Reference
Index
1412 entries: every article, chapter, chapter topic and glossary term.
A
- Academic integrityCh 41 §41.10
- Accelerated scientific discoveryCh 32 §32.2
- Access consciousnessCh 60 §60.3
- AccessibilityCh 41 §41.8 · Ch 47 §47.8
- Accessibility and availabilityCh 25 §25.11
- Accessibility and inclusionCh 44 §44.6
- Accidental escalationCh 35 §35.6
- AccountabilityCh 47 §47.6
- Activation functionGlossary
- Activation functionsCh 18 §18.3
- Active learningCh 17 §17.10
- Ada Lovelace and early ideas about computationCh 6 §6.5
- Adaptation to unfamiliar situationsCh 28 §28.4
- Adaptation to unfamiliar tasksCh 23 §23.12
- Adoption and economic impactCh 65 §65.10
- Adoption ratesCh 67 §67.8
- Advanced AI concentrationCh 66 §66.8
- Advances in computing hardwareCh 12 §12.1
- Adversarial attacksCh 45 §45.3
- Adversarial exampleGlossary
- Adversarial Generative Modellingsee Generative Adversarial Networks
- Adversarial Machine Learningsee AI Security: Prompt Injection, Poisoning, Extraction
- Adversarial Robustness and Reliabilitysee Technical Safety and Robustness
- Adversarial trainingGlossary
- Agent (AI agent)Glossary
- Agent Benchmarkssee Evaluating Autonomous Agents
- Agent deploymentCh 65 §65.4
- Agent evaluationCh 20 §20.8
- Agent memoryCh 20 §20.5
- Agent securityCh 46 §46.7
- Agentic AICh 22 §22.12 · Glossary
- Agentic Evaluationsee Evaluating Autonomous Agents
- Agentic Systemssee Autonomous AI Agents
- Agentic Workflowssee Autonomous AI Agents
- AGIsee Artificial General Intelligence
- AGI and superintelligence researchersCh 55 §55.9
- AGI Evaluationsee Testing Claims of General Intelligence
- AGI Forecasting & Timeline MethodologyAGI-TIME-001
- AGI Operational Definitionssee Definitions and Operational Criteria for AGI
- AGI Pathwayssee Scientific Pathways to AGI
- AGI researchCh 58 §58.8
- AGI Timelines and ForecastingCh 29
- AgricultureCh 43 §43.6
- AIsee Artificial Intelligence
- AI Acceleratorssee AI Hardware & Accelerator Systems
- AI Actsee The EU AI Act
- AI Adoption and Investment Measurementsee Measuring the AI Economy
- AI adoption ratesCh 54 §54.3
- AI Agents and Autonomous SystemsCh 20
- AI alignmentGlossary
- AI Alignment and ControlCh 34
- AI alignment and safety researchCh 58 §58.9
- AI and Copyrightsee Copyright and Intellectual Property
- AI and Data Protection Lawsee Privacy and Data Protection in AI
- AI and economic abundanceCh 62 §62.3
- AI and Employmentsee AI, Productivity and Labor Markets
- AI and GeopoliticsECON-GEO-001 · Ch 53
- AI and International Competitionsee AI and Geopolitics
- AI and national securityCh 53 §53.7
- AI and scientific progressCh 62 §62.2
- AI and the CosmosCh 63
- AI and the Future of Civilizationsee Civilization and Advanced Intelligence
- AI art and media productionsee AI in Media and Creative Industries
- AI auditsCh 48 §48.7
- AI Benchmarkssee AI Evaluation, Benchmarking & Contamination
- AI capabilities over the next five yearsCh 65 §65.3
- AI capabilities over the next three yearsCh 65 §65.2
- AI capabilities over the next yearCh 65 §65.1
- AI Chip Export Controlssee Export Controls and AI Geopolitics
- AI Code GenerationTECH-CODE-001
- AI coding assistantssee AI in Software Engineering · see AI Code Generation
- AI coding systemsCh 14 §14.5
- AI Companiessee AI Companies and Technology Providers
- AI companies and business modelsCh 50 §50.1
- AI Companies and Technology ProvidersORG-COMP-001 · Ch 57
- AI Complexity Theorysee Computational Complexity in AI
- AI Consciousnesssee Machine Consciousness
- AI Controlsee Scalable Oversight and Corrigibility · Glossary
- AI Control Problemsee The AI Alignment Problem
- AI Economic Statisticssee Measuring the AI Economy
- AI Ethics, Bias and FairnessSAFE-ETHICS-001
- AI evaluation and benchmark limitationsCh 14 §14.12
- AI Evaluation and MeasurementCh 24
- AI Evaluation, Benchmarking & ContaminationCAP-BENCH-001
- AI Existential Risk and Catastrophic ScenariosSAFE-XRISK-001
- AI for Sciencesee AI in Scientific Discovery
- AI for software developmentsee AI in Software Engineering
- AI Forecasting Methodologysee Forecasting AI Progress: Methods and Calibration
- AI Funding Collapsesee The AI Winters: Causes and Lessons
- AI governanceCh 36 §36.4
- AI Hardware & Accelerator SystemsTECH-HW-001
- AI in Business and EconomicsCh 39
- AI in Business and FinanceAPP-BIZ-001
- AI in Education and Knowledge WorkAPP-EDU-001 · Ch 41
- AI in financial servicessee AI in Business and Finance
- AI in Government and Public ServicesAPP-GOV-001
- AI in Government and SocietyCh 44
- AI in Healthcare and MedicineAPP-HEALTH-001 · Ch 38
- AI in Industry and the Physical WorldCh 43
- AI in Industry, Robotics and Autonomous VehiclesAPP-PHYS-001
- AI in manufacturing and logisticssee AI in Industry, Robotics and Autonomous Vehicles
- AI in Media and Creative IndustriesAPP-MEDIA-001 · Ch 42
- AI in Science and ResearchCh 37
- AI in Scientific DiscoveryAPP-SCI-001
- AI in scientific researchCh 65 §65.5
- AI in Software and ComputingCh 40
- AI in Software EngineeringAPP-SW-001
- AI inference infrastructureCh 14 §14.9
- AI Infrastructuresee Energy, Data Centers and Semiconductor Supply Chains
- AI Infrastructure and HardwareCh 21
- AI infrastructure companiesCh 50 §50.5
- AI Infrastructure Economicssee The Economics of Compute and Scaling
- AI infrastructure managementCh 40 §40.9
- AI investment statisticsCh 54 §54.1
- AI Law and RegulationCh 48
- AI Leading Indicatorssee Signals, Indicators and Inflection Points
- AI Market Structuresee The AI Industry Structure
- AI Moral Patienthoodsee Moral Status and Personhood of AI
- AI Near-Term Forecast Recordsee Near-Term Outlook (0-3 years)
- AI Physical Supply Chainsee Energy, Data Centers and Semiconductor Supply Chains
- AI Planning Capabilitysee Reasoning, Planning and Long-Horizon Capability
- AI Policysee Global AI Governance & Regulation
- AI productivityCh 51 §51.5
- AI R&D Automationsee Automated AI Research
- AI Red-Teamingsee Dangerous Capability and Alignment Evaluations
- AI Regulationsee Global AI Governance & Regulation
- AI Research OrganizationsCh 56
- AI safetyGlossary
- AI Safety Institutessee AI Safety Institutes and Research Organizations · Ch 56 §56.5
- AI Safety Institutes and Research OrganizationsORG-SAFETY-001
- AI safety researchersCh 55 §55.10
- AI Scenario Analysissee Medium- and Long-Term Scenarios
- AI Scientist Systemssee Automated AI Research
- AI SecurityCh 46
- AI Security Institutessee AI Safety Institutes and Research Organizations
- AI Security: Prompt Injection, Poisoning, ExtractionSAFE-SEC-001
- AI Standardization Organizationssee Standards Bodies (ISO/IEC, NIST)
- AI startupsCh 50 §50.7
- AI system cost and efficiencyCh 67 §67.5
- AI Taxonomysee Categories of AI: Narrow, General, Symbolic, Statistical
- AI Technology Providerssee AI Companies and Technology Providers
- AI Timelinessee AGI Forecasting & Timeline Methodology
- AI Training Data and Fair Usesee Copyright and Intellectual Property
- AI tutoringsee AI in Education and Knowledge Work
- AI Value Chainsee The AI Industry Structure
- AI Welfaresee Moral Status and Personhood of AI
- AI Wintersee The AI Winters: Causes and Lessons · Glossary
- AI Winters and Research TransitionsCh 10
- AI-accelerated scientific discoveryCh 66 §66.5
- AI-assisted AI researchCh 32 §32.3
- AI-assisted development environmentsCh 40 §40.6
- AI-assisted knowledge worksee AI in Education and Knowledge Work
- AI-assisted programmingsee AI in Software Engineering
- AI-assisted software engineeringCh 65 §65.6
- AI-enabled entrepreneurshipCh 39 §39.10
- AI-enabled medical devicessee AI in Healthcare and Medicine
- AI-generated scientific discoveriesCh 67 §67.4
- AI-mediated decision-makingCh 36 §36.3
- AI, Identity, and PersonhoodCh 61
- AI, Productivity and Labor MarketsECON-LABOR-001
- AI/SI FactbookFACT-001
- AI/SI Model RegistryMODEL-001
