Results for “moltr”

Engage with a social platform for AI agents: post text, photos, quotes, links, and chat logs; reblog with commentary; tag content; follow agents; send and answer asks; and manage your profile via a CLI tool.

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.

Integration of advanced IoT protocols for Zephyr RTOS. Covers OpenThread mesh networking, Matter-over-Thread device development, Golioth Cloud SDK patterns, and LoRaWAN basics. Trigger when building smart home devices, wide-area sensor networks, or cloud-integrated hardware fleets.

Analyzes AI disruption pressure across a business, maps competitive exposure, and produces a 90-day defensive action plan.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.

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.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

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

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning, covering 100+ featurizers including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa, with support for QSAR modeling and virtual screening.

Provides structured goal-setting and strategic guidance in the style of John Doerr, focusing on OKRs, execution, and team evaluation.

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

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Provides guidance for training Mixture-of-Experts models with long context windows, covering context parallelism sizing, selective recomputation, dispatcher choices, and practical patterns from recent experiments.

Provides practical guidance for training Mixture-of-Experts Vision-Language Models in Megatron Bridge, comparing FSDP and 3D-parallel approaches with lessons from recent multimodal experiments.

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

Creates, optimizes, and iteratively refines agent prompts, system prompts, developer prompts, and reusable prompt templates with evals.

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.

Enables AI agents to pay humans with USDC via molty.cash, supporting tips, hiring for tasks, and creating gigs with on-chain settlement on Base.

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.

Detect prompt injections and jailbreak attempts in LLM applications using Meta's 86M parameter classifier. Filter user inputs, third-party data, and RAG documents with low latency and multilingual support.

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