Pith. sign in

REVIEW 1 cited by

Leveraging Large Language Models and Social Media for Automation in Scanning Probe Microscopy

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2405.15490 v1 pith:SU25HAWY submitted 2024-05-24 physics.app-ph cond-mat.mes-hall

classification physics.app-phcond-mat.mes-hall
keywords integrationlanguagellmsmicroscopyprobescanningsocialsystem
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We present the development of an automated scanning probe microscopy (SPM) measurement system using an advanced large-scale language model (LLM). This SPM system can receive instructions via social networking services (SNS), and the integration of SNS and LLMs enables real-time, language-agnostic control of SPM operations, thereby improving accessibility and efficiency. The integration of LLMs with AI systems with specialized functions brings the realization of self-driving labs closer.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Generative AI Uses and Risks for Knowledge Workers in a Science Organization

    cs.HC 2025-01 accept novelty 5.0 of 10

    At Argonne National Lab, early adopters of generative AI reported copilot and workflow agent use cases, small but growing usage, and concerns about reliability, privacy, academic publishing, and jobs.

Pith tools