Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 24

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.

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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.

New Data Centers Will Be Powered by Human Brain Cells

Now, Cortical Labs is ready to scale up the operation. As Bloomberg reports, the company says it’s working on “biological data centers” in Melbourne, Australia, and Singapore. Simply put, instead of relying on Nvidia chips like AI companies, Cortical Labs is planning to outfit its futuristic facilities with racks of CL1 biological computers, powered by many more human brain cells, instead.

The company refers to this approach as “wetware,” an unsettling new take on software and hardware terminology. Simply put, the computers send electrical signals to neurons derived from human blood stem cells. The chips embedded within record those neurons’ responses as the output.

The company teamed up with DayOne Data Centers, to develop the two facilities. The Melbourne data center will house 120 CL1 units, while DayOne is planning to deploy as many as 1,000 units at the one in Singapore.

Communication-aware neural networks could advance edge computing

Edge computing is an emerging IT architecture that enables the processing of data locally by smartphones, autonomous vehicles, local servers, and other IoT devices instead of sending it to be processed at a centralized large data center. This approach could allow artificial intelligence (AI) models and other computational systems to perform tasks rapidly, while consuming less power.

Despite the potential of this approach, typically local devices have a limited battery capacity and restricted computing capabilities. This means they often need to send data to remote cloud servers via the internet to complete complex calculations. This transmission of information via wireless communication can consume significant amounts of energy, while also slowing down the rates of transmission.

Researchers at Nanjing University recently introduced a new approach that could potentially boost the speed of communication between edge devices and cloud servers, while also reducing energy consumption. Their proposed strategy, introduced in a paper published in Nature Electronics, relies on newly developed communication-aware in-memory wireless neural networks, new computational tools that combine computing, memory, and wireless communication into a single AI-powered system.

Novel AI semiconductor uses hydrogen ions for learning and memory

A research team led by Lee Hyun Jun and Noh Hee Yeon from the Division of Nanotechnology at DGIST has succeeded in implementing the world’s first two-terminal-based artificial intelligence (AI) semiconductor that precisely controls hydrogen with electrical signals to enable self-learning and memory. The team’s work appears in Advanced Science.

Whereas modern AI requires the rapid processing of vast amounts of data, the separation of computation and memory in conventional computers results in speed degradation and high power consumption. “Neuromorphic semiconductors,” which perform computation and storage simultaneously by mimicking the human brain, are gaining attention as a next-generation technology that can resolve this problem. At the heart of this semiconductor is an artificial synapse device that changes its conductivity based on electrical signals and maintains that state, and the research team focused on hydrogen as the solution.

Conventional oxide-based memory devices have primarily utilized the migration of oxygen vacancies (defects) as memory. However, this has made it difficult to ensure long-term stability and uniformity between devices. In contrast, the research team solved this problem by developing its own method to precisely control the injection and discharge of hydrogen ions (H+) using an electric field.

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