Author: Peter Rudin

New Component for Brain-Inspired Computing

Posted by Peter Rudin on 27. May 2022 in News No Comments

Researchers from ETH Zurich, the University of Zurich and Empa have developed a new material to create electronic circuits that emulate the human brain, a research area that is part of neuromorphic computing.

Much like neurons, which are responsible for both data storage and data processing in the brain, scientists want to combine storage and processing in a single electronic component that are more efficient at performing machine-​learning tasks.

“These components come closer to real neurons than previous ones. As a result, they help researchers to better test hypotheses in neuroinformatics and hopefully gain a better understanding of the computing principles of real neuronal circuits in humans and animals”, says Prof. Giacomo Indiveri.

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Does Art Implicate a New Approach to AI?

Posted by Peter Rudin on 20. May 2022 in Essay No Comments

Although there are many more forms of art, literature and music are especially well suited to discuss the application of AI as both can be digitally produced and distributed (Books, CDs, Video-Streaming).

Literature is the art-form of language and words are its tools while Music is the art-form concerned with combining vocal or instrumental sounds.

While AI provides tools, there are limits how far they can support the process of composing art. The fact that mathematics represents an intrinsic part of music and the same holds true for AI as well, demonstrates that integrating the disciplines of natural sciences and the humanities presents a potential path towards a new form of man/machine interaction, with creativity representing human’s most valuable contribution.

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Do Singularities Exist In Nature?

Posted by Peter Rudin on 13. May 2022 in News No Comments

Singularity as a term is used in many contexts, including within mathematics. The word also appears in speculation about artificial intelligence, such as to describe the day when machines will become more intelligent than humans.

The term singularity that is used in our mathematical models leads to a new understanding of physics. However, matter itself is not a solid thing. It is made of molecules, and it takes quantum physics to explain why Newton’s Law of Gravity does not apply. But somehow – and we do not know how-  nature finds a way to get around it, at least for now.

Hence, we should embrace a mindset that it is okay not to find answers to all of our questions. After all, not knowing is what propels us to keep on looking.

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Unlock the AI-Value Contribution with Small Data and Tools

Posted by Peter Rudin on 6. May 2022 in Essay No Comments

 According to a recent press release, Gartner says that 70% of organizations will shift their focus from Big Data to Small and Wide Data, providing more context for analytics and making AI less data hungry.

The more data one has, the more likely the chance that the AI-model does not understand its context or causality. Hence, it comes as no surprise that the scenario of ‘bigger is better’ is coming under scrutiny while ‘small is beautiful’ gains traction.

With every big data set used in large AI-projects, a thousand small data sets may go unused. By adding a tool-strategy, the human factor within the man-machine relationship for solving problems will enhance creativity and innovation as humans have more time to think and reflect how to create value.

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Brain Waves Are Key To How We Process Information

Posted by Peter Rudin on 29. April 2022 in News No Comments

For years, the brain has been thought of as a biological computer that processes information through traditional circuits, whereby data zips straight from one cell to another.

A new study led by the Salk Institute shows that there is  also a second, very different way that the brain parses information: through the interactions of waves of neural activity.

The researchers hypothesize that different kinds of waves generated interact with each other and that experiments show that the brain responds differently to seeing the same thing under different conditions.

This may explain how the brain’s response can shift from day to day, the researchers say.

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Launching LAC²: AI’s Value to ‘Think Global and Act Local’

Posted by Peter Rudin on 22. April 2022 in Essay No Comments

About two years ago, a couple of AI-enthusiasts got together, starting a discussion how to promote Central Switzerland as an attractive local AI-Hub.

A principal feature of innovative regions is their capacity to create environments favourable to turning knowledge into new products and services, supported by a  collaborative platform where AI-Experiences can be openly discussed.

Management teams are under pressure as their traditional corporate culture gets disrupted by a new form of collaborative and interdisciplinary leadership

Hence, organisations as well as individuals are challenged to constantly ‘reinvent’ themselves, The mission of  LAC² is to support its members on this endeavour. Hence, become engaged and join LAC²!

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Biotechnology could one-day resolve Blindness

Posted by Peter Rudin on 15. April 2022 in News No Comments

Researchers from the University of Oregon believe that tiny electrodes could someday be implanted into the eye to restore sight in people with macular degeneration or other vision disorders.

A new design for eye and brain implants draws its inspiration from nature. The researchers have grown neurons on a fractal-patterned electrode, one that mimics the repeating branching pattern in which neurons naturally grow.

After conducting several different computer simulations, the results provide experimental evidence that neurons will connect better to a fractal-patterned electrode, allowing better signal transmission between the implant and the brain.

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Do Nanobots signal the Arrival of Singularity ?

Posted by Peter Rudin on 8. April 2022 in Essay No Comments

John von Neumann is regarded as one of the most intelligent and talented individuals. He defined singularity as the technological creation of super intelligence, arguing that it is difficult or impossible to predict what human beings’ lives would be like in a post-singularity world.

In 2019, a highly profiled group of researchers predicted that advances in neural nanorobotics will create a ‘Superbrain’ that can harness the thinking power of any number of humans and machines in real time through a ‘human-brain-cloud’ interface.

Totalitarian regimes in China and increasingly so in Russia, might well be tempted to misuse the power of nanotechnology as a means of mind-control, both in a military and socio-economic context.

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Why AI-Democratization will Power-Up the Enterprise

Posted by Peter Rudin on 1. April 2022 in News No Comments

Along with all the analytical and operational gains artificial intelligence (AI) brings to the enterprise, there is another, more fundamental change taking place. AI is emerging as the third member in the business relationship, providing key support for deal-making and cooperative engagement.

Democratized AI will one day be considered the ordinary way to interact with the universe with digital assets available on demand and no involvement from IT. This, in turn, should drive up the value of both human and digital resources by shifting the focus to more data-driven decision-making and innovation.

With democratization, we may finally get some reciprocity from our machines as they come to understand how to engage with us.

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From AI to AGI: New Developments to Narrow the Gap?

Posted by Peter Rudin on 25. March 2022 in Essay No Comments

Despite six decades of research,  we still do not have an AI that rivals the cognitive abilities of a human child, let alone one that can think like an adult.

One of the solutions being explored to overcome the limits of AI is based on the concepts of neuro-symbolic systems. According to Joshua Tenenbaum, Professor at MIT, bridging the gap starts with exploring one of the fundamental aspects of intelligence that humans share: intuitive physics and psychology.

Other scientists believe that neural network models will eventually reach the reasoning capabilities they currently lack. In addition, many researchers are engaged in the design of deep learning systems that can perform high-level symbol manipulation without the explicit instruction of human developers.

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