Advanced AI-driven strategies
Designing, optimising and scaling machine learning trading systems that fund the wider research programme and stress-test our predictive methods against live markets.
Research
Studying the mechanics between subject and object_
We believe the interaction between mind and outcome holds the key to significant human advancement. Our programme is built to test that claim honestly, at scale, in public.
Library
Academic research
Reviews of the studies our protocols are built on — what the original work showed, where it is fragile, and what we do differently.
Focus areas
Three programmes, one dataset
Each programme contributes to the same MetaModel — and each is accountable to the same statistical standard.
Enhanced ARV protocol
Associative Remote Viewing rebuilt for the modern era: blinded targets, structured judging, large sample sizes and machine-assisted analysis of every session.
Decentralised organisation
Governance, contribution and reward encoded on-chain so the community shares in both the direction and the upside of the research.
Method
Rigour is the product
Extraordinary claims require ordinary, boring, repeatable process.
Pre-register
Hypothesis, sample size and analysis plan are fixed and timestamped before a single session runs.
Run blinded
Participants, judges and analysts are separated. Targets are selected after the judgement is locked.
Analyse openly
Effect sizes, confidence intervals and null results are published alongside the raw, anonymised data.
100%
Sessions pre-registered
2x
Independent judging
Open
Null results published
Anon
Participant data
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The day science begins to study non-physical phenomena, it will make more progress in one decade than in all the previous centuries of its existence.
Research at Implausible is exploratory. We publish what we find, including when we find nothing. No result presented here should be read as investment advice or as a settled scientific claim.
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We're building a democratised platform to harness the power of psi, artificial intelligence and machine learning.