Sublime
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AI Overlords
Shachaf Rodberg • 2 cards
Deep learning at the speed of light.
Luminal is a deep learning library that uses composable compilers to achieve high performance.
use luminal::prelude::*;
// Setup graph and tensors
let mut cx = Graph::new();
let a = cx.tensor().set([[1.0], [2.0], [3.0]]);
let b = cx.tensor().set([[1.0, 2.0, 3.0, 4.0]]);
// Do math...
let mut c = a.matmul(b).retrieve();
... See more
Luminal is a deep learning library that uses composable compilers to achieve high performance.
use luminal::prelude::*;
// Setup graph and tensors
let mut cx = Graph::new();
let a = cx.tensor().set([[1.0], [2.0], [3.0]]);
let b = cx.tensor().set([[1.0, 2.0, 3.0, 4.0]]);
// Do math...
let mut c = a.matmul(b).retrieve();
... See more
jafioti • GitHub - jafioti/luminal: Deep learning at the speed of light.
AI
Marvin Chang • 1 card
here are two basic approaches to creating AI datasets. The first one, which is typical of the case we have been studying, a pool of open works is purposefully chosen to ensure license compliance. The second approach creates the dataset by scraping the “raw internet” and relying on copyright exceptions. LAION , a dataset of 400 million image-text pa... See more
Alek Tarkowski • Filling the governance vacuum related to the use of information commons for AI training
how can you take the knowledge work that someone is doing and use AI to help them be dramatically more productive at doing that particular flavor of cognitive work? In our observation with developers, more than anything else, AI helps keep them in flow state longer than they otherwise would. Rather than hitting a blocker when you’re writing a chunk... See more
Sarah Wang • What Builders Talk About When They Talk About AI | Andreessen Horowitz
Capture all of your AI product data
Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback.
02
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05
Analyze model performance
Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases.
03
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05
Impr... See more
Get the full picture of your model's performance. Log inputs and outputs and seamlessly enrich them with metadata and user feedback.
02
/
05
Analyze model performance
Figure out how your model is really working, and where you can improve. Monitor for errors and discover underperforming cohorts and use cases.
03
/
05
Impr... See more
Gantry | Build AI your users trust
Setting up the necessary machine learning infrastructure to run these big models is another challenge. We need a dedicated model server for running model inference (using frameworks like Triton oder vLLM), powerful GPUs to run everything robustly, and configurability in our servers to make sure they're high throughput and low latency. Tuning the in... See more