Tessera
Folgen

Luis Lopez

@lglopez.bsky.social

Postdoctoral Researcher at the Munich Center for Mathematical Philosophy (MCMP) - LMU Munich (https://shorturl.at/4XROY)

12 Posts162 Follower159 Folgt
Simon Lohse@simonlohse.bsky.social · last mo.

Update: I’m co-editing a special issue of @jgps.bsky.social on “Comparative Philosophy of Science” (i.e. the systematic comparison of scientific fields and practices from a philosophical perspective) together with @karimbschir.bsky.social #philsci #HPS #HOPOS philevents.org/event/show/1...

EXTENDED DEADLINE - Towards Comparative Philosophy of Science (Special Issue of the Journal for General Philosophy of Science)

CALL FOR PAPERS: Towards Comparative Philosophy of Science (Special Issue of the Journal for General Philosophy of Science) Guest editors: Simon Lohse (Nijmegen) & Karim Bschir (St....

philevents.org

Al Wilson@modalizing.bsky.social · 2mo ago

Hello philosophers - I've written an introduction to philosophy of physics (100K words) for Routledge. I'll be finalizing it around end of summer and am keen to take soundings as to how it could be made more useful for students and teachers. Please comment below if you'd like a copy of the MS!

LMU Munich Philosophy Faculty@lmuphilosophy.bsky.social · 2mo ago

A great Faculty Research Day last Friday: excellent talks, inspiring posters, and many conversations across different areas of philosophy. A good reminder of how much interesting work is happening around us. Thanks to everyone who contributed, and to the Siemens Stiftung for the warm hospitality.

Bild
Cassandra Yang@cassandrazieyang.bsky.social · 3mo ago

How should models across scales be connected and evaluated? Who gets explanatory priority — the tissue or the cell? What challenges do imaging and sequencing techniques bring to data alignment? We are hosting a one-day philosophy of biology workshop in Cambridge to address exactly these questions:

Bild
David Colaço@davidcolaco.bsky.social · 6mo ago

As a final reminder, the deadline for commentary proposals for our BBS target article, "Metabolic considerations for cognitive modeling," is next Tuesday, February 3. For details, follow the link. Please share if you can @phaueis.bsky.social #philsci #cogsky #CognitiveNeuroscience

Call for Commentary Proposals - Metabolic considerations for cognitive modeling

Call for Commentary Proposals - Metabolic considerations for cognitive modeling

cambridge.org

Minnesota Center for Philosophy of Science@mcps-philsci.bsky.social · 7mo ago

Looking forward to welcoming Edoardo Peruzzi(Leibniz University Hannover) to our first International Postdoc Forum of 2026! Edoardo will present "Formal template accumulation, unification&scientific progress". 4 Feb 12:15 pm CST (UTC -6). @unihannover.bsky.social Zoom link online:

Spring 2026 International Postdoctoral Forum

Edoardo Peruzzi, from the Institute of Philosophy at the Leibniz University Hannover, will discuss "Formal template accumulation, unification and scientific progress."

buff.ly

Stephan Hartmann@stephanhartmann.bsky.social · 7mo ago

Great Research Day of my Faculty at the Siemens Stiftung on Friday: excellent talks by Hannes Leitgeb, Andrew Stephenson, Christof Rapp, Ignacio Ojea Quintana, and Thomas Oehl, plus a PhD poster session and a discussion on AI in philosophy led by Sven Nyholm. Thanks to all who contributed.

Bild
Sabina Leonelli@sabinaleonelli.bsky.social · 9mo ago

The call for applications for 2026 European Advanced School in Philosophy of Life Sciences is now open! Deadline 15 Jan 2026, theme will be “philosophy of biology for a healthy planet”, all info here: www.kli.ac.at/en/events/ev... graduate students &early postdocs, do consider joining us! #philsci

Events | Event Calendar | Discover The KLI

The Konrad Lorenz Institute provides a stimulating and creative environment for fellows, visiting scholars, students, and external faculty.

kli.ac.at

Daniel Kostic@danielkostic.bsky.social · 10mo ago

Our paper "Large physics models: towards a collaborative approach with large language models and foundation models" is now published online! @philsci.bsky.social @epsaphilsci.bsky.social @hoposjournal.bsky.social @ishpssb.bsky.social @henkderegt.bsky.social @lglopez.bsky.social

Large physics models: towards a collaborative approach with large language models and foundation models - The European Physical Journal C

This paper explores the development and evaluation of physics-specific large-scale AI models, which we refer to as large physics models (LPMs). These models, based on foundation models such as large language models (LLMs) are tailored to address the unique demands of physics research. LPMs can function independently or as part of an integrated framework. This framework can incorporate specialized tools, including symbolic reasoning modules for mathematical manipulations, frameworks to analyse specific experimental and simulated data, and mechanisms for synthesizing insights from physical theories and scientific literature. We begin by examining whether the physics community should actively develop and refine dedicated models, rather than relying solely on commercial LLMs. We then outline how LPMs can be realized through interdisciplinary collaboration among experts in physics, computer science, and philosophy of science. To integrate these models effectively, we identify three key pillars: Development, Evaluation, and Philosophical Reflection. Development focuses on constructing models capable of processing physics texts, mathematical formulations, and diverse physical data. Evaluation assesses accuracy and reliability through testing and benchmarking. Finally, Philosophical Reflection encompasses the analysis of broader implications of LLMs in physics, including their potential to generate new scientific understanding and what novel collaboration dynamics might arise in research. Inspired by the organizational structure of experimental collaborations in particle physics, we propose a similarly interdisciplinary and collaborative approach to building and refining large physics models. This roadmap provides specific objectives, defines pathways to achieve them, and identifies challenges that must be addressed to realise physics-specific large scale AI models.

link.springer.com