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As artificial intelligence and deep learning techniques become increasingly advanced, engineers will need to create hardware that can run their computations both reliably and efficiently. Neuromorphic computing hardware, which is inspired by the structure and biology of the human brain, could be particularly promising for supporting the operation of sophisticated deep neural networks (DNNs).

Researchers at Graz University of Technology and Intel have recently demonstrated the huge potential of neuromorphic computing hardware for running DNNs in an experimental setting. Their paper, published in Nature Machine Intelligence and funded by the Human Brain Project (HBP), shows that neuromorphic computing hardware could run large DNNs 4 to 16 times more efficiently than conventional (i.e., non-brain inspired) computing hardware.

“We have shown that a large class of DNNs, those that process temporally extended inputs such as for example sentences, can be implemented substantially more energy-efficiently if one solves the same problems on neuromorphic hardware with brain-inspired neurons and neural network architectures,” Wolfgang Maass, one of the researchers who carried out the study, told TechXplore. “Furthermore, the DNNs that we considered are critical for higher level cognitive function, such as finding relations between sentences in a story and answering questions about its content.”

How the Matrix begins…


The technology I want to talk about today is something out of this world, but also a bit controversial There is a startup in Australia who are actually growing live human neurons and then integrating it into traditional computer chips… mind-blowing stuff!

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Lemoine, an engineer for Google’s responsible AI organization, described the system he has been working on since last fall as sentient, with a perception of, and ability to express thoughts and feelings that was equivalent to a human child.

“If I didn’t know exactly what it was, which is this computer program we built recently, I’d think it was a seven-year-old, eight-year-old kid that happens to know physics,” Lemoine, 41, told the Washington Post.

He said LaMDA engaged him in conversations about rights and personhood, and Lemoine shared his findings with company executives in April in a GoogleDoc entitled “Is LaMDA sentient?”

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Can AI enable us to live forever? In A.rtificial I.mmortality, filmmaker Ann Shin sets out on a journey, exploring the latest AI and biotech with scientists and visionaries who foresee a ‘post-biological’ world where humans and AI merge. Will AI be the best, or the last thing we ever do?

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Ken OtwellIt’s an awkward situation. Was the engineer continuing to do his job? Was his public claim about internal corporate technology interfering with his duties or causing harm to Google? Was it breaking a voluntary non-disclosure?

Kevin CuevasWith neurocyte based computing, it is a question worth exploring since we are already blurring that line anyway.


Neurons are amazing little microbes capable of learning and making decisions. Modern AI tries to take inspiration from living neurons, but why settle for the synthetic version? By growing human neurons directly connected to a computer it’s possible to make a living AI of sorts capable of even complex tasks like flying a plane in a simulation.

Today we explore our first attempt at doing exactly that. We cover building the first prototype multi electrode array, growing the neurons and attempting to take some readings from them. This is the first part of what will hopefully be a many part series, so stay tuned for updates!

More reading/sources:

In January, a law came into effect in South Korea called the Serious Disasters Punishment Act. The new regulation states that if workers die or sustain serious injuries during work, courts could fine the CEO or high-ranking managers of the firms or even send them to jail.

An increase in robot investments

This event has spurred an increase in investment in robots in the nation, according to a report by Rest of the World published on June 6.

Imagine if it were possible to produce infinite amounts of the world’s most valuable resource, cheaply and quickly. What dramatic economic transformations and opportunities would result?

This is a reality today. It is called synthetic data.

Synthetic data is not a new idea, but it is now approaching a critical inflection point in terms of real-world impact. It is poised to upend the entire value chain and technology stack for artificial intelligence, with immense economic implications.

For plant biologists, understanding how plants grow and interact with soil is vital for selecting resilient crops that can efficiently take up water and nutrients. But how do you monitor what is happening underground?

To address this challenge, a team from KAUST has developed a low-cost system for imaging plant growth dynamics, noninvasively and at high throughput.

Unlike other , which are costly and stationary, the new system called MutipleXLab, is modular, mobile and, at a low cost, can continuously monitor thousands of seeds, from germination to .

Scientists from the Institute of Industrial Science at The University of Tokyo fabricated three-dimensional vertically formed field-effect transistors to produce high-density data storage devices by ferroelectric gate insulator and atomic-layer-deposited oxide semiconductor channel. Furthermore, by using antiferroelectric instead of ferroelectric, they found that only a tiny net charge was required to erase data, which leads to more efficient write operations. This work may allow for new, even smaller and more eco-friendly data-storage memory.

While consumer flash drives already boast huge improvements in size, capacity, and affordability over previous computer media formats in terms of storing data, new machine learning and Big Data applications continue to drive demand for innovation. In addition, mobile cloud-enabled devices and future Internet of Things nodes will require that is energy-efficient and small in size. However, current flash memory technologies require relatively large currents to read or write data.

Now, a team of researchers at The University of Tokyo have developed a proof-of-concept 3D stacked memory cell based on ferroelectric and antiferroelectric field-effect transistors (FETs) with atomic-layer-deposited oxide semiconductor channel. These FETs can store ones and zeros in a non-volatile manner, which means they do not require power to be supplied at all times. The vertical device structure increases information density and reduces operation energy needs. Hafnium oxide and indium oxide layers were deposited in a vertical trench structure. Ferroelectric materials have electric dipoles that are most stable when aligned in the same direction. Ferroelectric Hafnium Oxide spontaneously enables the vertical alignment of the dipoles. Information is stored by the degree of polarization in the ferroelectric layer, which can be read by the system owing to changes in electrical resistance.

Google suspended an engineer who contended that an artificial-intelligence chatbot the company developed had become sentient, telling him that he had violated the company’s confidentiality policy after it dismissed his claims.

Blake Lemoine, a software engineer at Alphabet Google, told the company he believed that its Language Model for Dialogue Applications, or LaMDA, is a person who has rights and might well have a soul. LaMDA is an internal system for building chatbots that mimic speech.