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Conjecture

Safety Org

Conjecture

Conjecture is a 30-40 person London-based AI safety org founded 2022, pursuing Cognitive Emulation (CoEm) - building interpretable AI from ground-up rather than aligning LLMs - with $30M+ Series A funding. Founded by Connor Leahy (EleutherAI), they face high uncertainty about CoEm competitiveness (3-5 year timeline) and commercial pressure risks.

TypeSafety Org
Founded2022
LocationLondon, UK
Related
People
Connor LeahyVidur KapurConnor Leahy
Organizations
AnthropicRedwood ResearchUK AI Safety InstituteControlAI
Safety Agendas
Prosaic Alignment
1.6k words · 8 backlinks

Overview

Conjecture is an AI safety research organization founded in 2022 by Connor Leahy and a team of researchers concerned about existential risks from advanced AI. The organization pursues a distinctive technical approach centered on "Cognitive Emulation" (CoEm) - building interpretable AI systems based on human cognition principles rather than aligning existing large language models.

Based in London with a team of 30-40 researchers, Conjecture raised over $10M in Series A funding in 2023. Their research agenda emphasizes mechanistic interpretability and understanding neural network internals, representing a fundamental alternative to mainstream prosaic alignment approaches pursued by organizations like Anthropic and OpenAI.

AspectAssessmentEvidenceSource
Technical InnovationHighNovel CoEm research agendaConjecture Blog
Funding SecurityStrong$30M+ Series A (2023)TechCrunch Reports
Research OutputModerateSelective publication strategyResearch Publications
InfluenceGrowingEuropean AI policy engagementUK AISI

Risk Assessment

Risk CategorySeverityLikelihoodTimelineTrend
CoEm UncompetitiveHighModerate3-5 yearsUncertain
Commercial Pressure CompromiseMediumHigh2-3 yearsWorsening
Research InsularityLowModerateOngoingStable
Funding SustainabilityMediumLow5+ yearsImproving

Founding and Evolution

Origins (2022)

Conjecture emerged from the EleutherAI collective, an open-source AI research group that successfully recreated GPT-3 as open-source models (GPT-J, GPT-NeoX). Key founding factors:

FactorImpactDetails
EleutherAI ExperienceHighDemonstrated capability replication feasibility
Safety ConcernsHighRecognition of risks from capability proliferation
European GapMediumLimited AI safety ecosystem outside Bay Area
Funding AvailabilityMediumGrowing investor interest in AI safety

Philosophical Evolution: The transition from EleutherAI's "democratize AI" mission to Conjecture's safety-focused approach represents a significant shift in thinking about AI development and publication strategies.

Funding Trajectory

YearFunding StageAmountImpact
2021SeedUndisclosedInitial team of ≈15 researchers
2023Series A$30M+Scaled to 30-40 researchers
2024OperatingOngoingSustained research operations

Cognitive Emulation (CoEm) Research Agenda

Research Areas

No data available.

Core Philosophy

Conjecture's signature approach contrasts sharply with mainstream AI development:

ApproachPhilosophyMethodsEvaluation
Prosaic AlignmentTrain powerful LLMs, align post-hocRLHF, Constitutional AIBehavioral testing
Cognitive EmulationBuild interpretable systems from ground upHuman cognition principlesMechanistic understanding

Key Research Components

Mechanistic Interpretability

  • Circuit discovery in neural networks
  • Feature attribution and visualization
  • Scaling interpretability to larger models
  • Interpretability research collaboration

Architecture Design

  • Modular systems for better control
  • Interpretability-first design choices
  • Trading capabilities for understanding
  • Novel training methodologies

Model Organisms

  • Smaller, interpretable test systems
  • Alignment property verification
  • Deception detection research
  • Goal representation analysis

Key Personnel

Key People

No data available.

