Results for “moltr”

Expert guidance for Mojo, the programming language by Modular that combines Python's usability with C-level performance. Helps developers write high-performance AI/ML code, optimize numerical computations with SIMD and parallelism, and gradually port Python code to Mojo for orders-of-magnitude speedups.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Decide where to save any piece of information — monday.com, local file, daily notes, or MEMORY.md. Use this skill before saving anything to ensure the right destination. Prevents local clutter and ensures the owner can access all relevant content in monday.com.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Integrates on-device and cloud machine learning into Flutter apps with TensorFlow Lite and Firebase ML Kit, covering image classification, object detection, OCR, face detection, and barcode scanning.

Sets up MQTT brokers and clients for messaging in IoT systems. Use for lightweight messaging in IoT.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Configure Kotlin build and quality tooling, including Gradle Kotlin DSL, Version Catalogs, KMP, ktlint, Detekt, MockK, coverage, and quality plugins. Use for Kotlin-specific build, lint, test-tool, or coverage setup; defer Java-only tooling and Spring test behavior.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Analyze AI disruption pressure across a business, map competitive exposure, and produce a 90-day defensive action plan.

Plan, debug, tune, evaluate, export, or deploy public Nemotron embedding and reranking retrieval recipes using the current checkout.

Selects Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes based on Orin SM 8.7 vs Thor SM 11.0 and JetPack version.

Estructura aplicaciones Flutter en módulos independientes y reutilizables con flutter_modular, incluyendo diseño de paquetes, dependencias y configuración de Melos.

Provides idiomatic Kotlin implementation patterns including coroutine concurrency, Flow stream handling, multiplatform architecture, Compose UI construction, Ktor server setup, and type-safe DSL design.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Use when implementing ML functionality with production-grade patterns and safeguards.

Write memoranda of understanding for partnerships. TRIGGERS - Use when user needs help with mou-writer related tasks.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.

Computes the AUROC metric using torchmetrics, handling binary, multiclass, and multilabel tasks with configurable thresholds and averaging.

Fast-executing ML engineer for experiments. Use when the user asks to talk to Jett, requests the ML engineer, or needs experiment implementation.

CONDOR v2.0 — Multi-Asset Thesis Picker. Evaluates BTC, ETH, SOL, HYPE simultaneously and enters the strongest thesis. Conviction-scaled margin. DSL exit managed by plugin runtime via runtime.yaml.

Use when building a cursor trail whose spacing stays constant at any hand speed by emitting motes per distance travelled (not on a timer)—sub-segment placement, ring-buffer ordering, idle breath, 3D screen anchoring, coasting, touch and reduced-motion fallbacks—for wisps, sparks, embers, comet tails, plankton, or dust.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.