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@bridge2ai.bsky.socialOct 5, 2026, 5:44 PM

Two Bridge2AI Investigators receive the IEEE Innovation in Societal Infrastructure Award ๐Ÿ† Read more about our Investigators awarded for their leadership in privacy-preserving clinical research: bit.ly/4doccGq

#ArtificialIntelligence #BiomedicalInformatics #MedSky #MedAI #AISky #MLSky

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@antifocal.bsky.socialOct 5, 2026, 12:41 PM

When neighbouring elements scatter X-rays alike, ordered and disordered phases give near-identical powder patterns. People chose the targets and in the end re-analysed the patterns by hand.

Szymanski et al., Nature 624, 86 (2023)

Values are representative.

#MLSky #AIforScience #research

@betterthanrandom.substack.comOct 5, 2026, 9:24 AM

betterthanrandom.substack.com/p/do-ai-assi...

#databs #MLSky

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@antifocal.bsky.socialOct 4, 2026, 7:37 PM

People set the safe voltage range, chose the two plunger gates, designed the score and labelled every map. This was coarse tuning, not a qubit, with five runs per device.

Moon et al., Nature Communications 11, 4161 (2020)

Values are representative.

#MLSky #AIforScience #research

@antifocal.bsky.socialOct 3, 2026, 1:59 PM

People still polish the surface, set voltage, tilt and detector distance, then check any phase the model has not seen.

Kaufmann et al., Science 367, 564 (2020)

Values are representative.

#MLSky #AIforScience #research

@antifocal.bsky.socialOct 3, 2026, 1:55 PM

The detector loses the phase, so different profiles can fit one curve. The operator set bounds for every parameter. In a PTCDI-Cโ‚ˆ test, results below about 250 ร… scattered more.

Pithan et al., J. Synchrotron Rad. 30, 1064 (2023)

Values are representative.

#MLSky #AIforScience #research

@bridge2ai.bsky.socialOct 1, 2026, 6:20 PM

Join the CM4AI-AnVIL DREAM Challenge: Help pioneer in silico microscopy, build "virtual cells", and develop #GenerativeAI models for protein localization ๐Ÿš€ย 

๐Ÿ† Up to $25k cash + $40k GCP credits
๐Ÿ”— bit.ly/4AK1uE9

#AISky #MLSky #ArtificialIntelligence #BiomedicalInformatics #MedSky #MedAI #Genomics

CM4AI AnVIL CellMap Prediction DREAM Challenge A single human cellcontainsthousandsofproteintypes,eachpreciselypositionedtokeepthe cellaliveandworking.Whereaproteinisplacedandhowitmovesinthecellshapeseverything fromcellstructuretohowcellssenseandrespondtotheirenvironment.Yettodayโ€™simagingtools canvisualizeonlytensofproteinsinthesamecell.Weneedtechnologiesthatintegratesuchdata tolearnandsimulateproteinlocalization.Thiswillenableustobuildcompleteproteinmapsof cellsandmodelhowcellularproteinarchitectureshiftsinhealthanddisease. Helppioneerinsilicomicroscopyandbuildโ€œvirtualcellsโ€:jointhischallengeto developgenerativeAImodelsthatpredictwhereaproteinlocalizes,using referencemicroscopyimagesandtheproteinโ€™saminoacidsequenceasinput. WHEN PRIZES Starts CashGCPcredits October19,2026$25K$40K 1st Ends 2nd $15K$20K February1,2027$10K$10K 3rd JOINTHE CHALLENGE WEBSITE synapse.org/CM4AI_DREAM
@alxndrmlk.bsky.socialSep 29, 2026, 12:50 PM

Our new episode with Robert J. Reynolds is out now!

1/

#CausalSky #StatSky #EpiSky #MLSky

Square Causal Bandits Podcast thumbnail on a blue background. Large white text reads 'CAUSAL MODELS at NASA', with NASA in red. Alex Molak is on the left and Robert J. Reynolds on the right, with a grey astronaut figure between them. A caption at the bottom reads 'Robert Reynolds, PhD'.
@betterthanrandom.substack.comSep 29, 2026, 7:44 AM

betterthanrandom.substack.com/p/industry-r...

#databs #MLSky

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@antifocal.bsky.socialSep 29, 2026, 4:27 AM

๐Ÿ”ฌ ๐—–๐—ฎ๐—ป ๐—ฎ๐—ป ๐—”๐—œ ๐—ฎ๐—น๐—ถ๐—ด๐—ป ๐—ฎ๐—ป ๐—ฒ๐—น๐—ฒ๐—ฐ๐˜๐—ฟ๐—ผ๐—ป ๐—บ๐—ถ๐—ฐ๐—ฟ๐—ผ๐˜€๐—ฐ๐—ผ๐—ฝ๐—ฒ ๐—ฏ๐˜† ๐—น๐—ผ๐—ผ๐—ธ๐—ถ๐—ป๐—ด ๐—ฎ๐˜ ๐˜๐—ต๐—ฒ ๐—ถ๐—บ๐—ฎ๐—ด๐—ฒ ๐—ฎ๐—น๐—ผ๐—ป๐—ฒ?

Bayesian optimisation tuned a STEM on image contrast: 18 to 32 images per aberration.
Amorphous or drifting samples defeat it. People set region and bounds.

Values are representative.

#MLSky #AIforScience #research

Infographic titled AI tuned a STEM's lenses, cutting astigmatism from 12 to 2 nm. Subtitle: Bayesian optimisation changed the corrector settings and scored the contrast of each new image. A loop of four stations, 30 to 40 s per turn. 1, Set: lens and dial, change corrector settings. 2, Image: atom columns, scan the sample. 3, Score: a wide histogram marked sharp beside a narrow one marked blurred, contrast as variance. 4, Choose: a model curve with a dashed line at its peak, pick next setting. Centre: 18 to 32 images per aberration. People band: chose a clean, high-contrast region, set the search bounds per sample, picked the noise model, left third order to standard software. Figures: astigmatism 12 to 2 nm, checked by ptychography; axial coma 554 to 224 nm; 18 to 25 min per run against 68 s for a standard tableau. Bold line: The loop only works where the sample gives the image contrast worth sharpening. Source: Pattison et al., npj Comput. Mater. 11, 274 (2025).
@betterthanrandom.substack.comSep 28, 2026, 8:42 AM

betterthanrandom.substack.com/p/lets-build...

#databs #MLSky

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@alxndrmlk.bsky.socialSep 28, 2026, 8:30 AM

Last week I went to New York to talk to Robert J. Reynolds, PhD, for a new podcast series with @sobor.bsky.social and UBC.

Rob had quite a story to tell about his work with causal models at NASA.

#CausalSky #StatSky #MLSky

A New York City street selfie of two smiling men. A label reads 'This is Rob' with a red arrow pointing to the man on the left, Robert J. Reynolds, next to Alex Molak on the right. The NASA logo is in the bottom-left corner and the Causal Bandits Podcast logo is in the top-right.
@alxndrmlk.bsky.socialSep 27, 2026, 6:07 PM

We just sent today's issue of Causal Python Bi-Weekly.

Here's what's inside:

1/

#CausalSky #StatSky #EconSky #EpiSky #MLSky

Causal Python Bi-Weekly issue 180 thumbnail. Headline 'When the best recommendation is the one we hold back' with a portrait of Athanasios Vlontzos (Hologen, ex-Spotify), on making Spotify's recommender causal using holdback data already collected. Also inside: Hume, de Finetti and induction, with David Rohde on deferring to a machine, and UBC's causal AI cluster launching October 8 with a keynote by Robert J. Reynolds.
@antifocal.bsky.socialSep 26, 2026, 2:28 PM

