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AI in Search for new Inspirations and Human Contribution

Posted by Peter Rudin on 1. December 2017 in Essay 1 Comment

Continuous progress in artificial intelligence (AI) is raising expectations to build systems that learn and think like people. Many advances have come from using deep neural networks trained in tasks such as object recognition, language translation or board games.

Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways.

One source of inspiration to advance AI to a level closer to human thinking comes from Geoffrey Hinton, Professor at the University of Toronto and a Google researcher. Another comes from Joshua Tenenbaum, Professor at MIT’s Department of Brain and Cognitive Sciences, engaged in reverse engineering the human mind.

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AI and Neuro-Technology: Ethics a must for Human Survival

Posted by Peter Rudin on 17. November 2017 in Essay 3 Comments

As Neuroscience and AI is beginning to merge to come up with a true ‘Artificial General Intelligence (AGI)’ the ‘issue of ethics’ needs new attention.

Technological developments in machine intelligence and Neuro-Technology implicate that it will be possible to decode people’s mental processes and directly manipulate the brain mechanisms underlying their intentions, emotions and decisions.

Consequently the current efforts to incorporate standards of ethics in AI have to be extended to include Neuro-Technology as well. There is no way to reap the potential benefits of Singularity without the adaptation and implementation of strong ethics fostering our human values.

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What happens when Artificial equals Human Intelligence?

Posted by Peter Rudin on 3. November 2017 in Essay No Comments

Very much driven by ongoing progress in neuroscience to crack the neural code of intelligence, most scientists seem to agree that this moment of intelligence-equality also referred to as ‘Singularity’ will happen within the next 15 to 65 years.

What is the fate of humanity after this milestone is reached? Before we try to answer this question we should keep in mind that intelligence is only part of what human existence is all about.

To deal with the widespread fear that the potential of AI can be misused by governments to rage war or the concern that market-controlling institutions misuse their data-analysis power, we have to widen our scope.

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Google adds Ethics Unit to reach AI Supremacy

Posted by Peter Rudin on 20. October 2017 in Essay 1 Comment

Google has implemented the world’s most powerful network of data centers. With its own AI-optimized hardware design, Google currently provides services to 2 billion active Android devices, 1 billion You Tube users watching 1 billion hours of video every day and handling over 1 million search inquiries per second.

In a bold move to take leadership in the discussion about ethics, DeepMind, Google’s subsidiary, also known for its AlphaGo software that beat the world’s best Go player, has announced the formation of a major new AI research unit called ‘Deep Mind Ethics and Society (DMES)’ comprised of a full-time staff and external advisors.

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Thoughts about a Brain inspired Organization (BiO)

Posted by Peter Rudin on 6. October 2017 in Essay No Comments

While current machine-learning efforts are mainly focused on extracting knowledge from ‘big-data’, the next stage of Artificial General Intelligence (AGI) will provide systems with learning and decision making capabilities equivalent to those of a human.

Consequently we have the opportunity to create an intelligent organization, modelled on the architecture of the human brain in short a thought model of a Brain inspired Organization (BiO).

Decision-making is one of the fundamental tasks of any organization. Thanks to its continuous, unlimited learning capacity for knowledge generation applying AGI technology, a BiO is far more capable to adapt to change compared to a conventional organization.

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Reverse Engineering the Human Brain

Posted by Peter Rudin on 22. September 2017 in Essay No Comments

The human brain is the most elementary biological component of our socio-economic system yet very little is known as to how it functions. Some researchers believe that it makes no sense to reverse engineer something we don’t understand.

Regardless of these critics, heavily subsidized efforts are in full swing to crack the neural code and to find out how our brain works.

Today’s neural networks as applied in AI machine learning software have little in common with biological neural networks. In the context of AI, neural networks provide the software architecture to process huge amounts of data concurrently, while mathematical techniques and algorithms are used to extract ‘knowledge’ from this data, mimicking some limited functions of biological neurons.

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Content Personalization vs. Privacy and Trust

Posted by Peter Rudin on 8. September 2017 in Essay No Comments

Online content is becoming increasingly personalized. As firms have expanded their data collection efforts to link data across sites, everything from the advertisements a user sees to the top search results on Google has been enhanced for personal relevance.

The invasion of AI technology and Neuroscience is crossing the border into our private sphere. ‘Smart home’ applications based on IoT devices or bidirectional loudspeakers are opening new paths to profile the user including emotion sensing.

We all know that it takes years building trust, seconds to break and forever to repair. Trust requires transparency, something the big tech companies only partially provide. Many of us don’t trust Google, Facebook, Amazon and Co. but we like the convenience their products and services are providing.

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With Neuroscience and AI to a new level of Conversational Learning

Posted by Peter Rudin on 25. August 2017 in Essay No Comments

Classroom teaching with the large amount of knowledge educators have to transfer leaves little room for conversations. Yet it is widely recognized that formal lecturing and reading has a combined learning retention level of less than 20%.

As neuroscience and AI are beginning to complement each other, new learning algorithms like ‘reasoning’ and ‘relationship learning’ or new brain-inspired neural learning models are being developed.

Imagine you have a 24 hour/7 day access to an artificial personalized coach, answering questions about a topic you just learned in school or via MOOC- learning will be much more fun. The retention level will substantially increase and your motivation for life-long learning will remain high.

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AI+IoT+Neuroscience = the Intelligent Organization

Posted by Peter Rudin on 11. August 2017 in Essay No Comments

Dear Reader,

A year ago the singularity2030 website went live as a gift to myself for my 75th birthday. Since the beginning every Friday a Newsletter or Essay is published and the number of subscribers or visitors to the website has steadily grown.

I would like to say thank you to all friends, colleagues and partners that support me in this fascinating venture.

In its second year of operation the website starts with an Essay that opens a new chapter regarding the emergence of Singularity. The integration of AI, IoT and Neuroscience provides new and exciting scenarios to implement intelligent organizations managed by humans.

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Going from Digital Transformation to AGI: are we really ready?

Posted by Peter Rudin on 28. July 2017 in Essay No Comments

Currently, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. Different types of machine learning, such as speech recognition or identifying objects in an image, require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks.

In a paper published in the journal Neuron, Demis Hassabis, CEO of Google’s DeepMind subsidiary and three co-authors argue that only by better understanding human intelligence can we hope to push the boundaries of what artificial intellects can achieve.

A general intelligence will need more human-like characteristics—such as an intuitive understanding of the real world and more efficient ways of learning.

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