neuroscience AI Videos - Artificial Intelligence Videos

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11:01

Terrifying Animal Experiments • Brain-Computer Interfaces •

Long before Brain Computer Interface Companies such as Neuralink existed, there’ve always been Brain Experiments done on Animals with crazy results. Whether it’s looking through the eyes of a cat, a monkey controlling a computer robot arm, or controlling a living beetle. Many creepy, but also amazing inventions have been done in the field of […]

08:49

Reading Memories from the Human Brain – SECRET Brain Project

For the first time ever, Scientists working for the United States Government and Google have managed to read and understand a portion of a brain in real time. This is going to enable abilities such as reading minds and memories from humans in the future. The question is how long it will take until the […]

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10:16

YOU WILL want these New Robotic Limbs! – AI-Controlled Prosthetics

Advances in Artificial Intelligence, neuroscience and robotics have gotten us to a point where people might want to replace their biological limbs with robotic limbs due to there being more and more advantages with every passing day. Things like improved movement, intelligent controlling systems with the help of machine learning AI can help you control […]

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09:14

Becoming Immortal for 10,000$? – Upload Your Mind THIS DECADE!

Becoming Immortal through Mind Uploading sounds like something that’ll only be possible around the 2100’s. But amazingly, a group of scientists at Nectome are working on giving us the ability to live forever inside of a computer simulation by the end of this decade for around 10000$. Ray Kurzweil, director of engineering at Google, has […]

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10:45

Why People are Microchipping their Brains – Next-Gen BCI's: Neurograins

Neurograins might be the future of implantable Brain Computer Interfaces due to their advantages in terms of abilities and safety in terms of implantation. Due to being the smallest Microchips ever made, in addition to being very powerful, they can make very high resolution recordings of brain activity and even stimulate areas in the brain […]

21:03

Neural Data Science — Lecture 13 — Data management in neuroscience

Lecture 13 in the Neural Data Science course by Philipp Berens, Summer Term 2021 at the University of Tübingen. Source of this “Tübingen Machine Learning” AI Video

43:18

PaccMann^RL: Designing Anticancer Drugs with Reinforcement Learning w/ Jannis Born – #341

Today we’re joined by Jannis Born, Ph.D. student at ETH & IBM Research Zurich. We caught up with Jannis a few weeks back at NeurIPS, to discuss: His research paper “PaccMann^RL: Designing anticancer drugs from transcriptomic data via reinforcement learning,” a framework built to accelerate new anticancer drug discovery. How his background in cognitive science […]

40:56

What the Human Brain Can Tell Us About NLP Models with Allyson Ettinger – #483

Today we continue our ICLR ‘21 series joined by Allyson Ettinger, an Assistant Professor at the University of Chicago. One of our favorite recurring conversations on the podcast is the two-way street that lies between machine learning and neuroscience, which Allyson explores through the modeling of cognitive processes that pertain to language. In our conversation, […]

05:26

Cosyne 2021: Disparate energy consumption despite similar network activity

Disparate energy consumption despite similar network activity Michael Deistler, Pedro J. Gonçalves*, Jakob H. Macke* *These authors contributed equally to this work. Computational and Systems Neuroscience (Cosyne) 2021 Source of this “Tübingen Machine Learning” AI Video

07:57:30

Health Stage Live at CogX 2019 | CogX 2019

Join the CogX Global Leadership Summit and Festival of AI and Breakthroughs Technology – June 8th to 10th 2020 – https://cogx.co/ Subscribe to our epic newsletters for free https://cognitionx.com/newsletter-subscribe/ From digital blockbusters and revolutionary forms of medical imaging to advanced neuroscience and patient-centric care – As we prepare for ageing populations and 100-year lives, AI […]

47:06

Rebuilding the Brain from AI “Legos” – Interview with Kanaka Rajan – 524

Today we’re joined by Kanaka Rajan, an assistant professor at the Icahn School of Medicine at Mt Sinai. Kanaka, who is a recent recipient of the NSF Career Award, bridges the gap between the worlds of biology and artificial intelligence with her work in computer science. In our conversation, we explore how she builds “lego […]

