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WASHINGTON, Oct 6 (Reuters) — Since beginning operations last year, the James Webb Space Telescope has provided an astonishing glimpse of the early history of our universe, spotting a collection of galaxies dating to the enigmatic epoch called cosmic dawn.

But the existence of what appear to be massive and mature galaxies during the universe’s infancy defied expectations — too big and too soon. That left scientists scrambling for an explanation while questioning the basic tenets of cosmology, the science of the origin and development of the universe. A new study may resolve the mystery without ripping up the textbooks.

The researchers used sophisticated computer simulations to model how the earliest galaxies evolved. These indicated that star formation unfolded differently in these galaxies in the first few hundred million years after the Big Bang event 13.8 billion years ago that initiated the universe than it does in large galaxies like our Milky Way populating the cosmos today.

Blucap Moto has developed new navigational augmented reality sunglasses.

To listen to more of John Wheeler’s stories, go to the playlist: https://www.youtube.com/playlist?list=PLVV0r6CmEsFzVlqiUh95Q881umWUPjQbB

American physicist, John Wheeler (1911−2008), made seminal contributions to the theories of quantum gravity and nuclear fission, but is best known for coining the term ‘black holes’. A keen teacher and mentor, he was also a key figure in the Manhattan Project. [Listener: Ken Ford]

Continue reading “John Wheeler — Kurt Gödel and the Closed Time-like Line” »

The most widely used machine learning algorithms were designed by humans and thus are hindered by our cognitive biases and limitations. Can we also construct meta-learning algorithms that can learn better learning algorithms so that our self-improving AIs have no limits other than those inherited from computability and physics? This question has been a main driver of my research since I wrote a thesis on it in 1987. In the past decade, it has become a driver of many other people’s research as well. Here I summarize our work starting in 1994 on meta-reinforcement learning with self-modifying policies in a single lifelong trial, and — since 2003 — mathematically optimal meta-learning through the self-referential Gödel Machine. This talk was previously presented at meta-learning workshops at ICML 2020 and NeurIPS 2021. Many additional publications on meta-learning can be found at https://people.idsia.ch/~juergen/metalearning.html.

Jürgen Schmidhuber.
Director, AI Initiative, KAUST
Scientific Director of the Swiss AI Lab IDSIA
Co-Founder & Chief Scientist, NNAISENSE
http://www.idsia.ch/~juergen/blog.html.

Continue reading “Meta-Learning Machines in a Single Lifelong Trial” »

This video discusses what it would mean to live forever or to have a greatly expanded lifespan. Would we inevitably grow bored with existence? Why do we even want to live longer?

We also discuss the philosophy of the Ship of Theseus as it applies to mind upload or body transfer. If you transfer your mind to a new body, are you still the same person? We conclude that the answer is yes if and only if you experience no discontinuities in consciousness.

Continue reading “How humans will reach beyond biological bodies” »

Physicists have used the famous particle smasher to investigate the strange phenomena of quantum entanglement at far higher energies than ever before.

By Alex Wilkins

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Continue reading “Higher HRV, Lower RHR: Potential Impacts For Weight Loss And Consistent Exercise Training” »

James Somers on how A.I. chatbots such as ChatGPT and Google’s Bard will continue to learn and the contradictions entailed in their mission.