AI Fairness Requires Fighting Bias with Bias

Posted by Peter Rudin on 15. October 2021 in News No Comments

Bias is a tricky term in general, and psychiatrists have developed long treatises trying to explain what it is and how it works.

Most biases tend to creep into AI unintentionally, both in the coding of the algorithm and the selection of training data. This means organizations must actively counter this bias by fostering diversity, training employees to spot biases and in general constantly monitor the output of AI processes to ensure that the results are fair.

Without the ability to account for the bias that exists all around us, it will never provide equal service to all. And even then, we must avoid the temptation to think that we will achieve a state of perfect fairness from AI.

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A Single Neuron is a Computer a New Study Finds

Posted by Peter Rudin on 1. October 2021 in News No Comments

Comparing brains to computers is a long and dearly held analogy in both neuroscience and computer science.

Deep learning, a powerful form of artificial intelligence, for example, is loosely modelled on the brain’s vast, layered networks of neurons.

In the study, the team found it took a five- to eight-layer neural network, or nearly 1,000 artificial neurons, to mimic the behavior of a single biological neuron from the brain’s cortex.

So far, following the brain’s blueprint has been a rewarding strategy. And if this work is any indication, future neural networks may well dwarf today’s networks in size and complexity.

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Mapping the Brain Circuitry of Spirituality

Posted by Peter Rudin on 17. September 2021 in News No Comments

Over eighty percent of the global population consider themselves religious, with even more identifying as spiritual, but the neural substrates of spirituality and religiosity remain unresolved.

Scientists have long suspected that religiosity and spirituality could be mapped to specific brain circuits.

Now, a new study using novel technology and the human connectome, a map of neural connections, has identified a brain circuit that seems to mediate this aspect of our personality.

These findings suggest that spirituality and religiosity map to a common brain circuit previously implicated in fear conditioning, pain modulation and altruistic behavior.

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Can AI Predict Behavior from Brain Activity?

Posted by Peter Rudin on 3. September 2021 in News No Comments

A new neuroscience study backed with funding from the European Research Council, published in eLife,  demonstrates how an AI deep learning algorithm is able to predict behavior by decoding brain activity.

In efforts to decipher the neural code, the researchers created an AI-based convolutional neural network (CNN,  to predict behaviors from neural activity.

In the last step, the team tested the AI-algorithm with electrocorticography recordings taken from brains of humans while moving their fingers.

The researchers demonstrated successfully that measuring neural activity can decode and predict finger movement and spatial behaviors with AI.

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Consciousness Research: ‘Dopamine’ Plays a Key Role

Posted by Peter Rudin on 20. August 2021 in News No Comments

Consciousness is arguably one of the most important scientific topics there is. Without consciousness, there would after all be no science. But while we all know what it is like to be conscious – meaning that we have personal awareness and respond to the world around us – it has turned out to be near impossible to explain exactly how it arises from the hardware of the brain. This is dubbed the “hard” problem of consciousness.

The brain is more than just a congregation of different areas. Brain cells also rely on a number of chemicals to communicate with other cells, enabling a number of brain functions. Dopamine is a chemical primarily released to the cortex region of the brain. New research gives hope for treatments of consciousness disorders, using drugs that act on dopamine.

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Quantum Computing: Google Creates Time Crystal

Posted by Peter Rudin on 6. August 2021 in News No Comments

Considered a major accomplishment for fundamental physics and quantum physics, scientists say they have figured out how to manufacture a scientific oddity called a time crystal.

Time crystals harness a quirk of physics in which they remain ever-changing yet dynamically stable. In other words, they don’t give off energy as they change conformation, evading the second  law of thermodynamics which states that all things irreversibly turn towards entropy and disorder.

If the new research holds up then we may find ourselves in a world with practical, powerful quantum computers that can actually solve computational problems which so far were beyond human reach.

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OpenAI Disbands Its Robotics Research Team

Posted by Peter Rudin on 23. July 2021 in News No Comments

OpenAI has disbanded its robotics team after years of research into machines that can learn to perform tasks like solving a Rubik’s Cube, shifting its focus to other domains, where data is more readily available.

“Because of the rapid progress in AI and its capabilities, we’ve found that other approaches, such as reinforcement learning with human feedback, lead to faster progress in our reinforcement learning research”, OpenAI cofounder Zaremba said.

Moving away from robotics might also reflect the economic realities the company faces. DeepMind, the Alphabet-owned AI research lab, has undergone a similar shift due to rising R&D cost in favour of work with applications, like protein shape prediction.

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Robots May Soon Be Able To Reproduce

Posted by Peter Rudin on 9. July 2021 in News No Comments

A team of researchers have recently demonstrated a fully automated technology to allow physical robots to repeatedly breed, evolving their artificial genetic code over time to better adapt to their environment.

The idea of digital evolution – imitating biological evolution in software to successively breed better and better solutions to a problem over time – is not new.

While scientists have always been confident that digital evolution could be effective as an optimisation tool, its creativity in producing original and unusual design has been more surprising. Unlike natural evolution which is driven simply by the goals of “survival and reproduction”, artificial evolution can be driven by specific targets.

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Will Reinforcement Learning Achieve General AI ?

Posted by Peter Rudin on 25. June 2021 in News No Comments

In a new paper, scientists at Google’s DeepMind AI research unit argue that intelligence and its associated abilities will emerge not from formulating and solving complicated problems but by sticking to a simple but powerful principle: reward maximization.

Reinforcement learning formalises the problem of goal-seeking intelligence. The general problem may be instantiated with a wide and realistic range of goals and worlds, corresponding to different reward signals to maximise in different environments.

The researchers also acknowledge that learning mechanisms for reward maximization is an unsolved problem that remains a central question to be further studied in reinforcement learning.

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Will AI Succeed? Quantum Theory Suggests Otherwise

Posted by Peter Rudin on 11. June 2021 in News No Comments

Will artificial intelligence one day surpass human thinking? The rapid progress of AI has raised concerns that its abilities will grow uncontrollably, eventually wiping out humanity.

One argument against the possibility reaching this level of intelligence comes from the fact that AI would need to accurately predict the future.

Quantum Theory, one of modern science’s key concepts for explaining the universe, says that predicting the future may not be possible because the universe is random. The next Singularity2030 Essay ‘Quantum Theory to Overcome the limits of AI’, to be published on June 18, 2021, augments this discussion. 

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