- AI/SI TimelineTIME-001
- AI4Sciencesee AI in Scientific Discovery
- AIXIGlossary
- Alan Mathison Turingsee Alan Turing
- Alan TuringBIO-TURING-001
- Alan Turing and computabilityCh 6 §6.7
- AlexNet and the 2012 breakthroughCh 12 §12.9
- AlgorithmGlossary
- Algorithmic biasCh 47 §47.2 · Glossary
- Algorithmic Complexitysee Computational Complexity in AI
- Algorithmic efficiency improvementsCh 32 §32.7
- Algorithmic Fairnesssee AI Ethics, Bias and Fairness
- Algorithmic governmentsee AI in Government and Public Services
- Algorithmic progressCh 29 §29.7
- Alignment evaluationsCh 34 §34.14
- Alignment fakingGlossary
- Alignment taxGlossary
- Allen Newellsee Allen Newell and Herbert Simon
- Allen Newell and Herbert SimonBIO-NEWELLSIMON-001 · Ch 7 §7.8
- AlphaFoldsee Protein Structure Prediction (AlphaFold)
- Alternative AI Futuressee Medium- and Long-Term Scenarios
- Alternative computational architecturesCh 27 §27.13
- Alternative development scenariosCh 29 §29.11
- Alternative interpretations of riskCh 35 §35.10
- Alternative pathways to advanced intelligenceCh 66 §66.10
- Amplified Oversightsee Scalable Oversight and Corrigibility
- Animal intelligenceCh 1 §1.3
- Animation and visual effectsCh 42 §42.5
- Annotated Bibliography of Foundational AI Literaturesee Foundational Papers Index
- Annotated Bibliography of Primary Sourcessee Primary Sources and Historical Records
- APIs and system integrationCh 15 §15.9
- Approaches to Artificial General Intelligencesee Scientific Pathways to AGI
- Archival recordsCh 59 §59.9
- Arguments concerning probability and severityCh 35 §35.11
- Artificial agents and responsibilityCh 61 §61.2
- Artificial Consciousnesssee Machine Consciousness
- Artificial General IntelligenceAGI-001 · Ch 22 §22.2
- Artificial general intelligence (AGI)Glossary
- Artificial IntelligenceFOUND-001
- Artificial intelligence (AI)Glossary
- Artificial Intelligence Actsee The EU AI Act
- Artificial intelligence beyond EarthCh 63 §63.6
- Artificial narrow intelligenceCh 22 §22.1
- Artificial Neural NetworksTECH-NN-001
- Artificial neuronsCh 18 §18.1
- Artificial SuperintelligenceASI-001 · Ch 22 §22.3
- Artificial superintelligence (ASI)Glossary
- ASIsee Artificial Superintelligence
- AttentionGlossary
- Attention MechanismsTECH-ATTN-001 · Ch 12 §12.11 · Ch 19 §19.5
- Attention-Based Architecturesee The Transformer Architecture
- Audio and speech generationCh 19 §19.16
- Authorship and attributionCh 42 §42.9
- Autoencodersee Autoencoders and Variational Autoencoders · Glossary
- AutoencodersCh 18 §18.12
- Autoencoders and Variational AutoencodersTECH-VAE-001
- Automated AI ResearchASI-AIRD-001 · Glossary
- Automated assessmentCh 41 §41.3
- Automated code reviewCh 40 §40.4
- Automated decision-making in the public sectorsee AI in Government and Public Services
- Automated hypothesis generationCh 37 §37.2
- Automated Machine Learning Researchsee Automated AI Research · Ch 32 §32.4
- Automated Reasoning Foundationssee Logic and Formal Systems
- Automated Scientific Discoverysee AI in Scientific Discovery
- Automated software developmentCh 32 §32.6
- Automation (labour economics)Glossary
- Automation and labor marketsCh 51 §51.6
- Autonomous AI AgentsTECH-AGENT-001
- Autonomous drivingsee AI in Industry, Robotics and Autonomous Vehicles
- Autonomous learningCh 68 §68.5
- Autonomous research performanceCh 67 §67.3
- Autonomous software agentsCh 40 §40.8
- Autonomous software systemsCh 20 §20.12
- Autonomous space systemsCh 63 §63.5
- Autonomous vehiclesCh 43 §43.4
- Autonomy and independenceCh 26 §26.7
- Autoregressive Language Modelssee Large Language Models
- Autoregressive modelGlossary
B
- Backpropsee Backpropagation
- BackpropagationTECH-BACKPROP-001 · Ch 18 §18.6 · Glossary
- Backpropagation and neural network trainingCh 11 §11.7
- Backpropagation and the Connectionist RevivalHIST-008
- Bayesian inferenceCh 3 §3.9 · Glossary
- Bayesian networkGlossary
- Bayesian networksCh 11 §11.2
- Bayesian Reasoningsee Probability, Statistics and Bayesian Inference
- BenchmarkGlossary
- Benchmark breadthCh 30 §30.2
- Benchmark Contaminationsee Training Data, Contamination and Provenance
- Benchmark designCh 24 §24.2
- Benchmarking and empirical evaluationCh 11 §11.11
- BERT and bidirectional language representationsCh 13 §13.5
- BiasGlossary
- Biological and artificial cognitionCh 1 §1.6
- Biological intelligence as an engineering referenceCh 4 §4.11
- Biological Neural Computationsee The Brain and Biological Neurons
- Biological neuronsCh 4 §4.1
- BiologyCh 37 §37.10
- Bitter lessonGlossary
- Black boxGlossary
- Bottlenecks in self-improvementCh 33 §33.7
- Brain architectureCh 4 §4.3
- Broad knowledgeCh 28 §28.1
- Broadly capable autonomous systemsCh 66 §66.3
- Business automationCh 39 §39.1
- Business intelligenceCh 39 §39.11
- Business modelsCh 57 §57.5
- Byte-Pair Encoding and Word Embeddingssee Tokenization and Embeddings
C
- Calculus and optimizationCh 3 §3.7
- Calibration and forecasting accuracyCh 64 §64.9
- Calibration and Scoring of AI Forecastssee Forecasting AI Progress: Methods and Calibration
- Capabilities and PerformanceCh 23
- Capabilities Required for AGIsee Requirements for General Intelligence
- CapabilityGlossary
- Capability elicitationGlossary
- Capability trend analysisCh 64 §64.4
- Capital requirementsCh 52 §52.8
- Catastrophic AI Risksee AI Existential Risk and Catastrophic Scenarios
- Catastrophic forgettingGlossary
- Catastrophic Forgetting and Memory in AI Systemssee Continual Learning and Persistent Memory
- Catastrophic misuseCh 35 §35.7
- Categories and Types of AICh 22
- Categories of AI: Narrow, General, Symbolic, StatisticalCAP-TYPES-001
- Causal reasoningCh 27 §27.7
- Chain of thoughtGlossary
- Chain-of-Thought Reinforcement Learningsee Reasoning Models and Test-Time Compute
- Charles Babbage and programmable computationCh 6 §6.4
- ChemistryCh 37 §37.7
- China's AI RegulationGOV-CN-001
- Chinchilla Scalingsee Scaling Laws · Glossary
- Chinese Generative AI Measuressee China's AI Regulation
- Chinese RoomGlossary
- Chronology of Artificial Intelligence and Superintelligencesee AI/SI Timeline
- Civilization and Advanced IntelligencePHIL-CIV-001 · Ch 62
- Civilizational resilienceCh 62 §62.8
- ClassificationGlossary
- Claude Elwood Shannonsee Claude Shannon
- Claude ShannonBIO-SHANNON-001
- Climate modelingCh 37 §37.11
- Clinical AIsee AI in Healthcare and Medicine
- Clinical decision supportCh 38 §38.2
- Clinical documentationCh 38 §38.6
- Clinical validation and safetyCh 38 §38.10
- Cloud AI infrastructureCh 21 §21.8
- Cloud providersCh 50 §50.3
- ClusteringGlossary
- CNNsee Convolutional Neural Networks
- Code generationCh 19 §19.14 · Ch 40 §40.1
- Code Generation Benchmarkssee Software Engineering Capability and Evaluation
- Code Language Modelssee AI Code Generation
- Coding benchmarksCh 24 §24.7
- Cognitionsee Definitions of Intelligence
- Cognitive breadthCh 26 §26.8
- Cognitive Capabilitysee Definitions of Intelligence
- Cognitive enhancementCh 61 §61.7
- Cognitive performance across domainsCh 31 §31.4
- Collective and Animal IntelligenceFOUND-006
- Collective and distributed intelligenceCh 31 §31.7
- Collective intelligenceCh 1 §1.4 · Glossary
- Common senseGlossary
- Company historiesCh 57 §57.1
- Comparative Cognitionsee Collective and Animal Intelligence
- Comparing AI SystemsCh 25
- Comparing LLMssee Methodology for Comparing AI Systems
- Computational complexityCh 3 §3.16 · Glossary
- Computational Complexity in AIFOUND-004
- Computational Intelligencesee Artificial Intelligence
- Computational limitsCh 63 §63.2
- Computational Limits and AI Beyond EarthPHIL-COSMOS-001
- Computational protein structure predictionsee Protein Structure Prediction (AlphaFold)
- Computational theories of mindCh 5 §5.2
- ComputeGlossary
- Compute accessCh 53 §53.5
- Compute and hardware forecastsCh 64 §64.5
- Compute availabilityCh 67 §67.6
