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Category: biological – Page 113

How a single synapse transmits both visual and subconscious information to the brain of fruit flies

Research led by Peking University, China, has discovered a single type of retinal photoreceptor cell in Drosophila (fruit fly) is involved in both visual perception and circadian photoentrainment by co-releasing histamine and acetylcholine at the first visual synapse.

In a paper, “A single photoreceptor splits perception and entrainment by cotransmission,” published in Nature, the team details the discovery that the Drosophila visual system segregates and circadian photoentrainment by co-transmitting two neurotransmitters, histamine and acetylcholine, in the R8 cells.

Light detection involves capturing signals through photoreceptors in the eye, which are essential for image formation and subconscious visual functions, such as regulating biological rhythms according to the daily light-dark cycle (photoentrainment of the ). The optical system has distinct pathways for image formation (based on local contrast) and non-image-related tasks (based on global irradiance).

OpenAI forms new team to assess “catastrophic risks” of AI

OpenAI’s new preparedness team will address the potential dangers associated with AI, including nuclear threats.

OpenAI is forming a new team to mitigate the “catastrophic risks” associated with AI. In an update on Thursday.

The team will also work to mitigate “chemical, biological, and radiological threats,” as well as “autonomous replication,” or the act of an AI replicating itself. Some other risks that the preparedness team will address include AI’s ability to trick humans, as well as cybersecurity threats.

We believe that frontier AI… More.

The preparedness team will address several potential threats.

New elephant trunk inspired robot for better human interaction

“We hope that this soft robotic arm exemplifies a future where machines assist, complement, and understand human needs more deeply than ever before.”

Drawing inspiration from the movements of elephant trunks and octopus tentacles, researchers at the CREATE lab of t. It ishe Swiss Federal Institute of Technology Lausanne (EPFL) has developed a revolutionary robotic structure, the “trimmed helicoid.”

Set to usher in greater compliance and control in robotic design, this structure ensures safer interactions between humans and robots and is a result of blending computational modeling with astute biological observations.

Adaptive optical neural network connects thousands of artificial neurons

Modern computer models—for example for complex, potent AI applications—push traditional digital computer processes to their limits. New types of computing architecture, which emulate the working principles of biological neural networks, hold the promise of faster, more energy-efficient data processing.

A team of researchers has now developed a so-called event-based architecture, using photonic processors with which data are transported and processed by means of light. In a similar way to the brain, this makes possible the continuous adaptation of the connections within the neural network. This changeable connections are the basis for learning processes.

For the purposes of the study, a team working at Collaborative Research Center 1,459 (Intelligent Matter)—headed by physicists Prof. Wolfram Pernice and Prof. Martin Salinga and computer specialist Prof. Benjamin Risse, all from the University of Münster—joined forces with researchers from the Universities of Exeter and Oxford in the UK. The study has been published in the journal Science Advances.

Chatbot Offers Roadmap for How to Conduct a Bio Weapons Attack

Jailbroken large language models (LLMs) and generative AI chatbots — the kind any hacker can access on the open Web — are capable of providing in-depth, accurate instructions for carrying out large-scale acts of destruction, including bio-weapons attacks.

An alarming new study from RAND, the US nonprofit think tank, offers a canary in the coal mine for how bad actors might weaponize this technology in the (possibly near) future.

In an experiment, experts asked an uncensored LLM to plot out theoretical biological weapons attacks against large populations. The AI algorithm was detailed in its response and more than forthcoming in its advice on how to cause the most damage possible, and acquire relevant chemicals without raising suspicion.

Where AI and organisms differ and what it means for AGI

“For AI to be motivated towards a goal, it must know what it wants.”

The possible board combinations in a game of Go are more than the number of atoms in the known universe, but it’s still a finite number. In the real world, there are infinite possibilities for what might happen next, and uncertainty is rampant. How realistic, then, is AGI?

A recent research paper published in Frontiers in Ecology and Evolution explores obstacles toward AGI. Biological systems with degrees of general intelligence — organisms ranging from the humble microbes to the humans reading this — are capable of improvising to meet their goals. What prevents AI from improvising?

Direct imaging reveals individual protein-bound glycans in new detail

Scanning tunnelling microscopy images of simple glycoconjugates and glycosaminoglycans and their corresponding structures.

Scanning tunnelling microscopy has enabled researchers to directly image important sugar molecules attached to lipids and proteins. The experiments provide a picture at the single-molecule level of the sequences and locations of glycans bound to important biomolecules, offering new insight into the role they play in biology.

Scientists propose sweeping new law of nature, expanding on evolution

WASHINGTON, Oct 16 (Reuters) — When British naturalist Charles Darwin sketched out his theory of evolution in the 1,859 book “On the Origin of Species” — proposing that biological species change over time through the acquisition of traits that favor survival and reproduction — it provoked a revolution in scientific thought.

Now 164 years later, nine scientists and philosophers on Monday proposed a new law of nature that includes the biological evolution described by Darwin as a vibrant example of a much broader phenomenon, one that appears at the level of atoms, minerals, planetary atmospheres, planets, stars and more.

It holds that complex natural systems evolve to states of greater patterning, diversity and complexity.

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