Brad Neuberg

347 Followers
611 Following
51 Posts
ML Engineer at Planet. Research w/ Frontier Development Lab. Prev @ Dropbox/Google. Started coworking. Interests: machine learning, space, earth observation, VR. He/Him, http://codinginparadise.org
machine learningearth observation
spacevirtual reality
@OpenSciTwente @jeroenbosman <waves> Hi! Unfortunately I actually didn’t know about that initiative before. Did you try archive.org?
@michael_nielsen @danb yeah that’s how I found both of you! Movetodoon converted as many of my Twitter followers to Mastodon followers as it could.
@judell @internetarchive I saw your name in that issue! It was awesome to see
Is there anything equivalent to Soul of a New Machine by Tracey Kidder but for the 2010+ era? Perhaps Liftoff! By @SciGuySpace but that’s more space than the computer field. https://a.co/d/31jx4sa https://a.co/d/iiPxDxv
I’m reading “Show Stopper!: The Breakneck Race to Create Windows NT and The Next Generation at Microsoft” from 1994, a fun, interesting snapshot in time right before Internet truly landed & changed PC landscape forever: https://a.co/d/hp41ovT
Reading 1991 Byte Magazine from @internetarchive on the Quest Pro browser with passthrough on
Engadget is part of the Yahoo family of brands

@karenmcgrane heads up that I think your personal website has a MIME type set incorrectly. On iOS browser tried to click it and it thought I was trying to download a binary file.
Very interesting review paper from 2022 of optical neural networks: https://www.mdpi.com/2076-3417/12/11/5338
A Review of Optical Neural Networks

With the continuous miniaturization of conventional integrated circuits, obstacles such as excessive cost, increased resistance to electronic motion, and increased energy consumption are gradually slowing down the development of electrical computing and constraining the application of deep learning. Optical neuromorphic computing presents various opportunities and challenges compared with the realm of electronics. Algorithms running on optical hardware have the potential to meet the growing computational demands of deep learning and artificial intelligence. Here, we review the development of optical neural networks and compare various research proposals. We focus on fiber-based neural networks. Finally, we describe some new research directions and challenges.

MDPI