At the end of of 2022, we released a film offering a reply to the fine tuning argument for God from leading physicists and philosophers of physics. This included both those that doubt there is any fine tuning and those that think there is but it can be solved by naturalistic means.
Subsequently astrophysicist Luke Barnes and philosopher Philip Goff offered their criticism of our criticism. Here we have assembled some of our original talking heads to review their criticism and offer a reply, defending the original position that fine tuning argument for God does not work.
Our original film can be found here: https://www.youtube.com/watch?v=jJ-fj3lqJ6M

Luke Barnes and Philip Goff’s reply is here: https://www.youtube.com/watch?v=QJYWkqOzUQ0&t=4036s and we also recommend this video on Bayes theorem on the Majesty of Reason Channel: https://www.youtube.com/watch?v=o1MdtyLL3Uw&t=4423s.

Our panel consists of Graham Priest, Distinguished Professor of Philosophy at The Graduate Center, City University of New York, well known for his work in logic especially non classical logic, the philosophy of mathematics and science and Buddhist philosophy.

Barry Loewer, who is the distinguished professor of philosophy at Rutgers University and director of the Rutgers Center for Philosophy and the Sciences. Barry specialises in philosophy of science and philosophical logic and the foundations of quantum mechanics, statical mechanics and probability.

Dan Linford who is one of the rising stars in the intersection of the philosophy of physics and philosophy of religion. He did his Phd in philosophy, under Paul Draper and had well known atheist cosmologist Sean Carroll and theistic fine tuning advocate Rob Collins on his thesis committee. He’s now doing a postdoc at the University of Nebraska and recently authored the book Existential Inertia and Classical Theistic Proofs with Joe Schmidt.

Niayesh Afshordi who is an astrophysicist and cosmologist, he’s Professor at the University fo Waterloo and faculty at the Permitter Institute for Theoretical physics. Niayesh won the silver medal at the world physics Olympiad as a teenager, won 1st prize the The Buchalter Cosmology Prize and works in a variety of fields from early universe cosmology, black holes, dark energy and quantum gravity.

For their new study, the researchers aimed to understand how quantum correlations inside a source material, be it a gas or a mineral, would impact the quantum properties of the light bursts coming out, if at all. “High harmonic generation is a very important area. And still, until recently, it was described by a classical picture of light,” Kaminer says.

In quantum mechanics, figuring out what’s going on with more than a few particles at the same time is notoriously difficult. Kaminer and Alexey Gorlach, a graduate student in his lab, used their COVID-imposed isolation to try to make progress on a fully quantum description of light emitted in high harmonics. “It’s really crazy; Alexey built a super complex mathematical description on a scale that we’ve never had before,” Kaminer says.

Next, to fully incorporate the quantum properties of the material used to generate this light, Kaminer and Gorlach teamed up with Andrea Pizzi, then a graduate student at the University of Cambridge and now a postdoctoral fellow at Harvard University.

Mathematical research from the University of Bath in the United Kingdom has shed new light on the formation and behavior of crowds.

Have you ever pondered how people, without having a discussion or even giving it a second thought, instinctively form lanes when walking through a crowded area?

A new theory, developed by mathematicians at the University of Bath in the UK and led by Professor Tim Rogers, explains this phenomenon. This theory is able to predict when lanes will be straight but also when they will be curved.

Algorithms are complex mathematical formulas used to perform tasks in our digital world. They are programmed to process information, make decisions, and take actions. Algorithms are used in various applications, such as search engines, social media, autonomous vehicles, and digital assistants.

But not all algorithms are innocent. Some algorithms have a sinister #scary side that poses a threat to our privacy, our freedom, and our humanity… #aiscarystories #aihorrorstories #scarystories #scarystory #horrorstories #horrorstory #realstories #realhorrorstories #realscarystories #truestories #truestory #creapystories #AIScarystory #AIHorror #artificialintelligence #scaryai #scaryartificialintelligence #trueaiscarystories #truescarystories.

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OpenAI has released a new version of ChatGPT, claiming that the new language learning model is capable of passing – and even excelling in – a variety of academic exams.

ChatGPT-4, which will be available on Bing as well as the OpenAI website, is more reliable and more creative than its predecessor, according to OpenAI. The team tested the model on a number of exams designed for humans, from the bar exam to biology, using publicly available papers. While no additional training was given to the model ahead of the tests, it was able to perform well on most subjects, performing in the estimated 90th percentile for the bar exam and the 86th-100th in art history.

Just as the previous model was accused of being bad at math, this version struggled more with calculus, scoring in the 43rd-59th percentile.

An international team of planetary scientists has characterized some of the features of an exoplanet named HD-207496-b, located approximately 138 light years from Earth. In their paper accepted for publication in the journal Astronomy & Astrophysics, and currently posted on the arXiv preprint server, the group describes their study of the exoplanet and the two theories regarding its likely makeup.

The exoplanet HD-207496-b was discovered as part of a larger effort to characterize naked core planets. As such, the team was analyzing HARPS spectroscopic observations of HD-207496—a bright k dwarf. By adding TESS photometry data, the group was able to measure the stars’ brightness and wavelength, and by studying the exoplanet’s transit characteristics, the team was able to calculate its period, mass, radius and density. That led them to a bit of a conundrum—was the exoplanet gaseous or watery?

The researchers calculated that the exoplanet had a radius 2.25 times that of Earth, with an orbit of 6.44 days. And it had a mass that was approximately 6.1 times Earth’s. Simple math showed that the exoplanet had a density of 3.27 grams per cubic centimeter, which is less than that of Earth.

He was ranked the number 1 most influential neuroscientist in the world by Semantic Scholar in 2016, and has received numerous awards and accolades for his work. His appointment as chief scientist of Verses not only validates their platform’s framework for advancing AI implementations but also highlights the company’s commitment to expanding the frontier of AI research and development.

Friston is short listed for a Nobel Prize, is one of the most cited scientists in human history with over 260,000 academic citations, and invented all of the mathematics behind the fMRI scan. As one pundit put it, “what Einstein was to physics, Friston is to Intelligence.”

Indeed Friston’s expertise will be invaluable in helping the company execute its vision of deploying a plethora of technologies working toward a smarter world through AI.

Through a vast network of nerve fibers, electrical signals are constantly traveling across the brain. This complicated activity is what ultimately gives rise to our thoughts, emotions, and behaviors – but also possibly to mental health and neurological problems when things go wrong.

Brain stimulation is an emerging treatment for such disorders. Stimulating a region of your brain with electrical or magnetic pulses will trigger a cascade of signals through your network of nerve connections.

However, at the moment, scientists are not quite sure how these cascades travel to impact the activity of your brain as a whole – an important missing piece that limits the benefits of brain stimulation therapies.

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Kaggle notebook with all the code: https://www.kaggle.com/wwsalmon/simple-mnist-nn-from-scratch-numpy-no-tf-keras.

Blog article with more/clearer math explanation: https://www.samsonzhang.com/2020/11/24/understanding-the-mat…numpy.html