Author(s): Jesus Rodriguez Originally published on Towards AI. Created Using IdeogramI recently started an AI-focused educational newsletter, that already has over 170,000 subscribers. TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers, and concepts. Please give it a try by subscribing below:
The reliable control of traveling waves emerging from the coupling of oscillations and diffusion in physical, chemical and biological systems is a long-standing challenge within the physics community. Effective approaches to control these waves help to improve the present understanding of reaction-diffusion systems and their underlying dynamics.
Researchers at Université libre de Bruxelles (ULB) and Université de Rennes recently demonstrated a promising approach to control chemical waves in a type of fluid flow known as hyperbolic flow. Their experimental methods, outlined in Physical Review Letters recently, entail the control of chemical waves via the stretching and compression of fluids.
“At a summer school in Corsica, discussions between the Brussels and Rennes team triggered the curiosity to see how chemical waves studied at ULB in Brussels would behave in hyperbolic flows analyzed in Rennes,” Anne De Wit, senior author of the paper, told Phys.org. “The primary objective was to see how a non-trivial flow would influence the dynamics of waves.”
A study suggests that by the time H. sapiens expanded, the differentiation between the two species had progressed to the extent that they were distinct and recognizable as separate species.
A recent study conducted by researchers from London’s Natural History Museum and the Institute of Philosophy at KU Leuven has strengthened the argument that Neanderthals and modern humans (Homo sapiens) should be classified as distinct species to more accurately trace our evolutionary history.
Different researchers have different definitions as to what classifies as a species. It is undisputed that H. sapiens and Neanderthals originate from the same parental species, however studies into Neanderthal genetics and evolution have reignited the debate over whether they should be classed as separate from H. sapiens or rather a subspecies (H. sapiens neanderthalensis).
Mosasaurs are extinct marine lizards, spectacular examples of which were first discovered in 1766 near Maastricht in the Netherlands, fueling the rise of the field of vertebrate paleontology. Paleontologist Michael Polcyn presented the most comprehensive study to date on the early evolution and ecology of these extinct marine reptiles.
On 16 December, Polcyn will receive his Ph.D. from Utrecht University for his research into the evolution of the mosasaurs. Mosasaurs are a textbook example of macroevolution, the emergence of new and distinct groups of animals, above the level of species. Although they have been studied for centuries, new discoveries, novel research approaches, and the application of technology, are still teaching us about their relationships and behaviors, some of which continue to surprise us.
For example, through the use of detailed comparative anatomy aided by micro-CT scanning technology, we have gained a much better understanding of what group of lizards mosasaurs likely evolved from.
Dopamine is a powerful signal in the brain, influencing our moods, motivations, movements, and more. The neurotransmitter is crucial for reward-based learning, a function that may be disrupted in a number of psychiatric conditions, from mood disorders to addiction.
Now, researchers led by MIT Institute Professor Ann Graybiel have found surprising patterns of dopamine signaling that suggest neuroscientists may need to refine their model of how reinforcement learning occurs in the brain. The team’s findings were published recently in the journal Nature Communications.
Dopamine plays a critical role in teaching people and other animals about the cues and behaviors that portend both positive and negative outcomes; the classic example of this type of learning is the dog that Ivan Pavlov trained to anticipate food at the sound of bell.
Through MIT OpenCourseWare, MITx, and MIT xPRO learn about machine learning, computational thinking, deepfakes, and more, all for free.
With the rise of artificial intelligence, the job landscape is changing — rapidly. MIT Open Learning offers online courses and resources straight from the MIT classroom that are designed to empower learners and professionals across industries with the competencies essential for succeeding in an increasingly AI-powered world.
They say beauty is in the eye of the beholder – and for physicists, beauty is in numbers.
Pedro Vieira, Clay Riddell Dirac Chair in Theoretical Physics at Perimeter Institute, is currently teaching a non-credit minicourse about ‘beautiful’ papers in physics. The course alternates between lectures on nine influential papers and student-led presentations about how these monumental papers influenced physics.
This is Vieira’s second time running the course and his first time offering it at Perimeter. He says the course is a way to cover spectacular papers while helping students understand the language of quantum field theory.
We are about to show you a technological innovation that could, one day, change the way every child in every school in America is taught. It’s an online tutor powered by artificial intelligence designed to help teachers be more efficient… and students learn more effectively. It’s called Khanmigo–conmigo means “with me,” in Spanish. And Khan…is its creator…Sal Khan, the well-known founder of Khan Academy — whose lectures and educational software have been used for years by tens of millions of students and teachers in the U.S. and around the world. Khanmigo was built with the help of OpenAI, the creator of ChatGPT. Its potential is staggering, but it’s still very much a work in progress. It’s being piloted in 266 school districts in the U.S. in grades three-12. We went to Hobart High School in Indiana to see how it works.
Melissa Higgason: Good morning, just a normal day in chem, right?
At eight in the morning Melissa Higgason knows it’s not always easy to get 30 high schoolers excited about chemistry.
Chatbots can wear a lot of proverbial hats: dictionary, therapist, poet, all-knowing friend. The artificial intelligence models that power these systems appear exceptionally skilled and efficient at providing answers, clarifying concepts, and distilling information. But to establish trustworthiness of content generated by such models, how can we really know if a particular statement is factual, a hallucination, or just a plain misunderstanding?
In many cases, AI systems gather external information to use as context when answering a particular query. For example, to answer a question about a medical condition, the system might reference recent research papers on the topic. Even with this relevant context, models can make mistakes with what feels like high doses of confidence. When a model errs, how can we track that specific piece of information from the context it relied on — or lack thereof?
To help tackle this obstacle, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers created ContextCite, a tool that can identify the parts of external context used to generate any particular statement, improving trust by helping users easily verify the statement.
The ContextCite tool from MIT CSAIL can find the parts of external context that a language model used to generate a statement. Users can easily verify the model’s response, making the tool useful in fields like health care, law, and education.
Nearly half a dozen institutions of higher education separately announced plans this week to make tuition free for undergraduates who meet certain income requirements, reflecting a growing nationwide effort to make college more affordable.
The schools span states from Massachusetts to New Mexico, and include some of the country’s leading universities. They all announced their initiatives within days of each other. And while the specific financial requirements for current students applicants vary between schools, all are slated to take effect in fall 2025.
The Massachusetts Institute of Technology in Cambridge, for example, says undergraduates with family income below $200,000 can attend tuition free starting next year, up from its current threshold of $140,000. It said in its announcement that 80% of American households meet the updated threshold.