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Data-driven economics impact that adds value. From banks to business; government to gaming; tech to trade; food to fashion; utilities to universities; real estate to racing; motion pictures to the metaverse.
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Machine Learning X Doing
5.6K posts
Machine Learning X Doing
@mlxdoing
The architecture of AGI. Solving the human condition.
Toronto, ON 👉 Katılım Haziran 2020
99 Takip Edilen1.2K Takipçiler
Beyond the binary of raw compute and mindless scale lies a third path: the causal equilibrium.
Our latest brief, "Causing Leadership," outlines the synthesis of frontier discovery and beautiful, scaled implementation.
The future awaits. machinelearningxdoing.com/research/causi…
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Machine Learning X Doing retweetledi
Yes. Computer science has the best research culture in my experience.
At this point, its impact speaks for itself.
Other disciplines like economics and the political economy of development could learn a lot to reach their ultimate potential.
How did they pull it off? Thread brought to you from .@mlxdoing .@DevEconX.
Megan Stevenson@MeganTStevenson
@cblatts It's interesting how research cultures have found different equilibriums. Have you heard of a field with a good balance of ambition, flexibility in methods, and friendliness? it seems like there's something about social cultures that makes this triad difficult to achieve
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Correlation is surface-level. Causality is the truth. We don’t just map the rock; we find the mechanism to break out of it.
We are pioneering Causal AI Inference to the world's most complex verticals.
The future of AI isn't more data: it's better logic.🌱📷 #MLXD #Causality
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Machine Learning X Doing retweetledi
More economists just need to get more technical so they can work in an AI research lab someday if they want to. .@mlxdoing.
John Friedman@johngfriedman
Economics vs CS job market discourse in a nutshell. Economics: 'if you're really good, after finishing your phd, you might get a chance to work with [distinguished professor] as a postdoc' CS: 'if you're really good, you might get hired by a lab for $2.5mn/year.'
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Maybe even earlier.
Motley Fool Stock Advisor@TMFStockAdvisor
Google CEO: Quantum is in the same place AI was in 2015
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Machine Learning X Doing retweetledi
This absolutely smells (and sounds!) like a critical AI research use case. cc .@mlxdoing.
60 Minutes@60Minutes
Creating a fragrance can take thousands of attempts. “Sometimes I need 20,000,” says master perfumer, or “nose”, Honorine Blanc, who creates scents for brands including Valentino and Gucci. cbsn.ws/3OJlu6R
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Machine Learning X Doing retweetledi
The real gap is teaching. At .@mlxdoing, we believe that the limitation isn't some hard, philosophical barrier in the nature of understanding itself, but a practical one in how we transfer or instill it.
kache@yacineMTB
you can outsource your thinking but you cannot outsource your understanding
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Machine Learning X Doing retweetledi
Machine Learning X Doing retweetledi
Perhaps, but not necessarily: it could just a much deeper transformer. More layers (or effective depth via other tricks) lets the model do more sequential reasoning inside each forward pass. (The paper's theorem still holds in spirit: extra depth helps graph traversal more than extra CoT length in the output.)
It could be any number of things, certainly.
Chris Hayduk@ChrisHayduk
I strongly suspect that Claude Mythos is a looped language model, as described in the paper "Scaling Latent Reasoning via Looped Language Models" from ByteDance The authors of that paper called out graph search as one of the areas where looping provides a huge theoretical advantage over standard RLVR. And look at where Mythos blows out its competitors the most
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Execution is the only differentiator that matters. We’re moving beyond the lab and into the real world—witness The Doing.
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Ready. Set. Done.
In consulting, the "Set" phase used to take months.
At .@mlxdoing we make the "Go" instantaneous.
We're the AI research and infrastructure that allows leading firms to outpace the market.
Precision at scale. Execution at speed.
We’re retooling the industry.
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Machine Learning X Doing retweetledi
Well done is better than well said.
— Benjamin Franklin.
Machine Learning X Doing@mlxdoing
Execution is the only differentiator that matters. We’re moving beyond the lab and into the real world—witness The Doing.
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Learn how AI is changing human behavior: thedecisionlab.com/insights/socie…
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