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Category: robotics/AI – Page 8

AI model predicts chemical effects on gene expression, speeding drug discovery

Inside a diseased cell, the genes are in chaos. Some are receiving signals to overproduce a protein. Others are reducing activity to abnormal levels. Up is down and down is up. The right molecule could restore order, reversing dysregulation in specific genes. But finding the ideal compound could require examining millions of chemicals for their influence on hundreds or thousands of genes.

An MSU-led team of researchers has demonstrated a better way. Using machine learning trained on enormous amounts of published data, they were able to predict how chemicals will influence gene expression, based solely on the structure of the chemical.

Their study, recently published in the journal Cell, has discovered compounds that are promising for treatment of two difficult diseases: the most aggressive form of liver cancer and a chronic lung disease with no curative options.

Lifelong behavioral screen reveals an architecture of vertebrate aging

By tracking nearly every movement of a tiny fish’s life from adolescence to death, a new Science study reveals a hidden behavioral blueprint of aging—one that can predict a fish’s age or how long an individual will live.

Mapping behavior of individual vertebrate animals across lifespan could provide an unprecedented view into the lifelong process of aging. We created a platform for high-resolution continuous behavioral tracking of the African killifish across natural lifespan from adolescence to death. We found that animals follow distinct individual aging trajectories. The behaviors of long-lived animals differed markedly from those of short-lived animals, even relatively early in life, and were linked to organ-specific transcriptomic shifts. Machine-learning models accurately inferred age and even forecasted an individual’s future lifespan, given only behavior at a young age. Finally, we found that animals progressed through adulthood in a sequence of stable and stereotyped behavioral stages with abrupt transitions, revealing precise structure for an architecture of aging.

Deep-learning-based de novo discovery and design of therapeutics that reverse disease-associated transcriptional phenotypes

Bulk and single-cell transcriptomics are widely used to characterize diseases and cellular states but remain underexplored for de novo drug discovery. Here, we present a strategy to screen and optimize compounds by matching disease transcriptomic profiles with compound-induced transcriptomic features predicted from chemical structures using a deep-learning model.

Ben Goertzel responds

As part of Future Day 2026, we hosted a conversation between two of the most provocative minds in AGI – Ben Goertzel and Hugo de Garis (with Adam Ford as moderator/provocateur) – to tackle the ultimate existential question: Is an Artilect War inevitable, and should humanity accept becoming the “number two” species?

The discussion will build upon last years discussion between Ben and Hugo on AGI and the Singularity.

It will explore the idea of human transcendence. If we can’t beat them, do we join them?

Will humanity transcend into a Jupiter brain quectotech utility fog?

Is the Artilect War the inevitable conclusion of biological intelligence? Or can we find a path toward existing in a universe that still finds us aesthetically pleasing?

0:00 Intro.

Continue reading “Ben Goertzel responds” | >

CellVoyager: AI CompBio agent generates new insights by autonomously analyzing biological data

CellVoyager is an artificial intelligence agent capable of exploring new biological hypotheses by autonomously analyzing single-cell RNA sequencing datasets and accounting for background information and prior analyses.

Researchers Upload Fly’s Brain to Matrix, Let It Control Virtual Body

Artificial intelligence seeks to emulate the faculties of the human mind through computational systems, a synthetic recreation of our brains’ capabilities to perceive, learn, and reason.

Now, a company claims to have taken a totally different tack by simulating the 125,000 neurons and 50 million synaptic connections of an adult fruit fly’s brain — and then letting it roam inside a Matrix-like virtual environment.

In a video shared by Eon Systems cofounder Alex Weissner-Gross, the crudely animated insect can be seen stretching its legs inside a simulated sandbox, rubbing its front feet together and using its labellum to drink from a small bowl.

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