Chronological feed of everything captured from Reid Hoffman.
paper / reid-hoffman / Jun 6
Using Hamiltonian Monte Carlo forward reconstruction constrained by the Cosmicflows-4 galaxy distance and velocity dataset, researchers mapped the gravitational basins of attraction in the local cosmic volume. The Sloan Great Wall emerges not only as a prominent large-scale structure in redshift surveys but as the dominant gravitational sink in the region, anchoring a basin of attraction spanning ~0.13c in diameter — the largest identified in the study volume. The work provides probabilistic density and velocity fields within a ΛCDM framework, with uncertainty estimates propagated from both observational noise and model stochasticity, and explores the spatial relationship of the Ho'oleilana baryon acoustic oscillation feature to this basin.
cosmologylarge-scale-structuregalaxy-dynamicsvelocity-fieldsbaryon-acoustic-oscillationcosmicflowsgravitational-potential
“The Sloan basin of attraction is the largest basin in the study region, with a diameter of approximately 0.13c (~390 Mpc/h).”
paper / reid-hoffman / Jun 6
This study benchmarks ten machine learning algorithms for in-season crop type mapping using Harmonized Landsat-Sentinel surface reflectance time series and crop rotation history, targeting corn in Iowa and almonds in California at 30m resolution. Using year-wise cross-validation across thousands of model configurations, Support Vector Machines emerged as the top-performing algorithm, achieving mean F1 scores of 0.74 for almonds and 0.59 for corn by early June — before harvest. The work directly addresses a gap in USDA capabilities, where no pre-harvest product currently exists with sufficient accuracy for real-time emergency response to crop threats. Interannual variability was identified as the dominant uncertainty source, with ensemble methods and ancillary data flagged as promising paths to further gains.
machine-learningremote-sensingcrop-mappingfood-securitysatellite-imagerygeospatial-aiagriculture
“Support Vector Machines achieved the highest overall performance among ten ML algorithms for pre-harvest crop mapping, with a mean F1 score of 0.74 for almonds in California and 0.59 for corn in Iowa by early June.”
paper / reid-hoffman / Jun 6
Network misconfigurations are a leading cause of Internet outages, and while LLMs have been explored for automated repair, standalone models consistently fail on large-scale, complex scenarios and often introduce new errors. This paper benchmarks open- and closed-source LLMs augmented with formal network verification and context retrieval tools in an agentic architecture. The agentic setup achieves an average 12% improvement in repair efficacy and 17% improvement in safety over base LLMs, driven by dynamic context management and iterative validation loops.
agentic-aillm-applicationsnetwork-configurationai-evalsformal-verificationnetwork-reliability
“Agentic LLM architectures outperform base LLMs in network configuration repair efficacy by 12% on average.”
paper / reid-hoffman / May 25 / failed
paper / reid-hoffman / May 20
The IceCube Collaboration has published IceTracks-DR2, its most comprehensive public muon track dataset to date, spanning 14 years of observations (2008–2022) and superseding the prior 10-year release. The dataset incorporates improved detector calibration for post-2010 data and includes binned instrument response functions and effective areas, enabling third-party researchers to conduct independent point-source and transient neutrino analyses. Benchmark results using publicly available software are provided to support reproducibility, lowering the barrier for community-driven searches.
neutrino-astronomyicecube-observatoryparticle-astrophysicsopen-data-releaseneutrino-source-searchhigh-energy-astrophysicsmuon-track-detection
“IceTracks-DR2 extends IceCube's public muon track dataset from 10 years to 14 years of observations, covering April 6, 2008 to May 23, 2022.”
paper / reid-hoffman / May 18
Researchers demonstrate that scanning tunneling microscopy (STM) current pulses can write, reposition, and erase persistent nanometer-scale structural patterns on the surface of WTe₂ — a Weyl semimetal and ferroelectric material. The induced patterns manifest as picometer-scale in-plane and out-of-plane atomic displacements accompanied by local density-of-states changes, with in-plane displacements interpreted as ferroelectric switching and out-of-plane displacements modulating the Peierls-like distortion intrinsic to WTe₂'s Td phase. This establishes a nanoscale, reversible handle on ferroelectric order in a topological quantum material, a capability previously elusive despite prior work on bulk ferroelectric switching and ultrafast transient control.
quantum-materialsnanoscale-patterningscanning-tunneling-microscopyferroelectricsweyl-semimetalcondensed-matter-physics2d-materials
“STM current pulses can write and erase persistent nanometer-scale structural patterns on WTe₂ surfaces.”
paper / reid-hoffman / May 16 / failed
paper / reid-hoffman / May 16 / failed
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paper / reid-hoffman / May 10 / failed
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tweet / @reidhoffman / May 8 / failed
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tweet / @reidhoffman / May 8 / failed