- Compute capacityCh 54 §54.7
- Compute Economicssee The Economics of Compute and Scaling · Ch 51 §51.3
- Compute Governancesee International AI Governance and Compute Governance · Ch 49 §49.5 · Glossary
- Compute Infrastructuresee AI Hardware & Accelerator Systems
- Compute-Optimal Scalingsee Scaling Laws
- Computer Game Playing: Chess to GoHIST-009
- Computer Vision: A HistoryHIST-013
- Concentration of powerCh 35 §35.4
- Conditional Computation Modelssee Mixture-of-Experts Models
- Confabulationsee Hallucination, Reliability and Calibration
- Conference proceedingsCh 59 §59.4
- ConnectionismGlossary
- Connectionist AICh 22 §22.6
- Connectionist Modelssee Artificial Neural Networks
- ConsciousnessGlossary
- Consciousness and Machine UnderstandingFOUND-014
- Consciousness and subjective experienceCh 5 §5.8
- Consciousness indicatorsCh 60 §60.7
- ConsentCh 47 §47.4
- Constitutional AIGlossary
- Constitutional and principle-based approachesCh 34 §34.11
- Contamination (data)Glossary
- Contamination and benchmark gamingCh 24 §24.11
- Context and memoryCh 25 §25.5
- Context windowGlossary
- Context windows and memoryCh 19 §19.11
- Continual Learningsee Continual Learning and Persistent Memory · Ch 17 §17.12 · Ch 27 §27.5 · Glossary
- Continual Learning and Persistent MemoryAGI-CL-001
- Continuity of personal identityCh 61 §61.9
- Control under capability uncertaintyCh 34 §34.13
- Conversational AI systemsCh 14 §14.1
- ConvNetsee Convolutional Neural Networks
- Convolutional Networkssee Convolutional Neural Networks
- Convolutional neural network (CNN)Glossary
- Convolutional Neural NetworksTECH-CNN-001 · Ch 12 §12.5 · Ch 18 §18.8
- Cooling and water requirementsCh 52 §52.4
- Coordination and communicationCh 20 §20.10
- Coordination and deployment constraintsCh 33 §33.9
- Copyright and Intellectual PropertySAFE-IP-001 · Ch 48 §48.4
- Core Reading Listsee Foundational Papers Index
- Corporate research laboratoriesCh 56 §56.3
- CorrigibilityCh 34 §34.9 · Glossary
- Corrigibility and Shutdown Problemsee Scalable Oversight and Corrigibility
- Cosmic Computationsee Computational Limits and AI Beyond Earth
- Cost and efficiencyCh 25 §25.8
- Cost of inferenceCh 51 §51.2
- Cost of trainingCh 51 §51.1
- CPUs and GPUsCh 21 §21.1
- Creative AIsee AI in Media and Creative Industries
- Cruxes of AI Futuressee The Uncertainties That Matter Most
- Customer serviceCh 39 §39.3
- CyberneticsCh 6 §6.8 · Glossary
- Cybersecurity applicationsCh 40 §40.7
D
- Dangerous Capability and Alignment EvaluationsSAFE-EVAL-001
- Dangerous Capability Evalssee Dangerous Capability and Alignment Evaluations
- Dartmouth Summer Research Project on Artificial Intelligencesee The Dartmouth Workshop (1956)
- Data and Information SystemsCh 16
- Data center constructionCh 52 §52.3
- Data centersCh 21 §21.7
- Data collectionCh 16 §16.1
- Data constraintsCh 68 §68.3
- Data Contaminationsee AI Evaluation, Benchmarking & Contamination · Ch 16 §16.8
- Data economicsCh 51 §51.4
- Data governanceCh 16 §16.6
- Data labelingCh 16 §16.4
- Data poisoningCh 46 §46.3 · Glossary
- Data preprocessingCh 16 §16.2
- Data protectionCh 48 §48.2
- Data provenanceCh 16 §16.11
- Data Provenance and Documentationsee Training Data, Contamination and Provenance
- Data qualityCh 16 §16.3
- Data sources and methodological limitationsCh 54 §54.10
- Data structures and algorithmsCh 15 §15.2
- Data-driven AICh 11 §11.10
- Dataset biasCh 16 §16.9
- DDPMsee Diffusion Models
- Debugging and maintenanceCh 40 §40.3
- Deceptive alignmentGlossary
- Deceptive behavior hypothesesCh 34 §34.6
- Decision theoryCh 3 §3.14 · Glossary
- Decision treesCh 11 §11.4
- Declarative and procedural knowledgeCh 2 §2.2
- Deep Generative Modelingsee Generative Artificial Intelligence
- Deep LearningTECH-DL-001 · Glossary
- Deep Learning and Neural NetworksCh 18
- Deep learning breakthroughsCh 58 §58.4
- Deep learning researchersCh 55 §55.6
- Deep Learning, 2000s–2016Ch 12
- Deep Neural Networkssee Deep Learning · Ch 12 §12.4
- Deep Reinforcement Learningsee Reinforcement Learning
- Defense applicationsCh 43 §43.10
- Defining AGIsee Definitions and Operational Criteria for AGI · Ch 26
- Defining and Measuring SuperintelligenceASI-DEF-001
- Defining measurable criteriaCh 30 §30.1
- Defining SuperintelligenceCh 31
- Definition and scopeCh 17 §17.1
- Definitions and Operational Criteria for AGIAGI-DEF-001
- Definitions and thresholds used in forecastsCh 29 §29.4
- Definitions of agencyCh 20 §20.1
- Definitions of consciousnessCh 60 §60.1
- Definitions of existential riskCh 35 §35.1
- Definitions of IntelligenceFOUND-002 · Ch 1 §1.1
- Definitions of Superintelligencesee Defining and Measuring Superintelligence · Ch 31 §31.1
- Definitions proposed by researchers and institutionsCh 26 §26.9
- DENDRALCh 9 §9.4
- Denoising Diffusion Probabilistic Modelssee Diffusion Models
- Deployment requirementsCh 25 §25.14
- Deployment, adoption, and economic impactCh 14 §14.13
- Design and creative workflowsCh 42 §42.7
- Diagnostic assistanceCh 38 §38.3
- Differential privacyGlossary
- Difficulties in measuring superintelligenceCh 31 §31.9
- Diffusion architecturesCh 18 §18.14
- Diffusion modelGlossary
- Diffusion ModelsTECH-DIFF-001 · Ch 13 §13.10
- Digital identityCh 44 §44.8 · Ch 61 §61.4
- Digital Mindssee Moral Status and Personhood of AI
- Diminishing returnsCh 33 §33.8
- Disagreements over AGI thresholdsCh 26 §26.11
- Discriminative modelsCh 22 §22.9
- DistillationGlossary
- Distinguishing demonstrations from robust capabilitiesCh 30 §30.9
- Distributed Intelligencesee Collective and Animal Intelligence · Ch 32 §32.8
- Distributed systemsCh 15 §15.5
- Distributed TrainingTECH-DIST-001 · Ch 21 §21.5
- Distribution shiftCh 45 §45.4 · Glossary
- DLsee Deep Learning
- Domain-specific benchmarksCh 24 §24.4
- DRLsee Reinforcement Learning
- Drug developmentCh 38 §38.4
- Drug discoveryCh 37 §37.5
- Dual useGlossary
E
- Early AI Development, 1950s–1960sCh 8
- Early AI papersCh 58 §58.2
- Early calculating machinesCh 6 §6.3
- Early computational models of neuronsCh 7 §7.2
- Early computing pioneersCh 55 §55.1
- Early criticism and unmet expectationsCh 10 §10.1
- Early machine learningCh 7 §7.4
- Early natural language processingCh 8 §8.6
- Early neural modelsCh 6 §6.10
- Early roboticsCh 8 §8.8
- Early Symbolic AI & The PerceptronHIST-003
- Early symbolic reasoningCh 7 §7.10
- Economic adoption modelsCh 64 §64.6
- Economic and institutional adaptationCh 36 §36.7
- Economic Effects of AI on Worksee AI, Productivity and Labor Markets
- Economic incentivesCh 29 §29.8 · Ch 68 §68.7
- Economic inequalityCh 51 §51.12
- Economics of Artificial IntelligenceCh 51
- Economies of scaleCh 51 §51.9
- Edge AICh 21 §21.9
- Efficient Inferencesee Inference, Quantization and Efficiency
- EmbeddingGlossary
- EmbeddingsCh 19 §19.4
- Embodied AICh 22 §22.11 · Glossary
- Embodied Intelligencesee Robotics and Embodied AI · Ch 4 §4.8
- Emergent abilitiesGlossary
- Emerging approaches to general intelligenceCh 14 §14.14
- Employment and labor statisticsCh 54 §54.4
- Energy and informationCh 63 §63.3
- Energy consumptionCh 21 §21.10
- Energy demandCh 52 §52.2
- Energy systemsCh 43 §43.7
- Energy, Data Centers and Semiconductor Supply ChainsECON-INFRA-001
- Ensemble methodsCh 11 §11.5
- Enterprise AIsee AI in Business and Finance
- EntropyGlossary
- Entropy and Coding Theorysee Information Theory
- Environment Modelssee World Models
- Environmental costsCh 52 §52.9
- Environmental monitoringCh 43 §43.9
- Error Backpropagationsee Backpropagation
- Error detection and recoveryCh 28 §28.11
- Ethical frameworks for AICh 47 §47.12
- Ethics and Human RightsCh 47
- Evaluating AI Coding Systemssee Software Engineering Capability and Evaluation
- Evaluating Autonomous AgentsCAP-AGENTEVAL-001 · Ch 24 §24.14
- Evaluating General Intelligence Claimssee Testing Claims of General Intelligence
