A short blog post today, on how pull backs on predictions for autonomous cars should inform our evaluations of predictions on timing of AGI. https://rodneybrooks.com/agi-has-been-delayed/
Announcing the first 𝗜𝗖𝗖𝗩 𝘄𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗼𝗻 𝗦𝗰𝗲𝗻𝗲 𝗚𝗿𝗮𝗽𝗵 𝗥𝗲𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴. If your research involves structured data or graph-based learning, consider submitting to us by August 15, 2019: https://sgrl.stanford.edu
"Human Visual Understanding for Cognition and Manipulation -- A primer for the roboticist," Martin Hjelm: https://arxiv.org/abs/1905.05272
MeshCNN: A Network with an Edge https://ranahanocka.github.io/MeshCNN/
After point clouds (PoinNet style) this is an extension of neural networks to work directly on 3D meshes with mesh convolutions, pooling and unpooling operators.
An interactive article explaining why weight initialization is so important for training neural nets by @email@example.com, written in the http://distill.pub format. https://www.deeplearning.ai/ai-notes/initialization/
The academic job market
Difficult problems in the real world often require thinking more than one step in advance. Researchers from @IBMResearch@twitter.com discuss how we can teach the human concept of "planning" to AI. #IBM #planning
Check out our new blog in which we highlight our latest results. The first entry is on our CVPR 2019 paper "Occupancy Networks - Learning 3D Reconstruction in Function Space" in which propose a new output representation for 3D deep-learning. https://autonomousvision.github.io/occupancy-networks/
Excited to announce our #NeurIPS2019 competition: The MineRL Competition for Sample-Efficient Reinforcement Learning! With @firstname.lastname@example.org @email@example.com @firstname.lastname@example.org @email@example.com @firstname.lastname@example.org @OriolVinyalsML@twitter.com @email@example.com and others!
Participate here! http://minerl.io/competition
This is clearly the right way to present related work.
If there are a million Tesla robo-taxis functioning on the road in 2020, I will eat them. Perhaps @firstname.lastname@example.org will eat half with me? https://twitter.com/rodneyabrooks/status/1125964714087993344
Officially presenting HYPE at @email@example.com! If you train generative models and would like to see how yours fairs against the state of the art, please see our competition at https://hype.stanford.edu/
If you're at the conference, come get HYPE'd today in room R02! #ICLR2019
Adversarial Examples Are Not Bugs, They Are Features
"adversarial examples can be directly attributed to the presence of non-robust features ... patterns in the data distribution that are highly predictive, yet brittle and incomprehensible to humans"
Our digest of the last week in AI news is out!
Click on for a summary of the major stories about AI related to advances & business, concerns & hype, analysis & policy, and more.
Something nice: the great video game critic @Campster@twitter.com (re-posted) a video of him trying out something new which he thought "didn't work", and the comments are FULL of positivity as well as real constructive feedback. The internet ain't so bad sometimes...
Interesting thought: Twitter (and other social media) enable more widespread and distributed #scicomm , as opposed to a few high profile scientists doing most of the communication to broader public. Surely a good thing!
If you have a problem w scientists on Twitter, then don't follow them. A few reasons why I love Twitter: (1) we show scientists are ppl too, (2) learn sci outside my own discipline, (3) share gr8 work from colleagues, and (4) my mom isn't on here yet. https://twitter.com/Alex_Washburne/status/1123626408629039105
CS PhD at Stanford Vision Lab. Creator/lead editor http://skynettoday.com 🤖 Into AI, robots, cinema, coding, photography. Russian.
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