TabPFN is a foundation model trained on around 130,000,000 synthetically generated datasets that mimic “real world” tabular data. These datasets sampled dataset size and number
Tag: artificial intelligence
A recent paper published in Nature caught my eye, Accurate predictions on small data with a tabular foundation model by Hollmann et al., Here we present
A very nice review of generative models for molecular design from Morgan Thomas. https://cheminformantics.blogspot.com/2024/12/structure-aware-generative-molecular.html Includes Jupyter notebooks for data and analysis.
The CICAG Newsletter, which had its origins in the 1990s (when CICAG was two groups, the ‘Chemical Information Group’ and the ‘Computer Applications Subject Group’).
An interesting publication, using the IUPAC rules for naming compounds can be a challenge for for complex systems. This paper describes a transformer-based model https://doi.org/10.1186/s13321-024-00941-x
Apple are offering bounties for identification of vulnerabilities in their private cloud compute (PCC). PCC fulfills computationally intensive requests for Apple Intelligence, details are available
We have just got the results of the feedback from the 7th RSC-CICAG / RSC-BMCS Artificial Intelligence in Chemistry held at Churchill College in September.
This weeks WWDC gave details of upgrades to the various operating systems. Great to see the calculator make it to the iPad at last, the
When AlphaFold was originally published by Google/Deepmind it was a step change in predicting protein 3D structures and it sparked an upsurge in activity around
Whilst everyone is waiting for the WWDC 2024 and the latest plans from Apple to integrate more “AI”. I thought it might be amusing to