Author: Peter Rudin

The Search for Secrets of the Human Brain

Posted by Peter Rudin on 8. November 2019 in News No Comments

Large-scale national research projects hope to reveal how the brain learns, how it controls behavior and how it goes wrong.

Along with the goal of describing in detail just how the brain works at various levels, from the cellular to the behavioral, the hope is that these projects will lead to new ways to treat brain diseases and mental-health conditions, as well as advance artificial-intelligence (AI) technologies.

Investors are providing the projects with billions of dollars in new funding, creating career opportunities for not only neuroscientists but also physicists, mathematicians, chemists, materials scientists and medical specialists.

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The accelerating Impact of AI on Research

Posted by Peter Rudin on 1. November 2019 in Essay No Comments

Digital transformation, also dubbed as Industry 4.0, is in full swing. AI transformation, however, is just at the beginning, raising many societal and individual issues such as the replacement of human researchers with intelligent machines.

Many scientists are arguing that the latest techniques in machine learning and AI represent a fundamentally new way of doing scientific research.

One such approach, known as generative modelling, can help identify the most plausible theory among competing explanations for observational data, based solely on the data without any preprogramed knowledge of what physical processes might be at work in the system under study.

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Brain Scientists compete to understand Consciousness

Posted by Peter Rudin on 25. October 2019 in News No Comments

Brain scientists can watch neurons fire and communicate. They can map how brain regions light up during sensation, decision-making, and speech. What they can’t explain is how all this activity gives rise to consciousness.

The Templeton World Charity Foundation hopes to narrow the debate with experiments that directly pit theories of consciousness against each other.

The first two contenders are the global workspace theory (GWT), championed by Stanislas Dehaene and the integrated information theory (IIT), proposed by Giulio Tononi.

To test the schemes, six labs will run experiments with a total of more than 500 participants.

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AI and the Issue of Human Emotions

Posted by Peter Rudin on 18. October 2019 in Essay 1 Comment

One of the founding fathers of AI, Marvin Minsky was once questioned about machine emotions and said:

“The question is not whether intelligent machines can have any emotions, but   whether machines can be intelligent without any emotions”.

We have reached the point where computational methods can be applied to process the expression of emotions that occur with human interaction. However, this does not imply that intelligent machines have emotions.

For artificial intelligence to have human emotions, we would not only have to recreate the human brain but also its senses, body and consciousness.

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Inventing a Quantum Internet

Posted by Peter Rudin on 11. October 2019 in News No Comments

Fifty years after the current internet was born, the physicist and computer scientist Stephanie Wehner is planning and designing the next internet — a quantum one.

Wehner is the coordinator of the Quantum Internet Alliance, a European Union initiative to build a network for transmitting quantum information throughout the continent.

“Using such a network, we gain information about creativity and social sciences. If you look at the classical internet, people thought we would use it to send around some files. That’s great. But people have gotten more creative”, Wehner says.

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An Integrated Approach to Apply AI in Decision-Making

Posted by Peter Rudin on 4. October 2019 in Essay No Comments

Artificial Neural Networks (ANNs) and Machine-Learning Algorithms (Deep Learning) are applied to detect deviations from a given norm or to predict outcomes based on the analysis of historic data. However, this neuroinformatic, mathematical approach to simulate the human brain is reaching its limits.

Decision-making provides one good example how the application of integrated AI (neuromathematics, neurobiology and neurophilosophy) can improve the decision-making process.

Regardless which process is applied – rational, intuitive or emotional – understanding the functionality of the human brain holds the key to enhancing the quality of human decision-making.

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The Potential of Brain-Computer Interfaces

Posted by Peter Rudin on 27. September 2019 in News No Comments

Neural interfaces, brain-computer interfaces (BCIs) and other devices that blur the lines between mind and machine have extraordinary potential.

A new Royal Society report is for the first time systematically exploring whether it is “right” or not to use neural interfaces – machines implanted in or worn over the body to pick up or stimulate nervous activity in the brain or other parts of the nervous system.

The dangers of commercializing this field are obvious, not only in the area of leveraging BCIs to read others’ thoughts even when the subject is not willing, but if Big Tech companies manage to obtain monopolistic access to human thoughts and ideas.

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AI and Consciousness, from Philosophy to Neuroscience

Posted by Peter Rudin on 20. September 2019 in Essay No Comments

Whether consciously aware or unaware, the brain correlates and selects information, associate’s meanings, and influences motivation, value judgment and goal-directed behavior.

It is the combination of neuroscience getting involved in studying consciousness and philosophy becoming more open to studying natural sciences, including neuroscience, that has brought about a more promising research environment leading to the emergence of neurophilosophy.

The most powerful artificial intelligence algorithms remain distinctly un-self-aware, but developments towards conscious thought processing are already happening, eventually providing a conscious machine.

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Can AI Systems Understand Human Values?

Posted by Peter Rudin on 13. September 2019 in News No Comments

Machine learning (ML) algorithms can already recognize patterns far better than the humans they’re working for. This allows them to generate predictions and make decisions in a variety of high-stakes situations. However, for ML systems to truly be successful, they need to understand human values.

Researchers still need to answer empirical questions related to things like how values evolve and change over time. And once all the empirical questions are answered, researchers need to contend with the philosophical questions that don’t have an objective answer, like how those values should be interpreted and how they should guide an AGI’s decision-making.

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Is Alphabet’s DeepMind Subsidiary on the Right Track?

Posted by Peter Rudin on 6. September 2019 in Essay No Comments

DeepMind, the world’s largest research-focused artificial intelligence operation, is losing money fast. The rising magnitude of DeepMind’s losses is impressive, more than USD 1 billion in the past three years, mostly related to its ongoing hiring of top researchers worldwide at very high salary levels with a current headcount of over 850 employees.

Advances in deep reinforcement learning have fueled DeepMind’s impressive victories in Go and the computer game StarCraft. However, this has hardly advanced DeepMind’s declared goal of being the world-leader in Artificial General Intelligence (AGI).

Today AI-research covers Neuroinformatics, Neurobiology and Neurophilosophy. Is DeepMind on the right track?

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