Tag Archives: neural

Uninterrupted Deep Work Mix ~ Immersive Productivity Soundscape ~ Neural Focus Study Music

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Uninterrupted Deep Work Mix ~ Immersive Productivity Soundscape ~ Neural Focus Study Music
#DeepWork #FocusMusic #BrainwaveWorkspace #Productivity
Maximize your output with Brainwave Workspace. 🚀 This Uninterrupted Deep Work Mix is an immersive productivity soundscape crafted to keep you in a neural focus study music state for hours. 🌲

How long can you stay in a deep flow state without a break?
What kind of work are you tackling today?
Does a forest environment like this help you relax while working?

Engage with us in the comments! 👇 Your tips on productivity help everyone in the Brainwave Workspace community. Hit that notification bell!

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© Music and video belong to Brainwave Workspace. All rights reserved. 🚫 Please do not reupload in any form to confirm copyright.

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Brett Adcock: Humanoids Run on Neural Net, Autonomous Manufacturing, and $50 Trillion Market #229

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Peter u0026 Dave sit down with Brett Adcock to discuss the future of Figure and Humanoid Robots.

Get access to metatrends 10+ years before anyone else/ Humanoid report coming soon – https://qr.diamandis.com/metatrends

Brett Adcock is the founder of Figure, an AI robotics company developing general-purpose humanoid robots. (https://www.figure.ai/ )

Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360

Dave Blundin is the founder u0026 GP of Link Ventures

Chapters

(0:00) – The Entrepreneurial Mindset: From Idea to Exponential Impact
(7:32) – Humanoid Robots: The Next Frontier in Abundance
(19:10) – Convergence: AI, Software, and Physical Embodiment
(35:10) – The New Industrial Revolution: Reimagining Labor and Productivity
(48:20) – Solving the Global Labor Crisis through Automation
(58:09) – The Exponential Roadmap: Deploying Robots at Scale
(1:10:05) – Building Generational Companies to Uplift Humanity

–-

My companies:

Apply to Dave's and my new fund: https://qr.diamandis.com/linkventureslanding

Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy
_

Connect with Brett:
X: https://x.com/adcock_brett
Website: https://www.brettadcock.com/

Connect with Peter:
X: https://qr.diamandis.com/twitter
Instagram: https://qr.diamandis.com/instagram
A360 Livestream access: https://www.abundance360.com/livestream

Connect with Dave:
X: https://x.com/davidblundin
LinkedIn: https://www.linkedin.com/in/david-blundin/

Listen to MOONSHOTS:

Apple: https://qr.diamandis.com/applepodcast
Spotify: https://qr.diamandis.com/spotifypodcast

*Recorded on January 27th, 2026
*The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice.

Gradient descent, how neural networks learn | Deep Learning Chapter 2

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Cost functions and training for neural networks.
Help fund future projects: https://www.patreon.com/3blue1brown
Special thanks to these supporters: http://3b1b.co/nn2-thanks
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks

This video was supported by Amplify Partners.
For any early-stage ML startup founders, Amplify Partners would love to hear from you via 3blue1brown@amplifypartners.com

To learn more, I highly recommend the book by Michael Nielsen
http://neuralnetworksanddeeplearning.com/
The book walks through the code behind the example in these videos, which you can find here:
https://github.com/mnielsen/neural-networks-and-deep-learning

MNIST database:
http://yann.lecun.com/exdb/mnist/

Also check out Chris Olah's blog:
http://colah.github.io/
His post on Neural networks and topology is particular beautiful, but honestly all of the stuff there is great.

And if you like that, you'll *love* the publications at distill:
https://distill.pub/

For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs

"But I've already voraciously consumed Nielsen's, Olah's and Welch's works", I hear you say. Well well, look at you then. That being the case, I might recommend that you continue on with the book "Deep Learning" by Goodfellow, Bengio, and Courville.

Thanks to Lisha Li (@lishali88) for her contributions at the end, and for letting me pick her brain so much about the material. Here are the articles she referenced at the end:
https://arxiv.org/abs/1611.03530
https://arxiv.org/abs/1706.05394
https://arxiv.org/abs/1412.0233

Music by Vincent Rubinetti:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown

Thanks to these viewers for their contributions to translations
Звуковая дорожка на русском языке: Влад Бурмистров.
Hebrew: Omer Tuchfeld
Italian: @teobucci

——————-
Video timeline
0:00 – Introduction
0:30 – Recap
1:49 – Using training data
3:01 – Cost functions
6:55 – Gradient descent
11:18 – More on gradient vectors
12:19 – Gradient descent recap
13:01 – Analyzing the network
16:37 – Learning more
17:38 – Lisha Li interview
19:58 – Closing thoughts
——————

3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).

If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended

Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown

But what is a neural network? | Deep learning chapter 1

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Video Description

What are the neurons, why are there layers, and what is the math underlying it?
Help fund future projects: https://www.patreon.com/3blue1brown
Written/interactive form of this series: https://www.3blue1brown.com/topics/neural-networks

Additional funding for this project was provided by Amplify Partners

For those who want to learn more, I highly recommend the book by Michael Nielsen that introduces neural networks and deep learning: https://goo.gl/Zmczdy

There are two neat things about this book. First, it's available for free, so consider joining me in making a donation to Nielsen if you get something out of it. And second, it's centered around walking through some code and data, which you can download yourself, and which covers the same example that I introduced in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning

I also highly recommend Chris Olah's blog: http://colah.github.io/

For more videos, Welch Labs also has some great series on machine learning:
https://youtu.be/i8D90DkCLhI
https://youtu.be/bxe2T-V8XRs

For those of you looking to go *even* deeper, check out the text "Deep Learning" by Goodfellow, Bengio, and Courville.

Also, the publication Distill is just utterly beautiful: https://distill.pub/

Lion photo by Kevin Pluck

Звуковая дорожка на русском языке: Влад Бурмистров.

Thanks to these viewers for their contributions to translations
German: @fpgro
Hebrew: Omer Tuchfeld
Hungarian: Máté Kaszap
Italian: @teobucci, Teo Bucci

—————–
Timeline:
0:00 – Introduction example
1:07 – Series preview
2:42 – What are neurons?
3:35 – Introducing layers
5:31 – Why layers?
8:38 – Edge detection example
11:34 – Counting weights and biases
12:30 – How learning relates
13:26 – Notation and linear algebra
15:17 – Recap
16:27 – Some final words
17:03 – ReLU vs Sigmoid

Correction 14:45 – The final index on the bias vector should be "k"

——————
Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim

If you want to check it out, I feel compelled to warn you that it's not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.

Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown

Stream the music on Spotify:
https://open.spotify.com/album/1dVyjwS8FBqXhRunaG5W5u

If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then "add subtitles/cc". I really appreciate those who do this, as it helps make the lessons accessible to more people.
——————

3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you're into that).

If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended

Various social media stuffs:
Website: https://www.3blue1brown.com
Twitter: https://twitter.com/3Blue1Brown
Patreon: https://patreon.com/3blue1brown
Facebook: https://www.facebook.com/3blue1brown
Reddit: https://www.reddit.com/r/3Blue1Brown