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Category: biological

A multi-institutional collaboration of synthetic biology research centers in China has developed a genetically engineered strain of Vibrio natriegens capable of bioremediating complex organic pollutants, including biphenyl, phenol, naphthalene, dibenzofuran, and toluene, in saline wastewater and soils.

Complex are prevalent in industrial wastewater generated by petroleum refining and chlor-alkali processing. Due to their and resistance to natural degradation, these compounds persist in marine and saline environments, posing ecological risks and potential threats to public health.

Microbial bioremediation methods typically use consortia of wild-type bacterial strains, yet these organisms demonstrate limited capacity to degrade complex pollutant mixtures. Elevated salinity levels further inhibit bacterial activity, diminishing bioremediation efficacy in industrial and marine wastewater. Developing capable of degrading pollutants while tolerating saline conditions remains a critical challenge.

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Life truly is radiant, according to an experiment conducted by researchers from the University of Calgary and the National Research Council of Canada.

An extraordinary experiment on mice and leaves from two different plant species has uncovered direct physical evidence of an eerie ‘biophoton’ phenomenon ceasing on death, suggesting all living things – including humans – could literally glow with health, until we don’t.

The findings might seem a little fringe at first glance. It’s hard not to associate scientific investigations into biological electromagnetic emissions with debunked and paranormal claims of auras and discharges surrounding living organisms.

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In the domain of artificial intelligence, human ingenuity has birthed entities capable of feats once relegated to science fiction. Yet within this triumph of creation resides a profound paradox: we have designed systems whose inner workings often elude our understanding. Like medieval alchemists who could transform substances without grasping the underlying chemistry, we stand before our algorithmic progeny with a similar mixture of wonder and bewilderment. This is the essence of the “black box” problem in AI — a philosophical and technical conundrum that cuts to the heart of our relationship with the machines we’ve created.

The term “black box” originates from systems theory, where it describes a device or system analyzed solely in terms of its inputs and outputs, with no knowledge of its internal workings. When applied to artificial intelligence, particularly to modern deep learning systems, the metaphor becomes startlingly apt. We feed these systems data, they produce results, but the transformative processes occurring between remain largely opaque. As Pedro Domingos (2015) eloquently states in his seminal work The Master Algorithm: “Machine learning is like farming. The machine learning expert is like a farmer who plants the seeds (the algorithm and the data), harvests the crop (the classifier), and sells it to consumers, without necessarily understanding the biological mechanisms of growth” (p. 78).

This agricultural metaphor points to a radical reconceptualization in how we create computational systems. Traditionally, software engineering has followed a constructivist approach — architects design systems by explicitly coding rules and behaviors. Yet modern AI systems, particularly neural networks, operate differently. Rather than being built piece by piece with predetermined functions, they develop their capabilities through exposure to data and feedback mechanisms. This observation led AI researcher Andrej Karpathy (2017) to assert that “neural networks are not ‘programmed’ in the traditional sense, but grown, trained, and evolved.”

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The notion that the quantum realm somehow sits sealed off from the relativistic domain has captured popular imagination for decades. Perhaps this separation is comforting in a way, because it assigns neat boundaries to a notoriously complex theoretical landscape. Yet, a careful look at both cutting-edge research and historical development suggests that no such invisible barrier actually exists. Early quantum pioneers such as Planck (1901) and Heisenberg (1925) laid foundations that seemed confined to the minuscule domain of atoms and subatomic particles. Before long, Einstein (1916) showed us that gravity and motion operate in ways that defy purely Newtonian conceptions, especially at cosmic scales. Despite the apparent chasm between the quantum and relativistic descriptions, threads of continuity run deeper than we once imagined. The famous energy discretization proposed by Planck was intended to solve classical paradoxes at microscopic scales, but the fundamental constants he unveiled remain essential at any size, linking the behavior of infinitesimal systems to grand cosmic events.

Modern experiments push this continuity further into the mainstream conversation. Quantum coherences documented in biological processes illuminate the reality that phenomena once labeled “strictly quantum” can permeate living systems in everyday environments (Engel et al., 2007). Photosynthesizing cells exploit wave-like energy flows, migratory birds appear to navigate using subtle quantum effects, and intriguing evidence suggests that neuronal microtubules might process information at scales once deemed too large for quantum behavior (Hameroff, 1998). If relativity reliably predicts how massive objects curve spacetime, and quantum theory demonstrates how particles and fields manifest as discrete excitations, then the missing piece in unifying these perspectives may hinge on the realization that neither domain is airtight. We stand on a continuum of phenomena, from photosynthetic molecules absorbing photons to astrophysical bodies warping spacetime.

