Lifeboat Foundation

Back in 2016, we told you about the iBubble, an underwater drone that autonomously follows and films scuba divers. Well, it now has a more capable industrial-use big brother, known as the Seasam.

Manufactured by French marine tech company Notilo Plus, the Seasam actually first hit the market in 2019. That said, it recently gained attention when it was featured in the horror film The Deep House, in which a scuba diving couple explore an underwater haunted house … and yes, that is kind of a cool premise for a movie.

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A literature review by researchers at the School of Biomedical Engineering & Imaging Sciences fleshes out key issues currently preventing the proliferation of robotic procedures, specifically their use in image-guided interventional procedure in the brain.

Key criteria for future success are also highlighted.

The researchers conducted the systematic review of the literature by looking at applications of robotic systems in interventional neuroradiology—image-guided interventional procedures using devices in the blood vessels to treat diseases in the brain such as the treatment of aneurysms (blisters forming in blood vessels) which can cause catastrophic bleeding if they rupture. Another procedure is clot removal in stroke. Clot removal, known as mechanical thrombectomy, is performed to stop that area of the brain from dying.

The single technique for teaching neural networks multiple skills is a step towards general-purpose AI.

A giant 18-wheel transport truck is barreling down a multi-lane Texas highway, and there is no one behind the wheel.

The futuristic idea may seem surreal, but it is being tested in this vast southern US state, which has become the epicenter of a rapidly developing self-driving vehicle industry.

Before driverless trucks are allowed onto roads and highways, however, multiple tests must still be conducted to ensure they are safe.

Samsung, the world’s biggest memory chip maker, has announced that it has become the first in the world to demonstrate the MRAM (Magnetoresistive Random Access Memory) technology for in-memory computing. The company’s paper on its innovation, titled ‘A crossbar array of magnetoresistive memory devices for in-memory computing,’ was published by Nature on its website, and its print edition is coming next.

The research was a collaboration between SAIT (Samsung Advanced Institute of Technology), Samsung Foundry, and Samsung Semiconductor R&D. Dr. Seungchul Jung (Staff Researcher at SAIT), Dr. Donhee Ham (Fellow of SAIT and Professor of Harvard University), and Dr. Sang Joon Kim (Vice President of Technology at SAIT) worked on the research.

Usually, data is stored in memory chips (DRAM) and processed by a CPU or an AP (Application Processor). However, data storage and computing happen on the same chip with in-memory computing. Since there is no need to transfer data from memory to the processor and vice versa, a lot of time is saved. Data processing inside the memory happens in a highly parallel manner, resulting in substantial power savings. Samsung claims that MRAM technology will be great for things like AI processing.

Artificial intelligence and machine learning are currently affecting our lives in many small but impactful ways. For example, AI and machine learning applications recommend entertainment we might enjoy through streaming services such as Netflix and Spotify.

In the near future, it’s predicted that these technologies will have an even larger impact on society through activities such as driving fully autonomous vehicles, enabling complex scientific research and facilitating medical discoveries.

But the computers used for AI and machine learning demand a lot of energy. Currently, the need for computing power related to these technologies is doubling roughly every three to four months. And cloud computing data centers used by AI and machine learning applications worldwide are already devouring more electrical power per year than some small countries. It’s easy to see that this level of energy consumption is unsustainable.

I propose an underlying process which constitutes our intelligence as human beings, and argue that our current AI systems fundamentally lack it.

Sources:
John Vervaeke, Timothy P. Lillicrap, Blake A. Richards — Relevance Realization and the Emerging Framework in Cognitive Science http://www.ipsi.utoronto.ca/sdis/Relevance-Published.pdf.
Daniel Dennnett — Cognitive Wheels: The Frame Problem of AI https://folk.idi.ntnu.no/gamback/teaching/TDT4138/dennett84.pdf.
Francisco J. Varela, Eleanor Rosch and Evan Thompson — The Embodied Mind: Cognitive Science and Human Experience.

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They are.

The cyborgs are upon us. Turns out, they’re more ‘enhanced reality’ and less ‘science fiction.’

In 1998, Professor of Cybernetics Kevin Warwick had a chip implanted in his body that would open electronic doors and turn on lights as he passed. In 2002, he had a 100 electrode array wired into the nervous system of his arm to allow him to remotely control an artificial hand. Today, he’s working on using animal brain cells as a control system for robots.

Continue reading “The Cyborg Revolution: Are They Here Yet?” »