Favorite team:Arkansas 
Location:https://youtu.be/torc9P4-k5A
Biography:Sordid Details
Interests:under water basket weaving and tiddlywinks
Occupation:deck hand on tFlagship
Number of Posts:65115
Registered on:11/28/2011
Online Status:
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Turns out there are no new ideas, we’re all parroting unoriginal thoughts
Wondering why ideas are discussed is certainly a question
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Isreal is the greatest threat to everyone

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So, basically, 500 million Europeans expect 300 million Americans to protect them from 120 million Russians who can’t even defeat 40 million Ukrainians while those 500 million Europeans don’t even realize they are being conquered by 2 billion Muslims who claim they are being persecuted by 8 million Israelis. Is that about right?

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today, we introduce a little mischief to the world.

for four years, we’ve been brewing real brain cells on electrodes to understand how they compute. now, we’ve turned those discoveries into a video model anyone can use.

from 0.5¢ a second, mischief 1 is at least 5x faster than its base and the cheapest image-to-video model on @fal and @OpenRouter. soon to be on @awscloud marketplace.

it’s not a delusion anymore. biocompute is real, commercial and this is just the beginning.

What could possibly go wrong

LINK
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The brain is the most efficient computer ever known. We built a discovery platform to study how living neurons process information and turn that knowledge into faster and more efficient AI models.
We’re starting with video generation. Our models run on existing chips. The neurons stay in our lab.

We identify a specific problem in an AI model, such as slow generation or high computing costs, and design an experiment to explore a better way to compute.
A chip beneath a culture of living neurons lets us send electrical signals and record how the network responds.

We convert information from video into patterns of electrical stimulation. By changing those patterns, we can test how living neurons respond to different inputs.

We measure how electrical activity moves through the network and changes over time. These recordings let us study how the neurons process information we send.

We compare the inputs with responses, looking for patterns in timing and how neurons interact. Those patterns can suggest new ways for an AI model to process information more efficiently.

Our researchers turn promising findings into algorithms and test them in AI models. We compare each modified model with the original to see whether it works better, runs faster or uses less compute.
The neurons stay in our lab. What leaves is cheaper, faster, and better AI.
Would’ve been better off taking a chance on some alternate uniform

Of course that probably would’ve been criticized almost as much, same as if we went with a normal look.