Lifeboat Foundation

The Linac Coherent Light Source (LCLS), the world’s most powerful X-ray laser located at the SLAC National Accelerator Laboratory in the US, is set for a major upgrade that will increase its X-ray energy 3,000-fold, a press release shared with Interesting Engineering said.

When complete, the upgrade will let scientists explore atomic-scale processes in their search for answers in biology, materials science, quantum physics, and much more.

The study of computational biology is essential to understanding this transition. By exploring how life processes information, we gain insights into the nature of consciousness and intelligence itself. Computational models are key to revealing how systems organize, adapt, and evolve toward greater complexity and self-awareness. This progression suggests a future where intelligence is no longer bound by biological limitations but extends into the realm of artificial systems, creating a symbiotic relationship between humans and machines.

Ultimately, NOOGENESIS challenges traditional scientific paradigms by framing the universe as an informational “self-simulating” entity, where consciousness plays a central role in its evolutionary processes. The origins of life, the evolution of intelligence, and the potential for a post-Singularity future are all part of this grand narrative. By embracing this view, we can cultivate a more comprehensive understanding of the universe and our place within it—one that recognizes the fundamental role of consciousness in shaping reality and guiding evolution toward the apotheosis of Omega Singularity, the final convergence of intelligence and complexity.

Scientists are using ever more sophisticated AI algorithms trained on vast, unlabeled datasets to develop models that can ‘interpret’ biological data to help guide biomolecule design.

The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs. With the recent increasing need for the autonomy of machines in the real world, e.g., self-driving vehicles, drones, and collaborative robots, exploitation of deep neural networks in those applications has been actively investigated. In those applications, energy and computational efficiencies are especially important because of the need for real-time responses and the limited energy supply. A promising solution to these previously infeasible applications has recently been given by biologically plausible spiking neural networks. Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically realistic models of neurons to carry out the computation. Due to their functional similarity to the biological neural network, spiking neural networks can embrace the sparsity found in biology and are highly compatible with temporal code. Our contributions in this work are: (i) we give a comprehensive review of theories of biological neurons; (ii) we present various existing spike-based neuron models, which have been studied in neuroscience; (iii) we detail synapse models; (iv) we provide a review of artificial neural networks; (v) we provide detailed guidance on how to train spike-based neuron models; (vi) we revise available spike-based neuron frameworks that have been developed to support implementing spiking neural networks; (vii) finally, we cover existing spiking neural network applications in computer vision and robotics domains. The paper concludes with discussions of future perspectives.

Keywords: spiking neural networks, biological neural network, autonomous robot, robotics, computer vision, neuromorphic hardware, toolkits, survey, review.

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Rip up the old rules of biology.

Sara Imari Walker is a professor of physics at Arizona State University and the author of a new book Life as No One Knows It: The Physics of Life’s Emergence. As I wrote in my review of the book, I’m a big fan of Walker’s work (full disclosure, we have collaborated before on a paper and a proposal).

The subject of her work and the new book is what might be called the “Physics of Life.” This is different from biophysics, which tries to account for specific physics aspects of biological processes. Instead, the Physics of Life has a more ambitious goal: to understand what separates living from non-living systems.

Along with her collaborators, Walker developed Assembly Theory, which focuses on “selection” and is a fundamental physics account for the difference between life and non-life. Assembly Theory quantifies complexity by measuring how many unique steps are needed to build a molecular structure. By identifying complex patterns that signify biological processes, this framework could help scientists detect life forms on other worlds — even those that may not look like anything we’re familiar with on Earth.

In science fiction movies like Frankenstein and Re-Animator, human bodies are revived, existing in a strange state between life and death. While this may seem like pure fantasy, a recent study suggests that a “third state” of existence might actually be present in modern biology.

According to the researchers, this third state occurs when the cells of a dead organism continue to function after its death, sometimes gaining new capabilities they never had while the organism was alive.

Amazingly, if further experiments on cells from dead animals — including humans — prove this ability, it could even challenge the definition of legal death.

Denis Noble is a renowned biologist and pioneer in systems biology, known for his groundbreaking work on the heart and his influential contributions to the understanding of biological systems.

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Scientific Reports volume 12, Article number: 17,629 (2022) Cite this article.