Opening the AI black box: program synthesis via mechanistic interpretability

We present MIPS, a novel method for program synthesis based on automated mechanistic interpretability of neural networks trained to perform the desired task, auto-distilling the learned algorithm into Python code. We test MIPS on a benchmark of 62 algorithmic tasks that can be learned by an RNN and find it highly complementary to GPT-4: MIPS solves 32 of them, including 13 that are not solved by GPT-4 (which also solves 30). MIPS uses an integer autoencoder to convert the RNN into a finite state machine, then applies Boolean or integer symbolic regression to capture the learned algorithm. As opposed to large language models, this program synthesis technique makes no use of (and is therefore not limited by) human training data such as algorithms and code from GitHub. We discuss opportunities and challenges for scaling up this approach to make machine-learned models more interpretable and trustworthy.Comment: 24 page

Causal gene regulatory analysis with RNA velocity reveals an interplay between slow and fast transcription factors

<p>Data and code in support of <a href="https://www.biorxiv.org/content/10.1101/2022.10.18.512766">https://www.biorxiv.org/content/10.1101/2022.10.18.512766</a> and subsequent journal publication.</p&gt

The contribution of historical processes to contemporary extinction risk in placental mammals

Altres ajuts: CERCA Programme/Generalitat de Catalunya ; Secretaria d'Universitats i RecercaSpecies persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. Here, we surveyed genetic variation across single genomes of 240 mammals comprising the Zoonomia alignment to evaluate how historical effective population size (N ) impacts heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical N carry a proportionally larger burden of deleterious alleles due to long-term accumulation and fixation of genetic load, and have higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment. Genomic data from 240 species show that information encoded within a single genome can provide a conservation risk assessment

The contribution of historical processes to contemporary extinction risk in placental mammals

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.Funding was provided by NIH grant R01 HG008742 (E.K.K.); the Swedish Research Council Distinguished Professor Award (K.L.-T.); the Wallenberg Foundation (K.L.-T.); European Research Council European Union’s Horizon 2020 864203 (T.M.-B.); MINECO/FEDER, UE grant BFU2017-86471-P (T.M.-B.); Agencia Estatal de Investigación “Unidad de Excelencia María de Maeztu” CEX2018-000792-M (T.M.-B.); a Howard Hughes International Early Career award (T.M.-B.); Secretaria d’Universitats i Recerca (T.M.-B.); and CERCA Programme del Departament d’Economia i Coneixement de la Generalitat de Catalunya (T.M.-B.)

The contribution of historical processes to contemporary extinction risk in placental mammals

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment