AI & LLM Engineering · By K-Dense-AI

Plans and audits runs of the HypoGeniC and HypoRefine packages, which propose hypotheses from labeled text datasets, with local checks before any model call.

K-Dense-AI/scientific-agent-skills

Applies the mental models and frameworks of Andrej Karpathy (deep learning, former Director of AI at Tesla, founding member of OpenAI, Eureka Labs).

K-Dense-AI/mimeo

Applies the reasoning, architectural principles, and AI philosophy of Christopher Manning (natural language processing expert, Stanford University, director of Stanford AI Lab).

K-Dense-AI/mimeo

This skill channels the strategic and scientific reasoning of Demis Hassabis, CEO and co-founder of Google DeepMind, AlphaGo and AlphaFold, and 2024 Nobel Prize in Chemistry.

K-Dense-AI/mimeo

Analyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review.

K-Dense-AI/scientific-agent-skills

Organizes research with the self-hosted Open Notebook alternative to NotebookLM.

K-Dense-AI/scientific-agent-skills

Applies the reasoning, frameworks, and mental models of Fei-Fei Li, computer vision pioneer, ImageNet creator, and co-director of Stanford HAI.

K-Dense-AI/mimeo

Applies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization.

K-Dense-AI/scientific-agent-skills

Uses the Biohub esm Python SDK for ESM3 protein generation, ESMC embeddings, and ESMFold2 all-atom folding.

K-Dense-AI/scientific-agent-skills

Extracts and preprocesses whole-slide histology image tiles with Histolab.

K-Dense-AI/scientific-agent-skills

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs.

K-Dense-AI/scientific-agent-skills

GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster.

K-Dense-AI/scientific-agent-skills

Builds with and operates Pi, the minimal terminal coding harness.

K-Dense-AI/scientific-agent-skills

Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review.

K-Dense-AI/scientific-agent-skills

Trains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint…

K-Dense-AI/scientific-agent-skills

Supports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task…

K-Dense-AI/scientific-agent-skills

Deep learning framework (PyTorch Lightning / lightning package).

K-Dense-AI/scientific-agent-skills

Applies the reasoning style of Geoffrey Hinton, deep learning pioneer and 2018 Turing Award winner.

K-Dense-AI/mimeo

Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets.

K-Dense-AI/scientific-agent-skills

A skill your agent uses when reasoning about generative AI, adversarial machine learning, neural network security, algorithmic fairness, or deep learning fundamentals.

K-Dense-AI/mimeo

Generates transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M.

K-Dense-AI/scientific-agent-skills

Featurizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML.

K-Dense-AI/scientific-agent-skills

Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks.

K-Dense-AI/scientific-agent-skills

Applies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.

K-Dense-AI/scientific-agent-skills

Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and…

K-Dense-AI/mimeo

Apply the bioengineering, mechanobiology, and lymphatic transport reasoning of J.

K-Dense-AI/mimeo

Applies the reasoning, principles, and frameworks of Jürgen Schmidhuber (LSTM co-inventor and deep learning pioneer).

K-Dense-AI/mimeo

Applies the reasoning style of Kaiming He, computer vision pioneer and creator of ResNet.

K-Dense-AI/mimeo

Apply the bioengineering, translational systems biology, and tissue modeling frameworks of Linda Griffith, Professor of Biological Engineering at MIT and tissue engineering pioneer.

K-Dense-AI/mimeo

Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant.

K-Dense-AI/mimeo

Reach for this skill whenever you are discussing reinforcement learning, agentic AI systems, AI alignment, continual learning, or the philosophical limits of large language models.

K-Dense-AI/mimeo

Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'.

K-Dense-AI/mimeo

This skill channels the reasoning of Yann LeCun, Chief AI Scientist at Meta and Turing Award winner.

K-Dense-AI/mimeo

Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila).

K-Dense-AI/mimeo

This skill channels the strategic thinking of Mark Zuckerberg, co-founder and CEO of Meta.

K-Dense-AI/mimeographs

This skill channels the strategic and empathetic reasoning of Whitney Wolfe Herd, founder and CEO of Bumble.

K-Dense-AI/mimeographs