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Sebastian Lehrer
@sebastianlehrer
Why the world needs a Machine Learning Compute Protocol (i.e., @gensyn) 🧵
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Sebastian Lehrer
@sebastianlehrer
Machine Learning is an inevitable tech, essentially because of how effective it is in multiple areas. The internet as we know it today will broadly be replaced by machine learning models.
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Sebastian Lehrer
@sebastianlehrer
In the future, apps and websites will replace imperative code execution with probabilistic ML models, and we will get to a point where we will have intelligent agents acting on our behalf. This will obviously significantly increase the demand for compute power.
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Sebastian Lehrer
@sebastianlehrer
So, why do we want to decentralize this space? What do we get out of this? 3 things - (i) lower prices, (ii) increased scale, (iii) auditability.
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Sebastian Lehrer
@sebastianlehrer
(i) Lower prices – If we create an open market for ML compute (i.e., enable anyone to provide CPU/GPUs for the training/inference of these models), the increase in supply will lower costs and solve the huge logistics burden we currently face.
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Sebastian Lehrer
@sebastianlehrer
(ii) Increased scale – You essentially remove the scaling limit. If we can only run training/inference operations on data centers, we face huge constraints in terms of the compute power available.
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Sebastian Lehrer
@sebastianlehrer
That radically changes the sort of ML models we can create. Your compute power is no longer limited to Google data centers but potentially includes every phone and compute-having device.
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Sebastian Lehrer
@sebastianlehrer
(iii) Auditability – Open sourcing ML models makes it much easier to understand why someone is building something and what they are trying to achieve with a specific model.
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