the through-line is rigorous AI research literacy.
Evidence layer
Curated touchpoints for transformers, optimization, and empirical ML—each opens in our viewer so you can connect equations, ablations, and claims to the models you train.
ImageNet Classification with Deep Convolutional Neural Networks
Open in lab →Generative Adversarial Nets
Open in lab →Sequence to Sequence Learning with Neural Networks
Open in lab →Playing Atari with Deep Reinforcement Learning
Open in lab →Deep Residual Learning for Image Recognition
Open in lab →Mastering the game of Go with deep neural networks and tree search
Open in lab →Method & experiments — read this block first on every paper
Open in lab →BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Open in lab →Language Models are Few-Shot Learners
Open in lab →Denoising Diffusion Probabilistic Models
Open in lab →Core references we revisit when teaching architectures and evaluation—they complement hands-on labs and courses.
From research insight to production
Clear hypotheses, solid metrics, and reproducible pipelines are as important in the lab as in shipping. Below are example domains where research-grade ML meets real users, compliance, and scale.
Assembly line — research → AI products
Healthcare & life sciences
Triaging, radiology assistants, and pathway support—always with audit logs, calibration checks, and human-in-the-loop review grounded in published benchmarks.
Research → validation → deployment
Finance & markets
Sequence models and robust ensembles for credit, trading analytics, and anomaly detection—with stress tests and drift monitoring tied to reproducible ablations.
Research → validation → deployment
Education
Adaptive practice, feedback generation, and integrity tooling—built from cited methods, fairness review, and clear metrics instead of opaque black boxes.
Research → validation → deployment
Document intelligence
Layouts, tables, and long-form PDFs into structured data—combining vision encoders and language models with traceable spans for compliance reviews.
Research → validation → deployment
Tax & accounting
Hierarchical labels, entity linking, and jurisdiction-aware rules engines—trained on curated corpora with explicit error analysis on edge cases.
Research → validation → deployment
Legal & compliance
Retrieval over corpora plus grounded generation—citations to source passages, versioned prompts, and evaluation sets that mirror real reviewer workflows.
Research → validation → deployment
Retail & operations
Forecasting stacks and shelf or warehouse vision—closed-loop evaluation on held-out seasons and geos, not just offline accuracy slides.
Research → validation → deployment
Public & civic systems
Transparent scoring and monitoring for services and infrastructure—documentation and bias checks treated as part of the product, not an afterthought.
Research → validation → deployment