๐Ÿ”ฌ ๐——๐—ผ๐—ฒ๐˜€ ๐—•๐—ฎ๐˜†๐—ฒ๐˜€๐—ถ๐—ฎ๐—ป ๐—ผ๐—ฝ๐˜๐—ถ๐—บ๐—ถ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ธ๐—ป๐—ผ๐˜„ ๐˜„๐—ต๐—ฒ๐—ฟ๐—ฒ ๐˜๐—ต๐—ฒ ๐—ฏ๐—ฒ๐˜€๐˜ ๐—ฟ๐—ฒ๐—ฐ๐—ถ๐—ฝ๐—ฒ ๐—ถ๐˜€?

Tested points plus uncertainty make a map; the next run goes where the score peaks.
Engineer first, algorithm last: $52,000 to target vs $105,000 alone.

Figures as reported.

#MLSky #AIforScience #research

Diagram titled How the next experiment gets chosen. The upper plot, The map, shows five tested points, a predicted curve and an uncertainty band, wide in the untested gap. The lower plot, The score, peaks inside that gap at the point marked next experiment. Labels: Exploit, go where the prediction is high. Explore, go where the band is wide. Card one, Benchmark of 5 materials datasets: finding 80% of the top 5% of 600 printed structures takes about 75 samples with one lengthscale per variable, 85 with a random forest model and 170 with one lengthscale for all. Card two, Plasma etch game with 11 parameters, simulated process: 105,000 dollars to target for a senior engineer alone, a median 52,000 dollars for engineer first, algorithm last. Dark bar: up to 8 times faster than random sampling; 13 of 300 algorithm-only runs beat the engineer; half the cost. Footer: People are strongest early in the search; the algorithm is strongest near a tight target.
@scilove.bsky.socialSep 26, 2026, 9:30 AM

๐Ÿ”ฅ Trending on SciLove today ๐Ÿ”ฅ

๐Ÿ”ฌ Adaptive deep reinforcement learning for personalized learning pathways
๐Ÿ‘ค Ruan & Lu, 2025
๐Ÿ“– Computers and Education: Artificial Intelligence

๐Ÿ”— https://www.scilove.app/article/10.1016/j.caeai.2025.100463

#MLSky #AcademicSky #AcademicChatter

@harvardmcb.bsky.socialSep 25, 2026, 4:33 PM

Tenure-Track Professor in Life Science and AI ๐Ÿ”ฌ ๐Ÿง  ๐Ÿงช๐Ÿงฌ #AcademicSky #higherEd #MLSky
www.mcb.harvard.edu/department/n... @neurovenki.bsky.social @[email protected] @mitpress.bsky.social @kempnerinstitute.bsky.social @harvardbrainsci.bsky.social

@antifocal.bsky.socialSep 24, 2026, 8:11 AM

๐Ÿ”ฌ Why does AI miss the small phase in your XRD pattern?

One network found 94% of single phases but only 64% of minor phases (10โ€“30 wt%).
Shifted peaks caused 48% of its errors.
Check the residual yourself.

Szymanski et al., Chem. Mater. 2021

#ChemSky #MaterialsScience #MLSky

Infographic titled Why AI misses the small phase in an XRD pattern. Section 1: a sketched diffraction pattern with four tall main-phase peaks and three small minor-phase peaks, circled as A, weak, near the noise; B, hidden under a main peak; C, shifted, strain moves it off its reference. Section 2, how often it is right on simulated test patterns: one phase alone 94%, main phase at 70 to 90 wt% 92%, minor phase at 10 to 30 wt% 64%. Section 3: 48% of its errors came from shifted peaks, as in C. Section 4, what a person checks: A, the residual after the main phase is fitted; B, overlaps, a shoulder on a main peak; C, shifts from strain or a solid solution. Footer: let the model read the main phases; check the small signals yourself. Source: Szymanski et al., Chemistry of Materials, 2021; newer models may do better.
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