Leadership Team

Connor Leahy
CEO and Co-founder
EleutherAI, autodidact ML researcher
Sid Black
Co-founder
EleutherAI technical researcher
Gabriel Alfour
CTO
Former Tezos CTO, systems engineering

Connor Leahy Profile

AspectDetails
BackgroundEleutherAI collective member, GPT-J contributor
EvolutionFrom open-source advocacy to safety-focused research
Public RoleActive AI policy engagement, podcast appearances
ViewsShort AI timelines, high P(doom), interpretability-necessary

Timeline Estimates: Leahy has consistently expressed short AI timeline views, suggesting AGI within years rather than decades.

Research Focus Areas

Mechanistic Interpretability

Research AreaStatusKey Questions
Circuit AnalysisActiveHow do transformers implement reasoning?
Feature ExtractionOngoingWhat representations emerge in training?
Scaling MethodsDevelopmentCan interpretability scale to AGI-level systems?
Goal DetectionEarlyHow can we detect goal-directedness mechanistically?

Comparative Advantages

OrganizationPrimary FocusInterpretability Approach
ConjectureCoEm, ground-up interpretabilityDesign-time interpretability
AnthropicFrontier models + interpretabilityPost-hoc analysis of LLMs
ARCTheoretical alignmentEvaluation and ELK research
RedwoodAI controlInterpretability for control

Strategic Position

Theory of Change

Conjecture's pathway to AI safety impact:

  1. Develop scalable interpretability techniques for powerful AI systems
  2. Demonstrate CoEm viability as competitive alternative to black-box scaling
  3. Influence field direction toward interpretability-first development
  4. Inform governance with technical feasibility insights
  5. Build safe systems using CoEm principles if successful

European AI Safety Hub

RoleImpactExamples
Geographic DiversityHighAlternative to Bay Area concentration
Policy EngagementGrowingUK AISI consultation
Talent DevelopmentModerateEuropean researcher recruitment
Community BuildingEarlyWorkshops and collaborations

Challenges and Criticisms

Technical Feasibility

ChallengeSeverityStatus
CoEm CompetitivenessHighUnresolved - early stage
Interpretability ScalingHighActive research question
Human Cognition ComplexityMediumOngoing investigation
Timeline AlignmentHighCritical if AGI timelines short

Organizational Tensions

Commercial Pressure vs Safety Mission

  • VC funding creates return expectations
  • Potential future deployment pressure
  • Comparison to Anthropic's commercialization path

Publication Strategy Criticism

  • Shift from EleutherAI's radical openness
  • Selective research sharing decisions
  • Balance between transparency and safety

Current Research Outputs

Published Work

TypeFocusImpact
Technical PapersInterpretability methodsResearch community
Blog PostsCoEm explanationsPublic understanding
Policy ContributionsTechnical feasibilityGovernance decisions
Open Source ToolsInterpretability softwareResearch ecosystem

Research Questions

Key Questions

  • ?Can CoEm produce AI systems competitive with scaled LLMs?
  • ?Is mechanistic interpretability sufficient for AGI safety verification?
  • ?How will commercial pressures affect Conjecture's research direction?
  • ?What role should interpretability play in AI governance frameworks?
  • ?Can cognitive emulation bridge neuroscience and AI safety research?
  • ?How does CoEm relate to other alignment approaches like Constitutional AI?

Timeline and Risk Estimates

Leadership Risk Assessments

Conjecture's leadership has articulated clear views on AI timelines and safety approaches, which fundamentally motivate their Cognitive Emulation research agenda and organizational strategy:

Expert/SourceEstimateReasoning
Connor LeahyAGI: 2-10 yearsLeahy has consistently expressed short AI timeline views across multiple public statements and podcasts from 2023-2024, suggesting transformative AI systems could emerge within years rather than decades. These short timelines create urgency for developing interpretability-first approaches before AGI arrives.
Connor LeahyP(doom): High without major changesLeahy has expressed significant concern about the default trajectory of AI development in 2023 statements, arguing that prosaic alignment approaches pursued by frontier labs are insufficient to ensure safety. This pessimism about conventional alignment motivates Conjecture's alternative CoEm approach.
Conjecture ResearchProsaic alignment: InsufficientThe organization's core research direction reflects a fundamental assessment that post-hoc alignment of large language models through techniques like RLHF and Constitutional AI cannot provide adequate safety guarantees. This view, maintained since founding, drives their pursuit of interpretability-first system design.
OrganizationInterpretability: Necessary for safetyConjecture's founding premise holds that mechanistic interpretability is not merely useful but necessary for AI safety verification. This fundamental research assumption distinguishes them from organizations pursuing behavioral safety approaches and shapes their entire technical agenda.