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Michael Levin is a scientist at Tufts University; his lab studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems. He works at the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science. Respective papers are linked below.

Round 1 Interview | What are Cognitive Light Cones? • What are Cognitive Light Cones? (Mich…
Round 2 Interview | Agency, Attractors, & Observer-Dependent Computation in Biology & Beyond • Agency, Attractors, & Observer-Depend…

Bioelectric Networks: The cognitive glue enabling evolutionary scaling from physiology to mind https://link.springer.com/article/10…
Darwin’s Agential Materials: Evolutionary implications of multiscale competency in developmental biology https://link.springer.com/article/10…
Biology, Buddhism, and AI: Care as the Driver of Intelligence https://www.mdpi.com/1099-4300/24/5/710

Bioelectric Networks as \.

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The mechanism can also create better biological imaging tools to see deep inside tissues using safer infrared light. It could even cool materials with lasers, by removing thermal energy through UCPL.

“By establishing an intrinsic model of UCPL in single-walled carbon nanotubes, we hope to open up new possibilities for designing advanced optoelectronic and photonic devices,” added Kato.

What the RIKEN scientists have essentially discovered is that one does not need structural defects for up-conversion in carbon nanotubes. Instead, phonons and dark excitons do the trick. This opens up cleaner, more efficient, and more flexible designs for future energy and photonic technologies.

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We discuss Michael Levin’s paper “Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue.” Levin is a scientist at Tufts University, his lab studies anatomical and behavioral decision-making across biological, artificial, and hybrid systems. His work spans developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science. 🎥 Next, watch my first interview with Michael Levin… What are Cognitive Light Cones? • What are Cognitive Light Cones? (Mich… ❶ Memories as Agents 0:00 Introduction 1:40 2024 Highlights from Levin Lab 3:20 Stress sharing paper summary 6:15 Paradox of change: Species persist don’t evolve 7:20 Bow-tie architectures 10:00 🔥 Memories as messages from your past self 12:50 Polycomputing 16:45 Confabulation 17:55 What evidence supports the idea that memories are agential? 22:00 Thought experiment: Entities from earth’s core ❷ Information Patterns 31:30 Memory is not a filing cabinet 32:30 Are information patterns agential? 35:00 🔥 Caterpillar/butterfly… sea slug memory transfer 37:40 Bow-tie architectures are EVERYWHERE 43:20 Bottlenecks “scary” for information ❸ Connections & Implications 45:30 🔥 Black holes/white holes as bow-ties (Lee Smolin) 47:20 What is confabulation? AI hallucinations 52:30 Gregg Henriques & self-justifying apes… all good agents storytellers 54:20 Information telling stories… Joseph Campbell’s journey for a single cell 1:00:50 What comes next? 🚾 Works Cited 🚩 Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue https://www.mdpi.com/1099-4300/26/6/481 https://thoughtforms.life/suti-the-se… our way to health with robot cells | Michael Levin (Big Think 2023) • Biohacking our way to health with rob… https://peregrinecr.com/ 🚀 What is this channel? Exploring Truth in philosophy, science, & art. We’ll uncover concepts from psychology, mythology, spirituality, literature, media, and more. If you like Lex Fridman or Curt Jaimungal, you’ll love this educational channel. p.s. Please subscribe! Young channel here. =) #science #memory #biology #computing #mind #intelligence #attractor #polycomputing #bioelectric #cybernetics #research #life

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Recorded 6 November 2024. Michael Levin of Tufts University presents “Non-neural intelligence: biological architectures for problem-solving in diverse spaces” at IPAM’s Naturalistic Approaches to Artificial Intelligence Workshop. Abstract: The familiar, readily-recognized intelligence of brainy animals has long served as inspiration for AI. However, biological intelligence is far older than neurons, and indeed than multicellularity. My lab studies problem-solving in cells, tissues, and even subcellular components, operating in different spaces and at different scales than conventional intelligent agents. In this talk, I will describe a framework for detecting, communicating with, and creating collective intelligences, and show examples of how the fundamental properties of life suggest novel approaches for ethically relating to diverse and fascinating engineered and hybrid intelligences. Learn more online at: https://www.ipam.ucla.edu/programs/wo…

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Growing evidence suggests that subatomic phenomena can shape fundamental activities in cells, including how organisms handle energy at the smallest scales. Quantum biology, as it’s being called, is no longer just a fringe idea among researchers.

On May 5, 2025, scientists at The Hebrew University of Jerusalem announced a study linking quantum mechanics with key cellular functions in protein-based systems.

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