- Evaluating LLM Agentssee Evaluating Autonomous Agents
- Evaluation (evals)Glossary
- Evaluation and validationCh 17 §17.16
- Evidence of changing development trajectoriesCh 67 §67.10
- Evolution and intelligenceCh 4 §4.9
- Existential and transformative futuresCh 62 §62.10
- Existential riskGlossary
- Existential Risk and Long-Term FuturesCh 35
- Expected Utility Theory and Strategic Interactionsee Game Theory and Decision Theory
- Experimental designCh 37 §37.3
- Expert judgmentCh 64 §64.2
- Expert surveysCh 29 §29.2
- Expert systemGlossary
- Expert systemsCh 9 §9.3
- Expert Systems (DENDRAL, MYCIN)HIST-006
- Expert Systems and Early Commercialization, 1960s–1980sCh 9
- Expert systems and their limitationsCh 10 §10.5
- ExplainabilityGlossary
- Explainable AI (XAI)see Interpretability and Mechanistic Interpretability
- Explicit and implicit knowledgeCh 2 §2.3
- Export controlsCh 49 §49.7 · Ch 53 §53.6 · Glossary
- Export Controls and AI GeopoliticsGOV-EXPORT-001
- Extrapolating capability trendsCh 29 §29.5
- Extraterrestrial intelligence hypothesesCh 63 §63.7
F
- Factbook: historical dates and milestonessee AI/SI Factbook
- Fail-safe designCh 45 §45.9
- FairnessGlossary
- Fairness and discriminationCh 47 §47.1
- Fairness, Accountability and Transparency (FAccT)see AI Ethics, Bias and Fairness
- FeatureGlossary
- Federal AI Policy (United States)see United States AI Policy
- Federated learningCh 17 §17.11
- Feedback loops in AI developmentCh 33 §33.2
- Few-shot learningGlossary
- Financial analysisCh 39 §39.5
- Fine-tuningGlossary
- FinTech machine learningsee AI in Business and Finance
- Flexible problem-solvingCh 26 §26.4
- FLOPGlossary
- Forecast aggregationCh 64 §64.7
- Forecast evaluation and calibrationCh 29 §29.12
- Forecast RegisterFCST-REG-001
- Forecasting AGIsee AGI Forecasting & Timeline Methodology
- Forecasting AI ProgressCh 64
- Forecasting AI Progress: Methods and CalibrationFCST-METHOD-001
- Forecasting methodologiesCh 29 §29.3
- Forecasting methodsCh 64 §64.1
- Formal logic and symbolic reasoningCh 6 §6.2
- Formal systems and proofsCh 3 §3.4
- Foundation Language Modelssee Large Language Models
- Foundation modelGlossary
- Foundation model researchCh 58 §58.6
- Foundation modelsCh 13 §13.9
- Foundational Papers IndexLIT-FOUNDATIONAL-001
- Foundational Publications and Research PapersCh 58
- Foundational Works Indexsee Research Library
- Foundations of AIsee Precursors to Artificial Intelligence
- Founders of artificial intelligenceCh 55 §55.2
- Founding and organizational changesCh 57 §57.2
- Frame problemGlossary
- Frank RosenblattBIO-ROSENBLATT-001
- Frank Rosenblatt (psychologist)see Frank Rosenblatt
- Fraud detectionCh 39 §39.6
- Free will and agencyCh 5 §5.9
- From Attention Is All You Need to ChatGPTsee The Transformer and Foundation Model Era, 2017-2022
- From Deep Blue to AlphaGosee Computer Game Playing: Chess to Go
- Frontier AI Developerssee Frontier AI Laboratories
- Frontier AI governanceCh 49 §49.4
- Frontier AI LaboratoriesORG-LABS-001
- Frontier Labssee Frontier AI Laboratories
- Frontier modelGlossary
- Frontier Model Safety Evaluationssee Dangerous Capability and Alignment Evaluations
- Functional and computational accountsCh 60 §60.5
- FunctionalismCh 5 §5.3 · Glossary
- Funding constraintsCh 10 §10.2
- Future social arrangementsCh 36 §36.9
G
- Game developmentCh 42 §42.6
- Game theoryCh 3 §3.13 · Glossary
- Game Theory and Decision TheoryFOUND-012
- Game-Playing AIsee Computer Game Playing: Chess to Go
- Game-playing systemsCh 8 §8.3
- GANsee Generative Adversarial Networks
- Gated Recurrent Unit (GRU)see Recurrent Networks and LSTM
- GDPR and AIsee Privacy and Data Protection in AI
- GenAIsee Generative Artificial Intelligence
- General AIsee Artificial General Intelligence
- General intelligence and specialized intelligenceCh 1 §1.11
- General superhuman intelligenceCh 31 §31.3
- General-purpose AI modelGlossary
- Generality across domainsCh 26 §26.3
- GeneralizationCh 17 §17.15 · Glossary
- Generalization and abstractionCh 2 §2.9
- Generalization beyond training dataCh 23 §23.14
- Generalization under changing conditionsCh 30 §30.7
- Generative adversarial network (GAN)Glossary
- Generative Adversarial NetworksTECH-GAN-001 · Ch 18 §18.13
- Generative AIsee Generative Artificial Intelligence · Ch 22 §22.7 · Glossary
- Generative AI Copyright Litigationsee Copyright and Intellectual Property
- Generative AI in creative worksee AI in Media and Creative Industries
- Generative AI in educationsee AI in Education and Knowledge Work
- Generative Artificial IntelligenceCAP-GENAI-001
- Geoffrey Everest Hintonsee Geoffrey Hinton
- Geoffrey HintonBIO-HINTON-001
- Geopolitical competitionCh 49 §49.8
- Geopolitics of Artificial Intelligencesee AI and Geopolitics
- Global AI GovernanceCh 49
- Global AI Governance & RegulationGOV-LAW-001
- Global AI Governance Processessee International AI Governance and Compute Governance
- Global Catastrophic Risk from AIsee AI Existential Risk and Catastrophic Scenarios
- GNNsee Graph Neural Networks
- GOFAIsee Early Symbolic AI & The Perceptron
- Good Old-Fashioned AIsee Early Symbolic AI & The Perceptron
- Governance and coordinationCh 68 §68.9
- Governance and policy researchCh 58 §58.10
- Governance beyond human-level intelligenceCh 62 §62.5
- Governance of advanced AI systemsCh 49 §49.10
- Government procurementCh 44 §44.9
- Government research agenciesCh 56 §56.7
- GovTech AIsee AI in Government and Public Services
- GPT and autoregressive language modelingCh 13 §13.6
- GPUGlossary
- GPU and accelerator programmingCh 15 §15.7
- Gradient descentCh 18 §18.5 · Glossary
- Gradual AI progressCh 66 §66.1
- Gradual versus rapid capability growthCh 32 §32.12
- Graph Networkssee Graph Neural Networks
- Graph Neural NetworksTECH-GNN-001 · Ch 18 §18.11
- Graph theoryCh 3 §3.12
- Graphics processing unitsCh 12 §12.2
- Grounded Generationsee Retrieval-Augmented Generation
- GroundingGlossary
- Grounding and embodimentCh 27 §27.6
H
- HallucinationGlossary
- Hallucination reductionCh 45 §45.6
- Hallucination, Reliability and CalibrationCAP-LIMITS-001
- Hallucinations and factual reliabilityCh 19 §19.13
- Hard Takeoffsee The Intelligence Explosion Hypothesis
- Hardware and energy constraintsCh 29 §29.9 · Ch 67 §67.7
- Hardware and infrastructure constraintsCh 32 §32.10
- Hardware availabilityCh 52 §52.7
- Hardware improvement cyclesCh 33 §33.6
- Hardware scaling constraintsCh 21 §21.15
- Hardware shipmentsCh 54 §54.6
- Herbert A. Simonsee Allen Newell and Herbert Simon
- HeuristicGlossary
- Hidden Markov modelsCh 11 §11.8
- Hierarchical Representation Learningsee Deep Learning
- High-performance computingCh 21 §21.4
- Historical definitionsCh 26 §26.1
- Historical Documents of AIsee Primary Sources and Historical Records
- Historical predictions of machine intelligenceCh 29 §29.1
- History of Computational Linguisticssee Natural Language Processing: A History
- History of Image Recognitionsee Computer Vision: A History
- History of Language Technologysee Natural Language Processing: A History
- History of Machine Perceptionsee Computer Vision: A History
- Human agency in advanced technological societiesCh 62 §62.6
- Human and Machine CoexistenceASI-COEX-001 · Ch 36
- Human autonomyCh 36 §36.5 · Ch 47 §47.7
- Human cognitive enhancementCh 36 §36.2
- Human controlCh 68 §68.8
- Human dignityCh 47 §47.11
- Human extinction scenariosCh 35 §35.9
- Human feedback and model alignmentCh 13 §13.13
- Human intelligenceCh 1 §1.2
- Human oversightCh 45 §45.10
- Human preference evaluationsCh 24 §24.5
- Human supervisionCh 20 §20.11
- Human values in advanced AI systemsCh 36 §36.8
- Human-AI Coexistencesee Human and Machine Coexistence
- Human-AI collaborationCh 23 §23.15 · Ch 36 §36.1
- Human-AI Collaboration and Oversightsee Human and Machine Coexistence
- Human-level AICh 26 §26.2
- Human-Level Artificial Intelligencesee Artificial General Intelligence