Future Scenarios

Research Trajectory Projections

TimelineOptimisticRealisticPessimistic
2-3 yearsCoEm demonstrations, policy influenceContinued interpretability advancesCommercial pressure compromises
3-5 yearsCompetitive interpretable systemsMixed results, partial successResearch agenda stagnates
5+ yearsField adoption of CoEm principlesPortfolio contribution to safetyMarginalized approach

Critical Dependencies

FactorImportanceUncertainty
Technical FeasibilityCriticalHigh - unproven at scale
Funding ContinuityHighMedium - VC expectations
AGI TimelineCriticalHigh - if very short, insufficient time
Field ReceptivityMediumMedium - depends on results

Relationships and Collaborations

Within AI Safety Ecosystem

OrganizationRelationshipCollaboration Type
AnthropicFriendly competitionInterpretability research sharing
ARCComplementaryDifferent technical approaches
MIRIAligned concernsSkepticism of prosaic alignment
Academic LabsCollaborativeInterpretability technique development

Policy and Governance

UK Engagement

  • UK AI Safety Institute consultation
  • Technical feasibility assessments
  • European AI Act discussions

International Influence

  • Growing presence in global AI safety discussions
  • Alternative perspective to US-dominated discourse
  • Technical grounding for governance approaches

Sources & Resources

Primary Sources

TypeSourceDescription
Official WebsiteConjecture.devResearch updates, team information
Research PapersGoogle ScholarTechnical publications
Blog PostsConjecture BlogResearch explanations, philosophy
InterviewsConnor Leahy TalksLeadership perspectives

Secondary Analysis

TypeSourceFocus
AI Safety AnalysisLessWrong PostsCommunity discussion
Technical ReviewsAlignment ForumResearch evaluation
Policy ReportsGovAI AnalysisGovernance implications
Funding NewsTechCrunch CoverageBusiness developments
TopicInternal LinksExternal Resources
InterpretabilityTechnical InterpretabilityAnthropic Interpretability
Alignment ApproachesWhy Alignment is HardAI Alignment Forum
European AI PolicyUK AISIEU AI Office
Related OrgsSafety OrganizationsAI Safety Community

References

This appears to be a Google Scholar citations profile page for Conjecture, an AI safety research organization focused on cognitive emulation and interpretability. The page requires authentication to view full citation details, limiting direct access to research metrics and publication lists.

★★★★☆
2Research Publicationsconjecture.dev

Conjecture's research hub presents their primary safety agenda centered on Cognitive Emulation (CoEm), an AI architecture designed to bound system capabilities and make reasoning interpretable and controllable. Rather than directly solving alignment for AGI, they propose building predictably boundable intermediate systems as a simpler near-term step. The page indexes key publications including their foundational CoEm proposal, a roadmap for 'Cognitive Software,' and cross-organizational alignment discussions.

3AI Alignment ForumAlignment Forum·Blog post

The AI Alignment Forum is a central community platform for technical AI safety and alignment research discussion. The featured post argues against 'reductive utility' (utility functions over possible worlds) and proposes the Jeffrey-Bolker framework as an alternative that avoids ontological crises and computability constraints by grounding preferences in agent-relative events rather than universal physics.

★★★☆☆

This is a TechCrunch tag aggregation page for 'conjecture,' but based on the visible content it appears to contain only unrelated older hardware articles (MacBooks, gPhone) rather than content about Conjecture, the AI safety organization. The page does not surface meaningful AI safety coverage.

