Is it possible to enhance and rewire the adult brain?

From Guardian Science Weekly podcast: Nicola Davis asks: can we increase the window of brain plasticity in the later stages of life? And what do we know about the implications of doing so? In early development, the brain is hard at work making new connections between neurons, based on the new experiences we’re having. But the science around brain plasticity – ie the mind’s ability to learn, change and reorganise itself – is advancing. Research looking at people with severe neurological or physical damage tells us a lot about the possibility of enhancing the ability for our brain to rewire.

Custom carpentry with help from robots

From Every year thousands of carpenters injure their hands and fingers doing dangerous tasks such as sawing. In an effort to minimize injury and let carpenters focus on design and other bigger-picture tasks, a team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has created AutoSaw, a system that lets nonexperts customize different items that can then be constructed with the help of robots.

Waymo 360° experience: a fully self-driving journey

From Waymo began as the Google self-driving car project in 2009. Today, we have the world’s only fleet of fully self-driving cars on public roads. Step into our 360° video and take control of the camera to see through the “eyes” of our car. Then, be one of the first in the world to take a ride with Waymo. This film was built using footage and real-time data from an actual trip on city streets.

Tractor Hacking: The Farmers Breaking Big Tech's Repair Monopoly

From When it comes to repair, farmers have always been self reliant. But the modernization of tractors and other farm equipment over the past few decades has left most farmers in the dust thanks to diagnostic software that large manufacturers hold a monopoly over. In this episode of State of Repair, Motherboard goes to Nebraska to talk to the farmers and mechanics who are fighting large manufacturers like John Deere for the right to access the diagnostic software they need to repair their tractors.

Creative brains

From Your cat is smart, but its ability to choreograph a ballet or write computer code isn’t great. A lot of animals are industrious and clever, but humans are the only animal that is uniquely ingenious and creative. Neuroscientist David Eagleman and composer Anthony Brandt discuss how human creativity has reshaped the world. Find out what is going on in your brain when you write a novel, paint a watercolor, or build a whatchamacallit in your garage. But is Homo sapiens’ claim on creativity destined to be short-lived? Why both Eagleman and Brandt are prepared to step aside when artificial intelligence can do their jobs.

Optimal Transport Theory - New Frontiers in Mathematics - Cédric Villani

From New Frontiers in Mathematics: Imperial College London and CNRS international symposium Professor Villani from Université Claude Bernard (Lyon), discusses optimal transport theory, artificial intelligence and the journey and opportunities that a career in mathematics can offer.

Past, present, and future of neuroscience

From In this very special episode of Unsupervised Thinking, we bring together a group of neuroscientists and neuroscience enthusiasts to have a semi-structured discussion on the past, present, and future of the field of neuroscience. The group includes your three regular hosts plus Yann, Alex, and Ryan (whose voice you may recall from our Deep Learning episode) and we each give our thoughts on what got us into neuroscience, what we feel the field is lacking, and where the field will be in 20 years. This leads us on a path of discussing statistics, emergence, religion, depression, behavior, engineering, society, and more!

Fairness in Machine Learning: Lessons from Political Philosophy

From Abstract: What does it mean for a machine learning model to be `fair', in terms which can be operationalised? Should fairness consist of ensuring everyone has an equal probability of obtaining some benefit, or should we aim instead to minimise the harms to the least advantaged? Can the relevant ideal be determined by reference to some alternative state of affairs in which a particular social pattern of discrimination does not exist? Various definitions proposed in recent literature make different assumptions about what terms like discrimination and fairness mean and how they can be defined in mathematical terms. Questions of discrimination, egalitarianism and justice are of significant interest to moral and political philosophers, who have expended significant efforts in formalising and defending these central concepts. It is therefore unsurprising that attempts to formalise `fairness' in machine learning contain echoes of these old philosophical debates. This paper draws on existing work in moral and political philosophy in order to elucidate emerging debates about fair machine learning.

PDF link.


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