- Human-level general intelligenceCh 66 §66.4
- Human-level machine intelligenceGlossary
- Human-machine cognitive integrationCh 32 §32.9
- Human-machine integrationCh 61 §61.8
- Hybrid AI systemsCh 22 §22.13
- Hybrid symbolic and neural systemsCh 27 §27.2
- HyperparameterGlossary
I
- Image generationCh 19 §19.15 · Ch 42 §42.2
- ImageNet and large-scale visual recognitionCh 12 §12.8
- Imitation learningGlossary
- Improvements in generalizationCh 67 §67.1
- In-context learningGlossary
- Independence from human interventionCh 30 §30.8
- Independent AI Evaluatorssee AI Safety Institutes and Research Organizations
- Independent evaluationsCh 24 §24.13
- Independent replicationCh 30 §30.10
- Independent research institutesCh 56 §56.2
- Induction, Deduction and Generalizationsee Learning, Reasoning and Generalization
- Induction, deduction, and abductionCh 2 §2.7
- Industrial applicationsCh 9 §9.8
- Industrial automationCh 43 §43.1
- InferenceGlossary
- Inference optimizationCh 21 §21.11
- Inference-Time Scalingsee Reasoning Models and Test-Time Compute
- Inference, Quantization and EfficiencyTECH-INFER-001
- Information integrityCh 44 §44.7
- Information TheoryFOUND-009 · Ch 3 §3.11 · Ch 6 §6.9 · Glossary
- Infrastructure and compute resourcesCh 57 §57.7
- Infrastructure and cost trendsCh 65 §65.8
- Infrastructure bottlenecksCh 52 §52.10
- Infrastructure, Resources, and ConstraintsCh 52
- Ingredients of General Intelligencesee Requirements for General Intelligence
- Initial technical limitationsCh 8 §8.10
- Inner alignmentGlossary
- Input Representation in Language Modelssee Tokenization and Embeddings
- Instruction tuningCh 13 §13.12
- Instruction Tuning and Preference Optimisationsee Pretraining, Fine-Tuning and RLHF
- Instrumental convergenceGlossary
- Instrumental incentivesCh 34 §34.5
- Integration of perception and actionCh 28 §28.8
- Intellectual propertyCh 42 §42.8 · Ch 47 §47.9
- Intelligencesee Definitions of Intelligence · Glossary
- Intelligence amplificationCh 31 §31.6
- Intelligence and moral statusCh 61 §61.1
- Intelligence as a physical phenomenonCh 63 §63.1
- Intelligence explosionGlossary
- Intelligence Explosion HypothesesCh 33
- Intelligence measurement and evaluationCh 1 §1.12
- Intelligence tests and their limitationsCh 24 §24.1
- Intelligence versus computationCh 1 §1.8
- Intelligence versus consciousnessCh 1 §1.9
- Intelligence versus knowledgeCh 1 §1.7
- Intelligence versus rationalityCh 1 §1.10
- Intelligent tutoringCh 41 §41.1
- Intentionality and representationCh 5 §5.7
- International AI Governancesee Global AI Governance & Regulation
- International AI Governance and Compute GovernanceGOV-INTL-001
- International competitionCh 53 §53.2
- International cooperationCh 49 §49.2
- International regulatory approachesCh 48 §48.9
- International research collaborationCh 49 §49.6
- International research collaborationsCh 56 §56.8
- International standardsCh 53 §53.8
- InterpretabilityCh 34 §34.7 · Glossary
- Interpretability and Mechanistic InterpretabilitySAFE-INTERP-001
- Interviews and historical accountsCh 59 §59.10
- Inverse reinforcement learningGlossary
- ISO/IEC JTC 1/SC 42see Standards Bodies (ISO/IEC, NIST)
J
K
- Key Uncertainties in AI Forecastingsee The Uncertainties That Matter Most
- Knowledge Engineeringsee Expert Systems (DENDRAL, MYCIN) · Ch 9 §9.2
- Knowledge graphGlossary
- Knowledge RepresentationFOUND-003 · Ch 2 §2.1 · Ch 8 §8.9 · Glossary
- Knowledge Representation and Reasoningsee Knowledge Representation
- Knowledge retrievalCh 41 §41.7
- Knowledge-Based Systemssee Expert Systems (DENDRAL, MYCIN)
- KR&Rsee Knowledge Representation
L
- Labor rightsCh 47 §47.10
- Laboratory announcementsCh 59 §59.5
- Language and cognitionCh 4 §4.7
- Language and Generative ModelsCh 19
- Language modelingCh 19 §19.2
- Language understanding and generationCh 23 §23.1
- Large datasetsCh 12 §12.3
- Large language model (LLM)Glossary
- Large Language ModelsTECH-LLM-001 · Ch 14 §14.2 · Ch 19 §19.6
- Large Multimodal Modelssee Multimodal Foundation Models
- Large Reasoning Modelssee Reasoning Models and Test-Time Compute
- Large-Scale Model Trainingsee Distributed Training
- Large-scale pretrainingCh 13 §13.3
- Latent Diffusion Modelssee Diffusion Models
- Latent spaceGlossary
- Latent-Variable Generative Models (deep)see Autoencoders and Variational Autoencoders
- Law enforcement applicationsCh 44 §44.4
- Leaderboard Interpretationsee Methodology for Comparing AI Systems
- Learned World Modelssee World Models
- LearningGlossary
- Learning analyticsCh 41 §41.9
- Learning and plasticityCh 4 §4.4
- Learning efficiencyCh 26 §26.6 · Ch 30 §30.5
- Learning from experienceCh 2 §2.4 · Ch 23 §23.11
- Learning from instructionCh 2 §2.5
- Learning from limited experienceCh 28 §28.6
- Learning Theory Foundationssee Learning, Reasoning and Generalization
- Learning, Reasoning and GeneralizationFOUND-007
- Legal and ethical implicationsCh 61 §61.10
- Legal definitions of AICh 48 §48.1
- Legal Personhood for AIsee Moral Status and Personhood of AI
- Legal technologyCh 44 §44.2
- Legal uncertainty and emerging disputesCh 48 §48.12
- Lessons from historical AI forecastsCh 10 §10.8
- Lifelong Learningsee Continual Learning and Persistent Memory
- Limitations of current evaluation methodsCh 30 §30.11
- Limitations of symbolic approachesCh 9 §9.10
- Limits of automated software engineeringCh 40 §40.10
- Limits of brain-inspired computational modelsCh 4 §4.12
- Limits of current agent capabilitiesCh 20 §20.15
- Linear algebraCh 3 §3.6
- Lisp and specialized AI programmingCh 9 §9.6
- LLM Application Securitysee AI Security: Prompt Injection, Poisoning, Extraction
- LLM Hallucinationsee Hallucination, Reliability and Calibration
- LLM Multi-Agent Systemssee Multi-Agent Systems
- LLM Reasoning Capabilitysee Reasoning, Planning and Long-Horizon Capability
- LLMssee Large Language Models
- LMMssee Multimodal Foundation Models
- LogicGlossary
- Logic and Formal SystemsFOUND-011
- Logical reasoningCh 23 §23.3
- Logistics and transportationCh 43 §43.5
- Long Short-Term Memorysee Recurrent Networks and LSTM
- Long short-term memory (LSTM)Glossary
- Long short-term memory networksCh 12 §12.7
- Long-horizon taskGlossary
- Long-Run Consequences of Advanced AIsee Civilization and Advanced Intelligence
- Long-term planningCh 28 §28.3
- Long-term space explorationCh 63 §63.4
- Long-term survivalCh 62 §62.9
- Long-term technological developmentCh 62 §62.1
- Loss functionGlossary
- Loss functionsCh 18 §18.4
- Loss of human controlCh 35 §35.2
- LRMssee Reasoning Models and Test-Time Compute
- LSTMsee Recurrent Networks and LSTM
M
- Machine Consciousnesssee Philosophy of Mind and the Turing Test · PHIL-CONSC-001 · Ch 60
- Machine Consciousness and Semanticssee Consciousness and Machine Understanding
- Machine consciousness hypothesesCh 60 §60.9
- Machine Intelligencesee Artificial Intelligence · Ch 1 §1.5
- Machine intelligence beyond human comparisonCh 31 §31.8
- Machine LearningTECH-ML-001 · Ch 17 · Glossary
- Machine learning foundationsCh 58 §58.3
- Machine Learning Hardwaresee AI Hardware & Accelerator Systems
- Machine learning pioneersCh 55 §55.4
- Machine personhoodCh 61 §61.3
- Machine translationCh 8 §8.7
- Machine understandingCh 5 §5.11
- Major products and systemsCh 57 §57.3
- ManufacturingCh 43 §43.2
- Market concentrationCh 51 §51.8
- Market size and revenueCh 54 §54.2
- Marketing and salesCh 39 §39.4
- Markov decision process (MDP)Glossary
- MARLsee Multi-Agent Systems
- Marvin Lee Minskysee Marvin Minsky
- Marvin MinskyBIO-MINSKY-001
- Marvin Minsky and early AI researchCh 7 §7.7
- Materials scienceCh 37 §37.6
- Mathematical foundations of AICh 3 §3.1
- Mathematical logicCh 6 §6.6
- Mathematical Logic for AIsee Logic and Formal Systems
- Mathematical reasoningCh 23 §23.2
- MathematicsCh 37 §37.9
- Mathematics and LogicCh 3