★★★☆☆

This URL returns a 404 error, indicating the Conjecture blog has moved or been restructured. Conjecture is an AI safety company focused on cognitive emulation and interpretability research. Their content is now accessible via their research page at conjecture.dev/research.

A YouTube search results page aggregating talks and interviews by Connor Leahy, co-founder of EleutherAI and CEO of Conjecture, on AI safety topics. Leahy is a prominent voice warning about existential risks from advanced AI systems and advocates for strong alignment research and governance measures. The collection covers his views on AI risk, alignment strategies, and the urgency of solving safety before AGI.

★★☆☆☆
7AI Safety Institute - GOV.UKUK Government·Government

The UK AI Safety Institute (recently rebranded as the AI Security Institute) is a government body under the Department for Science, Innovation and Technology focused on minimizing risks from rapid and unexpected AI advances. It conducts and publishes safety research, international coordination reports, and policy guidance, while managing grants for systemic AI safety research.

★★★★☆

AISafety.info is a community hub providing accessible introductions, explainers, and curated resources on AI safety topics. It serves as an entry point for those new to the field as well as a reference for practitioners, covering technical safety, alignment concepts, and related research areas.

9TechCrunchTechCrunch

TechCrunch is a major technology news outlet covering startups, industry trends, and emerging technologies. It occasionally reports on AI safety, alignment, and governance topics as they intersect with the broader tech industry.

★★★☆☆

Conjecture is an AI safety research company focused on cognitive emulation (CoEm) as an approach to building aligned AI systems. Their blog covers technical AI safety research, interpretability, and alignment strategies with a particular emphasis on making AI systems that reason more like humans in interpretable ways.

11Conjecture - LessWrong Tag PageLessWrong·Blog post

This is the LessWrong tag page aggregating posts related to Conjecture, an AI safety research organization focused on cognitive emulation (CogEm) and interpretability approaches to alignment. Conjecture's work explores building AI systems whose reasoning processes are understandable and human-like rather than opaque.

★★★☆☆

The Centre for the Governance of AI (GovAI) is a leading research organization dedicated to helping decision-makers navigate the transition to a world with advanced AI. It produces rigorous research on AI governance, policy, and societal impacts, while fostering a global talent pipeline for responsible AI oversight. GovAI bridges technical AI safety concerns with practical policy recommendations.

★★★★☆

The EU AI Office is the European Commission's central body responsible for overseeing and implementing the EU AI Act, particularly for general-purpose AI models. It coordinates AI governance across member states, enforces compliance with AI safety requirements, and supports the development of AI standards and testing methodologies.

★★★★☆

Structured Data

7 factsView in FactBase →
Total Funding Raised
$25 million
as of Dec 2022
Founded Date
Mar 2022

All Facts

7
Organization
PropertyValueAs OfSource
Founded DateMar 2022
HeadquartersLondon, UK
Legal StructurePrivate company
Financial
PropertyValueAs OfSource
Total Funding Raised$25 millionDec 2022
People
PropertyValueAs OfSource
Founded ByConnor Leahy,Sid Black,Gabriel Alfour
Biographical
PropertyValueAs OfSource
Wikipediahttps://en.wikipedia.org/wiki/Conjecture
General
PropertyValueAs OfSource
Websitehttps://www.conjecture.org

Related Wiki Pages

Top Related Pages

Safety Research

Prosaic AlignmentAnthropic Core Views

Approaches

AI AlignmentAI EvaluationAI Safety Training ProgramsConstitutional AI

Analysis

Model Organisms of MisalignmentCapability-Alignment Race Model

Other

Vidur KapurAI ControlInterpretability

Key Debates

Why Alignment Might Be HardAI Alignment Research AgendasTechnical AI Safety Research

Concepts

Large Language ModelsAGI TimelineSafety Orgs Overview

Organizations

OpenAI

Risks

AI ProliferationDeceptive Alignment