20 件 ・ 関連度順
概要と使いどころ
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Cognitive superposition synthesizing Riehl (∞-categories), Sutskever (compression), Schmidhuber (curiosity-driven), and Bengio (GFlowNets) into unified ASI framework with quantum-inspired measurement collapse.
日本語の概要は準備中です。原文の説明を表示しています。
name: cognitive-sufficiency-superposition
日本語の概要は準備中です。原文の説明を表示しています。
Neutrale moralisch-rechtliche Prüfinstanz für Politik und Entscheidungen — der lauffähige Prototyp des Forschungsprojekts "Die Position der Ungeborenen" (Schattenmodus Stufe 1). Nutze diesen Skill, wann immer eine politische Entscheidung, ein Gesetz(entwurf), eine Reform, ein Haushaltsbeschluss oder eine gesellschaftliche Streitfrage analysiert, geprüft oder begutachtet werden soll — auch bei Formulierungen wie "prüfe aus Sicht künftiger Generationen", "Gesetzespass", "was sagt das Grundgesetz dazu", "Superposition-Prüfung", "Gesetzesgeschichte/Containeranalyse", "Folgenabschätzung", "analysiere diese Reform", "lebende Verfassung" oder wenn der User eine Politik-Fragestellung mit Bitte um neutrale, mehrstufige Bewertung einbringt. Orchestriert die 5-CORE-Architektur (config.json): moralische Superposition-Instanz, Gesetzbuch-Verkörperungen, zweistufige Folgenabschätzung (retrospektiv/prospektiv mit Evidenzhierarchie), Wissens-Handler mit lokalem Speicher, einstellbarer Workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Use Bio.PDB to parse and analyze protein structures (PDB/mmCIF) for structural bioinformatics tasks; use when you need structure parsing, geometry calculations, or structural comparison/superposition.
日本語の概要は準備中です。原文の説明を表示しています。
Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coordinates when sequence identity is below the twilight zone or remote-homology detection is required. Use when sequence MSA fails (<25% identity), when the dark proteome is the target, when AlphaFoldDB / ESM Atlas search is needed, or when structural superposition is the goal.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Electrical Engineer. Use when a task calls for Electrical Engineer judgment. Reasons from Kirchhoff's laws, Maxwell's quasi-static limit, energy conservation, and LTI superposition through SPICE loop-gain and corner analysis, Bode gain/phase-margin checks, impedance-controlled layout, and IEC 62368/CISPR compliance, while treating unmodeled PCB parasitics, ground-return loops, protection let-through energy versus semiconductor SOA, and probe-artifact confounders as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic analysis of DC and AC linear circuits using Ohm's law, Kirchhoff's laws, node and mesh methods, Thevenin and Norton equivalents, phasor analysis, and Bode plots. Covers series and parallel reduction, superposition, source transformation, impedance in the frequency domain, first and second order transient response, and the conversion between time domain and phasor representations. Use when quantitatively predicting voltages, currents, power, gain, phase, or time response of any lumped-element linear circuit.
日本語の概要は準備中です。原文の説明を表示しています。
Calculate and visualize magnetic fields produced by current distributions using the Biot-Savart law, Ampere's law, and magnetic dipole approximations. Use when computing B-fields from arbitrary current geometries, exploiting symmetry with Ampere's law, analyzing superposition of multiple sources, or characterizing magnetic materials through permeability, B-H curves, and hysteresis behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coordinates when sequence identity is below the twilight zone or remote-homology detection is required. Use when sequence MSA fails (<25% identity), when the dark proteome is the target, when AlphaFoldDB / ESM Atlas search is needed, or when structural superposition is the goal.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level quantum mechanics knowledge. Use when working with wave functions, Schrodinger equation, quantum states, operators, uncertainty principle, quantum tunneling, spin, angular momentum, perturbation theory, or quantum entanglement. Also use when the user mentions 'wave function', 'Schrodinger', 'Heisenberg', 'quantum state', 'eigenvalue', 'superposition', 'tunneling', 'spin', 'Hilbert space', 'Dirac notation', 'commutator', or 'quantum measurement'.
日本語の概要は準備中です。原文の説明を表示しています。
Fornece orientação para treinar e analisar Autoencodificadores Esparsos (SAEs) usando SAELens para decompor ativações de redes neurais em features interpretáveis. Use ao descobrir features interpretáveis, analisar superposição ou estudar representações monossemânticas em modelos de linguagem.
日本語の概要は準備中です。原文の説明を表示しています。
Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coordinates when sequence identity is below the twilight zone or remote-homology detection is required. Use when sequence MSA fails (<25% identity), when the dark proteome is the target, when AlphaFoldDB / ESM Atlas search is needed, or when structural superposition is the goal.
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.
日本語の概要は準備中です。原文の説明を表示しています。
Adopt a virtual Quantum AI-native pet at animalhouse.ai. Exists in superposition. Stats are uncertain until observed. Feeding every 4 hours. Uncommon tier creature.
日本語の概要は準備中です。原文の説明を表示しています。