46:46

Engineering a Less Artificial Intelligence with Andreas Tolias – #379

Today we’re joined by Andreas Tolias, Professor of Neuroscience at Baylor College of Medicine and Principal Investigator of the Neuroscience-Inspired Networks for Artificial Intelligence organization. We caught up with Andreas to discuss his recent perspective piece, “Engineering a Less Artificial Intelligence,” which explores the shortcomings of state-of-the-art learning algorithms in comparison to the brain. The […]

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08:02

Affective Deep Learning Research (TensorFlow Meets)

In this episode of TensorFlow Meets, Laurence chats with Christian Fanli Ramsey, Affective Deep Learning Researcher. They discuss Dyad X Machina and its goal of designing the affective layer into technology for people and groups. Watch to learn more about emotion versus cognition in neuroscience and what it means to work at the intersection of […]

55:28

Common Sense as an Algorithmic Framework with Dileep George – #430

Today we’re joined by Dileep George, Founder and the CTO of Vicarious. Dileep, who was also a co-founder of Numenta, works at the intersection of AI research and neuroscience, and famously pioneered the hierarchical temporal memory. In our conversation, we explore the importance of mimicking the brain when looking to achieve artificial general intelligence, the […]

01:30:51

#TWIMLfest: Office Hours – Reinforcement Learning

In the Office Hours series, we invite experts and practitioners in various topic areas for AMA (ask-me-anything) style sessions to answer community member questions. The intent is to answer technical questions and/or help participants advance their specific projects and interests. This week’s topic will be centered on Reinforcement Learning! Resources: Show notebooks in Drive – […]

39:33

Learning Long-Time Dependencies with RNNs w/ Konstantin Rusch – #484

Today we conclude our 2021 ICLR coverage joined by Konstantin Rusch, a Ph.D. Student at ETH Zurich. In our conversation with Konstantin, we explore his recent papers, titled coRNN and uniCORNN respectively, which focus on a novel architecture of recurrent neural networks for learning long-time dependencies. We explore the inspiration he drew from neuroscience when […]

21:11

CogX 2018 – Being a Beast Machine: Consciousness, AI, and Life | CogX

Join the CogX Global Leadership Summit and Festival of AI and Breakthroughs Technology – June 8th to 10th 2020 – https://cogx.co/ Subscribe to our epic newsletters for free https://cognitionx.com/newsletter-subscribe/ Stay up to date on All Things AI. Hand-picked news, insights and updates on the most important stories of the day. Subscribe to news briefings: https://cognitionx.com/newsletter-subscribe/ […]

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10:48

Dyad X Machina: bringing emotion into machine learning (TensorFlow Meets)

Dyad X Machina is a research partnership that combines affective neuroscience and deep learning. In this episode, Laurence meets with the co-founder, Haohan Wang, who explains Dyad’s mission as bringing emotion into machine learning. Haohan and her partner Christian created a course — Applied Deep Learning with TensorFlow and Google Cloud AI — that is […]

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39:21

NIPS 2015 Symposium: Brains, Minds and Machines (Demis Hassabis)

Neuroscience and the Quest for AI. How systems neuroscience can help in the quest for Artificial General Intelligence YouTube Source for this AI Video

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33:24

A systems neuroscience approach to building AGI – Demis Hassabis, Singularity Summit 2010

YouTube Source for this AI Video

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01:44:41

DeepMind x UCL | Deep Learning Lectures | 10/12 | Unsupervised Representation Learning

Unsupervised learning is one of the three major branches of machine learning (along with supervised learning and reinforcement learning). It is also arguably the least developed branch. Its goal is to find a parsimonious description of the input data by uncovering and exploiting its hidden structures. This is presumed to be more reminiscent of how […]

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02:39

Neuroscience and AI – Matt Botvinick