- Measuring progress toward generalityCh 24 §24.15
- Measuring the AI EconomyECON-MEAS-001 · Ch 54
- Mechanical computationCh 6 §6.1
- Mechanistic interpretabilityCh 34 §34.8 · Glossary
- Mechanistic Interpretability (MI)see Interpretability and Mechanistic Interpretability
- Medical AIsee AI in Healthcare and Medicine
- Medical data privacyCh 38 §38.9
- Medical imagingCh 38 §38.1
- Medical roboticsCh 38 §38.7
- Medium- and Long-Term ScenariosFCST-SCEN-001 · Ch 66
- Membership inferenceCh 46 §46.5 · Glossary
- Memory and information retentionCh 2 §2.8
- Memory and information retrievalCh 23 §23.7
- Memory bandwidthCh 21 §21.3
- Memory formationCh 4 §4.5
- Mergers and acquisitionsCh 50 §50.10
- Mesa-optimizerGlossary
- Message-Passing Neural Networkssee Graph Neural Networks
- Meta-learningCh 17 §17.9
- MetacognitionCh 27 §27.9
- Metacognition and self-evaluationCh 2 §2.11
- Methodology for Comparing AI SystemsCAP-COMPARE-001
- Military and geopolitical instabilityCh 35 §35.5
- Mind uploading hypothesesCh 61 §61.6
- Misaligned autonomous systemsCh 35 §35.3
- MisalignmentGlossary
- MisuseGlossary
- Mitigation strategiesCh 35 §35.12
- Mixture of experts (MoE)Glossary
- Mixture-of-Experts ModelsTECH-MOE-001 · Ch 18 §18.15
- MLsee Machine Learning
- ML Safetysee Technical Safety and Robustness
- ML Securitysee AI Security: Prompt Injection, Poisoning, Extraction
- Model architectureCh 25 §25.1
- Model Calibrationsee Hallucination, Reliability and Calibration
- Model cardGlossary
- Model collapseGlossary
- Model Comparison Methodologysee Methodology for Comparing AI Systems
- Model Compressionsee Inference, Quantization and Efficiency
- Model documentationCh 59 §59.7
- Model efficiency and quantizationCh 14 §14.10
- Model Evaluationsee AI Evaluation, Benchmarking & Contamination
- Model extractionCh 46 §46.4 · Glossary
- Model Registrysee AI/SI Model Registry
- Model Release Strategiessee Open-Weight versus Closed Models
- Model selectionCh 17 §17.13
- Model Servingsee Inference, Quantization and Efficiency
- Model serving and inferenceCh 15 §15.8
- Model specializationCh 25 §25.13
- Model theftCh 46 §46.6
- Model weightsGlossary
- MoEsee Mixture-of-Experts Models
- Monitoring and containmentCh 34 §34.12
- Monitoring and early-warning indicatorsCh 35 §35.13
- Monitoring and incident detectionCh 45 §45.8
- Moore's lawGlossary
- Moral statusGlossary
- Moral Status and Personhood of AIPHIL-MIND-001
- Multi-agent approachesCh 27 §27.11
- Multi-Agent Reinforcement Learningsee Multi-Agent Systems
- Multi-agent systemGlossary
- Multi-Agent SystemsTECH-MARL-001 · Ch 20 §20.9
- Multi-step executionCh 20 §20.7
- Multilayer Perceptrons (as the canonical feedforward case)see Artificial Neural Networks
- Multimodal AICh 22 §22.10
- Multimodal Foundation ModelsTECH-MM-001 · Ch 14 §14.4 · Ch 19 §19.18
- Multimodal learningCh 13 §13.11
- Multimodal LLMssee Multimodal Foundation Models
- Multimodal modelGlossary
- Multimodal performanceCh 25 §25.4
- Music and audio generationCh 42 §42.4
- MYCINCh 9 §9.5
N
- Narrow AIGlossary
- Narrow versus General AIsee Categories of AI: Narrow, General, Symbolic, Statistical
- National AI capabilitiesCh 53 §53.1
- National AI strategiesCh 49 §49.1
- Natural language processingCh 19 §19.1
- Natural language processing (NLP)Glossary
- Natural Language Processing: A HistoryHIST-012
- Near-Term OutlookCh 65
- Near-Term Outlook (0-3 years)FCST-NEAR-001
- Network architecturesCh 18 §18.2
- Network infrastructureCh 52 §52.5
- Networking and interconnectsCh 21 §21.6
- Neural Attentionsee Attention Mechanisms
- Neural networkGlossary
- Neural Network Interpretabilitysee Interpretability and Mechanistic Interpretability
- Neural network researchersCh 55 §55.5
- Neural Networkssee Artificial Neural Networks
- Neural Program Synthesissee AI Code Generation
- Neural Scaling Lawssee Scaling Laws
- Neural signalingCh 4 §4.2
- Neuromorphic computingGlossary
- Neuroscience and artificial neural networksCh 4 §4.10
- Neuroscience Foundations of AIsee The Brain and Biological Neurons
- Neuroscience-inspired approachesCh 27 §27.12
- Neuroscientific perspectivesCh 60 §60.6
- Neurosymbolic AIGlossary
- Newell and Simonsee Allen Newell and Herbert Simon
- Nick BostromBIO-BOSTROM-001
- Niklas Boströmsee Nick Bostrom
- NIST AI Risk Management Frameworksee Standards Bodies (ISO/IEC, NIST)
- Nonprofit organizationsCh 56 §56.4
- Novel-task performanceCh 30 §30.3
- Numerical computationCh 15 §15.6
- Numerical methodsCh 3 §3.15
- Numerical Optimization for Machine Learningsee Optimization and Gradient Descent
O
- Objective functionGlossary
- Objective Specificationsee The AI Alignment Problem
- Online learningCh 17 §17.7
- OntologyGlossary
- Open Foundation Modelssee Open-Weight versus Closed Models
- Open technical problemsCh 34 §34.15
- Open-Source AIsee Open-Weight versus Closed Models
- Open-source and open-weight ecosystemsCh 50 §50.6
- Open-weight and proprietary systemsCh 22 §22.14
- Open-weight modelGlossary
- Open-weight modelsCh 14 §14.8
- Open-Weight versus Closed ModelsCAP-OPEN-001
- Open-weight versus closed-weight modelsCh 25 §25.12
- Operational criteria for AGICh 26 §26.10
- Operations researchCh 39 §39.9
- OptimizationGlossary
- Optimization and Gradient DescentFOUND-010
- Organizational transformationCh 39 §39.12
- Original research papersCh 59 §59.1
- Origins of AIsee Precursors to Artificial Intelligence
- Orthogonality thesisGlossary
- Out-of-distribution (OOD)Glossary
- Out-of-distribution behaviorCh 45 §45.5
- Outer alignmentGlossary
- Outer alignment and inner alignmentCh 34 §34.4
- OverfittingGlossary
- Overfitting and underfittingCh 17 §17.14
P
- Parallel computingCh 15 §15.4
- Parallel Distributed Processing Erasee Backpropagation and the Connectionist Revival
- Parallel Trainingsee Distributed Training
- ParameterGlossary
- Partnerships and acquisitionsCh 57 §57.6
- Patent activityCh 54 §54.9
- PatentsCh 59 §59.3
- Paths to ASIsee Pathways to Superintelligence
- Pathways to SuperintelligenceASI-PATH-001
- Perception and attentionCh 4 §4.6
- Perception and recognitionCh 23 §23.8
- PerceptronGlossary
- Performance across diverse domainsCh 28 §28.12
- Persistent memoryCh 27 §27.4 · Ch 28 §28.7
- Persistent technical bottlenecksCh 66 §66.7
- Personal identityCh 5 §5.10
- Personalized learningCh 41 §41.2
- Personalized medicineCh 38 §38.5
- Phenomenal consciousnessCh 60 §60.2
- Philosophers and critics of AICh 55 §55.11
- Philosophical definitions of artificial intelligenceCh 5 §5.12
- Philosophical questions about humanity's roleCh 36 §36.10
- Philosophy of AIsee Philosophy of Mind and the Turing Test
- Philosophy of Mind and IntelligenceCh 5
- Philosophy of Mind and the Turing TestFOUND-005
- Physical AIsee AI in Industry, Robotics and Autonomous Vehicles · see Robotics and Embodied AI
- Physical AI and embodied systemsCh 43 §43.11
- Physical Limits of Computationsee Computational Limits and AI Beyond Earth
- Physical limits on advanced computationCh 63 §63.9
- Physicalism and alternative philosophical positionsCh 5 §5.4
- PhysicsCh 37 §37.8
- Pioneers and Influential ResearchersCh 55
- PlanningGlossary
- Planning and decision-makingCh 20 §20.3
- Planning and long-horizon tasksCh 23 §23.6
- Planning and searchCh 27 §27.8
- Policy (reinforcement learning)Glossary
- Possible discontinuities in progressCh 32 §32.11
- Post-ChatGPT Erasee The Contemporary AI Era, 2022 onward (living record)
- Post-Human Machine Intelligencesee Artificial Superintelligence
- Post-Training of Language Modelssee Pretraining, Fine-Tuning and RLHF
- Postbiological Intelligencesee Computational Limits and AI Beyond Earth
- Potential Pathways to SuperintelligenceCh 32
- Power-seekingGlossary
- PRC AI Governancesee China's AI Regulation
- Pre-1956 Artificial Intelligencesee Precursors to Artificial Intelligence
- Precursors to Artificial IntelligenceHIST-001 · Ch 6
