_adamr_1's profile picture. AI researcher and founder | prev ML PhD candidate at Sorbonne U

Adam

@_adamr_1

AI researcher and founder | prev ML PhD candidate at Sorbonne U

Adam reposted

♟️♟️Now our work on teaching superhuman chess strategies to grandmasters (one of whom @DGukesh who became the latest and the youngest world chess champion) is published on PNAS! 🎉🎉 Yes, we can transfer machine knowledge to humans to push the frontier of human. knowledge.…

Excited to share that our paper "Bridging the human–AI knowledge gap through concept discovery and transfer in AlphaZero" is now out in PNAS! With @weballergy, @banburismus_, @demishassabis, @ulrichpaquet, @_beenkim 🎉 📄 doi.org/10.1073/pnas.2…



Very impressed by the improvements brought by OpenAI’s o1 but it seems that some basic questions will always remain at the frontier of what LLMs can do

_adamr_1's tweet image. Very impressed by the improvements brought by OpenAI’s o1 but it seems that some basic questions will always remain at the frontier of what LLMs can do

How to be sure that ML model updates do not carry on unexpected changes in predictions? Introducing Deltaxplainer, a dynamic XAI approach to explain why two ML classifiers are different Paper at DynXAI workshop at ECML-PKDD 2023 Link in my bio (exploratory notebook included)

_adamr_1's tweet image. How to be sure that ML model updates do not carry on unexpected changes in predictions?

Introducing Deltaxplainer, a dynamic XAI approach to explain why two ML classifiers are different

Paper at DynXAI workshop at ECML-PKDD 2023
 
Link in my bio (exploratory notebook included)

Introducing Temporal Augmented Retrieval (TAR) TAR is an open source advanced RAG approach that aims to factor in the dynamic aspect of text data for retrieval It allows to study the evolution of discussed topics overtime Link in my bio Built during @_buildspace n&w s4

_adamr_1's tweet image. Introducing Temporal Augmented Retrieval (TAR)

TAR is an open source advanced RAG approach that aims to factor in the dynamic aspect of text data for retrieval

It allows to study the evolution of discussed topics overtime

Link in my bio
Built during @_buildspace n&w s4

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