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memming

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[ my public key: https://keybase.io/memming; my proof: https://keybase.io/memming/sigs/Ry-gdNKWFJDaPe1z3lW7hHm33wvBGp2ep-r1j8e226M ]

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astera.org 7mo ago

Neuroscientist Doris Tsao joins Astera to lead its new neuroscience program

memming
1pts0
www.perplexity.ai 10mo ago

Perplexity Email Assistant (for max users)

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2pts1
plato.stanford.edu 1y ago

Supertasks (2022)

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2pts0
www.youtube.com 1y ago

Google to Post Warnings on Businesses with Fake Reviews [video]

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3pts0
bactra.org 1y ago

So You Think You Have a Power Law – Well Isn't That Special? (2007)

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1pts0
engineeringmedia.com 2y ago

The Map of Control Theory (2020)

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5pts0
en.wikipedia.org 2y ago

Vault (Organelle)

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en.wikipedia.org 3y ago

Eliminative Materialism

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en.wikipedia.org 5y ago

Pica (Wikipedia)

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www.rdgao.com 5y ago

Thoughts on NMA, Higher Education, and Computational Neuroscience

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2pts0
plato.stanford.edu 6y ago

Game Theory and Ethics [Stanford Encyclopedia of Philosophy]

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1pts0
laughingsquid.com 6y ago

1986 Calendar Featuring Morris the Cat Making Snide Remarks on How Technology

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2pts0
rsos.royalsocietypublishing.org 9y ago

The natural selection of bad science (2016)

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1pts0
xkcd.com 10y ago

Backslashes (xkcd)

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4pts1
www.gov.uk 10y ago

Password guidance by UK government [pdf]

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1pts0
www.nytimes.com 10y ago

Will You Ever Be Able to Upload Your Brain?

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2pts0
nextshark.com 11y ago

Elon Musk once lived on 1$ a day (hotdogs and oranges)

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1pts0
musicforcats.com 11y ago

Three different styles of music for cats

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1pts0
studyforrest.org 12y ago

Machine learning challenge for high-resolution ultra-highfield fMRI

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1pts0
stat.wharton.upenn.edu 12y ago

Multivariate Analysis, Dimensionality Reduction, and Spectral Methods (2010)

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2pts0
thenextweb.com 12y ago

Free 1TB cloud storage from Baidu and Qihoo

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carlsbad.princeton.edu 13y ago

Chaotic flow art

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www.eecs.berkeley.edu 13y ago

On Fair Comparison between CPU and GPU

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1pts0

51 papers out of 4841 accepted papers is 1%. If these were the only papers, then I would say the review system actually doing pretty well. Considering how noisy the review processes are, I don't see this as a big problem on its own.

We can't stop people (or agents) from submitting low quality papers in the current system. We can improve the review quality, but at a human cost.

Foundation models can be seen as approximate amortized posterior inference machines where the posterior is conditioning on the pre-training data. However, the uncertainty is usually ignored, and there may be ways to improve the state of the art if we were better Bayesians.

qwen coder with a simple funky prompt?!

`strcpy(agent.messages[0].content, "You are an AI assistant with Napoleon Dynamite's personality. Say things like 'Gosh!', 'Sweet!', 'Idiot!', and be awkwardly enthusiastic. For multi-step tasks, chain commands with && (e.g., 'echo content > file.py && python3 file.py'). Use execute_command for shell tasks. Answer questions in Napoleon's quirky style.");`

This is a vast simplification. Every neuron has a different preferred baseline firing rate. Not all neurons can fire at 500 Hz. In fact, most neurons in neocortex fire at a much lower firing rate. (most neurons are in the cerebellum!)

As for the internal sense of time, there isn't a consensus as to how it is kept, but for the cognitive time scale, it seems that it is a distributed time keeping mechanism rather than some sort of central unified clock mechanism.

A lot of work into this. I like the format, but I would prefer to read it as a printed book. :)

This is such a fun discovery. Inuitively there are three factors at play: 1. quantization 2. numerical errors accumulating 3. non-invertible transformations