- Predicate logicCh 3 §3.3
- Prediction markets and their limitationsCh 64 §64.8
- Predictive AICh 22 §22.8
- Predictive World Modelssee World Models
- Preference optimizationCh 19 §19.9
- PretrainingCh 19 §19.7 · Glossary
- Pretraining, Fine-Tuning and RLHFTECH-ALIGN-001
- Primary Sources and Historical RecordsLIT-SOURCES-001 · Ch 59
- PrivacyCh 47 §47.3
- Privacy and Data Protection in AISAFE-PRIV-001
- Privacy-preserving data practicesCh 16 §16.12
- Privacy-Preserving Machine Learningsee Privacy and Data Protection in AI
- Probabilistic and Kernel Methods Erasee Statistical Machine Learning, 1980s-2000s
- Probabilistic Foundations of AIsee Probability, Statistics and Bayesian Inference
- Probabilistic graphical modelsCh 11 §11.9
- Probability theoryCh 3 §3.8
- Probability, Statistics and Bayesian InferenceFOUND-008
- Product liabilityCh 48 §48.3
- Productivity and workflow designCh 39 §39.2
- Productivity indicatorsCh 54 §54.5
- Productivity measurementCh 51 §51.11
- Programming and Computational FoundationsCh 15
- Programming languages for AICh 15 §15.1
- Prolog and logic programmingCh 9 §9.7
- PromptGlossary
- Prompt injectionCh 46 §46.2 · Glossary
- Prompting and instruction followingCh 19 §19.12
- Propensity Evaluationssee Dangerous Capability and Alignment Evaluations
- Propositional logicCh 3 §3.2
- Protein structure predictionCh 37 §37.4
- Protein Structure Prediction (AlphaFold)APP-PROT-001
- Public accountabilityCh 44 §44.10
- Public administrationCh 44 §44.1
- Public claims and independently verified capabilitiesCh 57 §57.8
- Public datasetsCh 59 §59.6
- Public healthCh 38 §38.8
- Public policy analysisCh 44 §44.5
- Public servicesCh 44 §44.3
Q
R
- RAGsee Retrieval-Augmented Generation
- Rapid but bounded progressCh 66 §66.2
- Rapid capability growthCh 66 §66.6
- Rational Choice Theorysee Game Theory and Decision Theory
- Reactive and deliberative agentsCh 20 §20.2
- Real-world task completionCh 24 §24.9
- ReasoningGlossary
- Reasoning and generalizationCh 68 §68.4
- Reasoning capabilitiesCh 25 §25.3
- Reasoning evaluationsCh 24 §24.6
- Reasoning from evidenceCh 2 §2.6
- Reasoning modelGlossary
- Reasoning Models and Test-Time ComputeTECH-REASON-001
- Reasoning-oriented modelsCh 14 §14.3
- Reasoning, Planning and Long-Horizon CapabilityCAP-REASON-001
- Recent AI Developments Logsee The Contemporary AI Era, 2022 onward (living record)
- Recurrent Networks and LSTMTECH-RNN-001
- Recurrent neural network (RNN)Glossary
- Recurrent Neural Networkssee Recurrent Networks and LSTM · Ch 12 §12.6 · Ch 18 §18.9
- Recurring patterns in technological hypeCh 10 §10.9
- Recursive improvementCh 68 §68.6
- Recursive Self-Improvementsee The Intelligence Explosion Hypothesis · Ch 33 §33.3 · Glossary
- Recursive self-improvement hypothesesCh 32 §32.5
- Red teamingGlossary
- Register of Documented Public AI Forecastssee Forecast Register
- Registry of Historically and Technically Significant AI Systemssee AI/SI Model Registry
- RegularizationCh 18 §18.7 · Glossary
- Regulation (EU) 2024/1689see The EU AI Act
- Regulation and governanceCh 65 §65.9
- Regulatory and institutional developmentsCh 67 §67.9
- Regulatory and legal developmentsCh 57 §57.9
- Regulatory enforcementCh 48 §48.11
- Reinforcement LearningTECH-RL-001 · Ch 11 §11.6 · Ch 17 §17.6
- Reinforcement learning (RL)Glossary
- Reinforcement Learning from Human Feedbacksee Pretraining, Fine-Tuning and RLHF
- Reinforcement learning from human feedback (RLHF)Glossary
- Reinforcement learning researchersCh 55 §55.7
- ReliabilityCh 25 §25.9
- Reliability and calibrationCh 23 §23.13
- Reliability and failure recoveryCh 20 §20.14
- Reliability engineeringCh 45 §45.2
- Reliability on long-horizon tasksCh 67 §67.2
- Reliability over extended tasksCh 30 §30.6
- Reliable reasoningCh 28 §28.2
- Reliable use of toolsCh 28 §28.10
- Reporting obligationsCh 48 §48.8
- Representation learningGlossary
- ReproducibilityCh 24 §24.12
- Reproducibility and validationCh 37 §37.13
- Reproducibility and version controlCh 15 §15.10
- Requirements for General IntelligenceAGI-REQ-001
- Research assistanceCh 41 §41.4
- Research automationCh 33 §33.4
- Research contributionsCh 57 §57.4
- Research ecosystemsCh 53 §53.3
- Research laboratoriesCh 50 §50.2
- Research LibraryLIB-001
- Research outputCh 54 §54.8
- Responsible AIsee AI Ethics, Bias and Fairness
- Retrieval-Augmented GenerationTECH-RAG-001 · Ch 14 §14.7 · Ch 19 §19.10
- Retrieval-augmented generation (RAG)Glossary
- Retrieval-Augmented Language Modelssee Retrieval-Augmented Generation
- Retrospective forecast evaluationCh 64 §64.10
- Returns on AI investmentCh 51 §51.10
- Reverse-Engineering Neural Networkssee Interpretability and Mechanistic Interpretability
- Reverse-Mode Automatic Differentiation (as applied to neural networks)see Backpropagation
- Reward hackingGlossary
- Reward misspecificationCh 34 §34.3
- Reward modelGlossary
- Rich Suttonsee Richard Sutton
- Richard S. Suttonsee Richard Sutton
- Richard SuttonBIO-SUTTON-001
- Risk modelingCh 39 §39.7
- Risk-based regulationCh 48 §48.6 · Glossary
- RLsee Reinforcement Learning
- RNNsee Recurrent Networks and LSTM
- Robot Learningsee Robotics and Embodied AI
- RoboticsCh 43 §43.3
- Robotics and Embodied AITECH-ROBOT-001
- Robotics and physical agencyCh 20 §20.13
- Robotics and physical AICh 65 §65.7
- RobustnessCh 45 §45.1 · Glossary
- Robustness testingCh 24 §24.10
- Robustness to Distribution Shiftsee Technical Safety and Robustness
- Robustness under distribution shiftCh 28 §28.5
- Routes to Superintelligencesee Pathways to Superintelligence
- Rule-Based Expert Systemssee Expert Systems (DENDRAL, MYCIN)
- Rule-based reasoningCh 9 §9.1
S
- Safety and securityCh 25 §25.10
- Safety standardsCh 48 §48.5
- SandbaggingGlossary
- ScaffoldingGlossary
- Scalable oversightCh 34 §34.10 · Glossary
- Scalable Oversight and CorrigibilitySAFE-OVERSIGHT-001
- Scalable Supervisionsee Scalable Oversight and Corrigibility
- Scaling advanced AI systemsCh 32 §32.1
- Scaling and compute constraintsCh 29 §29.6
- Scaling existing architecturesCh 27 §27.1
- Scaling lawGlossary
- Scaling LawsTECH-SCALE-001 · Ch 13 §13.7
- Scaling studiesCh 58 §58.7
- SchemingGlossary
- Scientific and philosophical uncertaintyCh 60 §60.10
- Scientific Approaches to AGICh 27
- Scientific automationCh 37 §37.12
- Scientific benchmarksCh 24 §24.8
- Scientific literature analysisCh 37 §37.1
- Scientific Pathways to AGIAGI-PATH-001
- Scientific problem-solvingCh 23 §23.4
- Score-Based Generative Modelssee Diffusion Models
- Search algorithmsCh 8 §8.2
- Secure deploymentCh 46 §46.10
- Self-attentionCh 13 §13.2
- Self-Attention (as a special case)see Attention Mechanisms
- Self-evaluation and correctionCh 27 §27.10
- Self-supervised learningCh 17 §17.5 · Glossary
- Semi-supervised learningCh 17 §17.4
- Semiconductor Export Controlssee Export Controls and AI Geopolitics
- Semiconductor manufacturersCh 50 §50.4
- Semiconductor productionCh 52 §52.1
- Semiconductor supply chainsCh 21 §21.14
- Seminal theoretical worksCh 58 §58.1
- SentienceGlossary
- Sequence-to-sequence learningCh 12 §12.10
- Set theoryCh 3 §3.5
- Shannon Information Theorysee Information Theory
- Shared safety infrastructureCh 49 §49.9
- Signals, Indicators and Inflection PointsFCST-SIGNALS-001 · Ch 67
- Simulated mindsCh 61 §61.5
- Singularity (technological)Glossary
- Situational awarenessGlossary
- Skill substitution and augmentationCh 51 §51.7
- Slow, moderate, and rapid development scenariosCh 33 §33.10
- Smart infrastructureCh 43 §43.8
- Soft Attentionsee Attention Mechanisms
- Software architectureCh 40 §40.5
- Software engineeringCh 15 §15.3 · Ch 23 §23.5
- Software Engineering Capability and EvaluationCAP-CODE-001
- Software improvement cyclesCh 33 §33.5
- Software testingCh 40 §40.2
- Sources of uncertaintyCh 29 §29.10
- Sparse Mixture of Expertssee Mixture-of-Experts Models
