Lifeboat Foundation

Human cerebral organoids are three-dimensional biological cultures grown in the laboratory to mimic as closely as possible the cellular composition, structure, and function of the corresponding organ, the brain. For now, cerebral organoids lack blood vessels and other characteristics of the human brain, but are also capable of having coordinated electrical activity. They have been usefully employed for the study of several diseases and the development of the nervous system in unprecedented ways. Research on human cerebral organoids is proceeding at a very fast pace and their complexity is bound to improve. This raises the question of whether cerebral organoids will also be able to develop the unique feature of the human brain, consciousness. If this is the case, some ethical issues would arise. In this article, we discuss the necessary neural correlates and constraints for the emergence of consciousness according to some of the most debated neuroscientific theories. Based on this, we consider what the moral status of a potentially conscious brain organoid might be, in light of ethical and ontological arguments. We conclude by proposing a precautionary principle and some leads for further investigation. In particular, we consider the outcomes of some very recent experiments as entities of a potential new kind.

We know students learn science concepts better when their learning is embedded in real-world issues. But teachers are currently not well prepared to teach science in this way.

Philosophy is often ridiculed by scientists as being little more than armchair speculation. Stephen Hawking famously declared it “dead.” This is unfortunate because the scientific method itself is a manifestation of philosophical thought arising from the subdiscipline known as epistemology. Historically, science and philosophy have worked hand-in-glove to advance our understanding of the world. In fact, “science” went by the moniker “natural philosophy” for much of history.

Scientists perhaps should be a bit more grateful. Advances in social and political philosophy helped prevent some scientists who upset the established order from being executed — but that’s a discussion for another day. Here, we will examine three philosophical insights that directly led to advances in how science is performed.

“What makes science different from everything else?” is inherently a philosophical question. That means that philosophy helps define what science is. This is important because, to learn about the world, we need to be sure of the validity of our methods. For most of the history of Western philosophy, Aristotle’s ideas reigned supreme. While Aristotle’s idea of finding causes through science was largely based on deductive reasoning, experimentation was not seen as a vital part of science.

Can human-aware artificial intelligence help accelerate science? In this article, the authors incorporate the distribution of human expertise by training unsupervised models on simulated inferences cognitively accessible to experts and show that this substantially improves the models’ predictions of future discoveries, but also enables AI to generate high-value alternatives that complement human discoveries.

In today’s column, I am going to identify and explain the momentous pairing of both generative AI and data science. These two realms are each monumental in their own respective ways, thus they are worthy of rapt attention on a standalone basis individually. On top of that, when you connect the dots and bring them together as a working partnership, you have to admire and anticipate big changes that will arise, especially as the two fields collaboratively reinvent data strategies all told.

This is entirely tangible and real-world, not merely something abstract or obtuse.

I will first do a quick overview of generative AI. If you are already versed in generative AI, perhaps do a fast skim on this portion.

Continue reading “Generative AI And Data Science Have Mightily Paired Up To Reinvent Data Strategies, Exemplified Via Release Of OpenAI’s ChatGPT Code Interpreter” »

If you’ve found yourself befuddled by extraordinary scientific-sounding claims, you’re not alone. But this centuries-old lesson can help.

Students at the Bay Area’s best universities once dreamed of working for Apple, Google and Meta. Then the lay-offs happened | 1843 magazine.

With artificial intelligence poised to assist in profound scientific discoveries that will change the world, Cornell is leading a new $11.3 million center focused on human-AI collaboration that uses mathematics as a common language.

The Scientific Artificial Intelligence Center, or SciAI Center, is being launched with a grant from the Office of Naval Research and is led by Christopher J. Earls, professor of civil and environmental engineering at Cornell Engineering. Co-investigators include Nikolaos Bouklas, assistant professor of mechanical and aerospace engineering at Cornell Engineering; Anil Damle, assistant professor of computer science in the Cornell Ann S. Bowers College of Computing and Information Science; and Alex Townsend, associate professor of mathematics in the College of Arts and Sciences. All of the investigators are field faculty members of the Center for Applied Mathematics.

With the advance of AI systems – built with tangled webs of algorithms and trained on increasingly large sets of data – researchers fear AI’s inner workings will provide little insight into its uncanny ability to recognize patterns in data and make scientific predictions. Earls described it as a situation at odds with true scientific discovery.

To celebrate the completion of the James Webb Space Telescope’s first year of science operations, NASA has released a close-up image of the birth of sun-like stars.

The image, captured on Webb’s telescope is a small star-forming region in the Rho Ophiuchi cloud complex – the nearest star-forming region to Earth.

The region’s proximity at 390 light-years allows for a highly detailed close-up, with no foreground stars in the intervening space.