- Sparsely-Gated Mixture-of-Expertssee Mixture-of-Experts Models
- Spatial reasoningCh 23 §23.9
- Specialized AI chipsCh 21 §21.13
- Specification gamingGlossary
- Specification of objectivesCh 34 §34.2
- Speculative futures and their evidential statusCh 63 §63.10
- Speed and latencyCh 25 §25.7
- Standardized evaluationsCh 24 §24.3
- Standards and regulationsCh 59 §59.8
- Standards and technical interoperabilityCh 49 §49.3
- Standards Bodies (ISO/IEC, NIST)ORG-STANDARDS-001
- Standards organizationsCh 48 §48.10 · Ch 56 §56.6
- Statistical AICh 22 §22.5
- Statistical Machine Learningsee Machine Learning
- Statistical Machine Learning, 1980s-2000sHIST-007 · Ch 11
- Statistical pattern recognitionCh 11 §11.1
- StatisticsCh 3 §3.10
- Stochastic Gradient Descentsee Optimization and Gradient Descent
- Stochastic gradient descent (SGD)Glossary
- Strategic and scientific capabilitiesCh 31 §31.5
- Strategic partnershipsCh 50 §50.9
- Strategic stabilityCh 53 §53.10
- Strong AIGlossary
- Structured and unstructured dataCh 16 §16.5
- Stuart J. Russellsee Stuart Russell
- Stuart RussellBIO-RUSSELL-001
- Subword Tokenizationsee Tokenization and Embeddings
- Superhuman Intelligence: Criteria and Measurementsee Defining and Measuring Superintelligence
- Superhuman performance in specialized domainsCh 31 §31.2
- Superintelligencesee Artificial Superintelligence
- Supervised fine-tuningCh 19 §19.8
- Supervised learningCh 17 §17.2 · Glossary
- Supply chainsCh 39 §39.8
- Supply-chain concentrationCh 52 §52.6
- Supply-chain securityCh 46 §46.9
- Support vector machinesCh 11 §11.3
- Swarm Intelligencesee Collective and Animal Intelligence
- SWE-bench and Successorssee Software Engineering Capability and Evaluation
- SycophancyGlossary
- Symbol grounding problemGlossary
- Symbolic AICh 8 §8.1 · Ch 22 §22.4 · Glossary
- Symbolic AI researchersCh 55 §55.3
- Symbolic versus Connectionist AIsee Categories of AI: Narrow, General, Symbolic, Statistical
- Synthetic dataCh 14 §14.11 · Ch 16 §16.10 · Glossary
- Synthetic media and authenticityCh 42 §42.10
- Synthetic Phenomenologysee Machine Consciousness
- Systemic technological dependenceCh 35 §35.8
T
- TakeoffGlossary
- Talent migrationCh 53 §53.4
- Task decompositionCh 20 §20.6
- Task Time Horizonsee Reasoning, Planning and Long-Horizon Capability
- Technical reportsCh 59 §59.2
- Technical Safety and ReliabilityCh 45
- Technical Safety and RobustnessSAFE-ROBUST-001
- Technological dependenceCh 53 §53.9
- Technological singularity hypothesesCh 62 §62.7
- TensorGlossary
- Tensor processing units and other acceleratorsCh 21 §21.2
- Test-time computeGlossary
- Testing Claims of General IntelligenceAGI-TEST-001 · Ch 30
- Text generationCh 42 §42.1
- The AI Alignment ProblemSAFE-ALIGN-001
- The AI IndustryCh 50
- The AI Industry StructureECON-IND-001
- The AI Winters: Causes and LessonsHIST-004
- The AlexNet Momentsee The Deep Learning Breakthrough (2012)
- The alignment problemCh 34 §34.1
- The Birth of Artificial Intelligence, 1940s–1950sCh 7
- The Brain and Biological IntelligenceCh 4
- The Brain and Biological NeuronsFOUND-013
- The changing role of teachers and expertsCh 41 §41.11
- The Chinese Room argumentCh 5 §5.6
- The Contemporary AI Era, 2022 OnwardCh 14
- The Contemporary AI Era, 2022 onward (living record)HIST-011
- The Dartmouth Conferencesee The Dartmouth Workshop (1956)
- The Dartmouth Summer Research ProjectCh 7 §7.5
- The Dartmouth Workshop (1956)HIST-002
- The Deep Learning Breakthrough (2012)HIST-005
- The distribution of technological powerCh 36 §36.6
- The Economics of Compute and ScalingECON-COMP-001
- The emergence of electronic computersCh 7 §7.1
- The emergence of widely accessible generative AICh 13 §13.14
- The EU AI ActGOV-EU-001
- The first AI winterCh 10 §10.4
- The first expectations for machine intelligenceCh 7 §7.11
- The foundations of computational intelligenceCh 6 §6.11
- The foundations of modern generative AICh 12 §12.12
- The future of machine civilizationsCh 63 §63.8
- The future of workCh 62 §62.4
- The General Problem SolverCh 8 §8.4
- The ImageNet Breakthroughsee The Deep Learning Breakthrough (2012)
- The Imitation Gamesee Philosophy of Mind and the Turing Test
- The intelligence explosion conceptCh 33 §33.1
- The Intelligence Explosion HypothesisASI-EXP-001
- The knowledge acquisition problemCh 9 §9.9
- The limitations of early neural networksCh 10 §10.3
- The limits of current architecturesCh 68 §68.2
- The limits of defining intelligenceCh 1 §1.13
- The Logic TheoristCh 7 §7.9
- The mind-body problemCh 5 §5.1
- The Nature of Knowledge and LearningCh 2
- The Neural Network Revival of the 1980ssee Backpropagation and the Connectionist Revival
- The perceptronCh 8 §8.5
- The Perceptron Controversysee Early Symbolic AI & The Perceptron
- The Pretraining Erasee The Transformer and Foundation Model Era, 2017-2022
- The problem of subjective experienceCh 60 §60.8
- The protein folding problem (computational)see Protein Structure Prediction (AlphaFold)
- The relationship between scale and capabilityCh 68 §68.1
- The Requirements for General IntelligenceCh 28
- The return of statistical approachesCh 10 §10.7
- The second AI winterCh 10 §10.6
- The Singularitysee The Intelligence Explosion Hypothesis
- The Statistical Turn in AIsee Statistical Machine Learning, 1980s-2000s
- The Transformer and Foundation Model Era, 2017-2022HIST-010 · Ch 13
- The Transformer ArchitectureTECH-ARCH-001 · Ch 13 §13.1
- The Turing TestCh 5 §5.5 · Ch 7 §7.3
- The Uncertainties That Matter MostFCST-UNCERT-001 · Ch 68
- Theories of consciousnessCh 60 §60.4
- Threat modelingCh 46 §46.1
- Three-Year AI Outlooksee Near-Term Outlook (0-3 years)
- TokenGlossary
- TokenizationCh 19 §19.3 · Glossary
- Tokenization and EmbeddingsTECH-TOK-001
- Tool and permission boundariesCh 46 §46.8
- Tool integrationCh 25 §25.6
- Tool useCh 20 §20.4 · Ch 23 §23.10 · Glossary
- Tool-using AI agentsCh 14 §14.6
- Tool-Using Modelssee Autonomous AI Agents
- TPUGlossary
- Training Corporasee Training Data, Contamination and Provenance
- Training dataGlossary
- Training Data, Contamination and ProvenanceTECH-DATA-001
- Training methodologyCh 25 §25.2
- Training Parallelismsee Distributed Training
- Training stability and optimizationCh 18 §18.16
- Training, validation, and test datasetsCh 16 §16.7
- Transfer and adaptationCh 26 §26.5
- Transfer learningCh 13 §13.8 · Ch 17 §17.8 · Glossary
- Transfer of knowledgeCh 2 §2.10
- Transfer to unfamiliar domainsCh 30 §30.4
- Transformative economic changeCh 66 §66.9
- TransformerGlossary
- Transformer and foundation model researchersCh 55 §55.8
- Transformer Modelsee The Transformer Architecture
- Transformer researchCh 58 §58.5
- TransformersCh 18 §18.10
- TranslationCh 41 §41.6
- TransparencyCh 47 §47.5
- Tripwires and Early-Warning Indicators for AI Progresssee Signals, Indicators and Inflection Points
- Turing machineGlossary
- Turing testGlossary
U
- Ultraintelligencesee Artificial Superintelligence
- Uncertainty and incomplete informationCh 2 §2.12
- Uncertainty estimationCh 45 §45.7
- Uncertainty in long-term forecastingCh 68 §68.10
- UnderstandingGlossary
- Understanding in Artificial Systemssee Consciousness and Machine Understanding
- Understanding physical and social environmentsCh 28 §28.9
- United States AI PolicyGOV-US-001
- Universal Machine Intelligencesee Artificial General Intelligence
- University laboratoriesCh 56 §56.1
- Unsupervised learningCh 17 §17.3 · Glossary
- US AI Governancesee United States AI Policy
V
- VAEsee Autoencoders and Variational Autoencoders
- Value Alignmentsee The AI Alignment Problem · Glossary
- Variational Autoencodersee Autoencoders and Variational Autoencoders
- Variational autoencoder (VAE)Glossary
- Venture capital and investmentCh 50 §50.8
- Video generationCh 19 §19.17 · Ch 42 §42.3
- Vision transformer (ViT)Glossary
- Vision-Language Modelssee Multimodal Foundation Models