Learn how to hire your AI team, ranging from role types & expectations, matching positions to project requirements, and interview structures.
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David Bressler, PhD
Building out an ML product can feel like a race to experiment, train models, and iterate quickly. Often, startups allocate GPUs and spin up cloud infrastructure without much thought to optimization—until sky-high bills spark a scramble for cost savings. Below are ten practical ways to keep your machine learning systems lean, efficient, and scalable from the start.
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David Bressler, PhD
Perhaps the most surprising aspect of the evolution of the Transformer architecture for language modeling is how consistent it has remained over the past near-decade
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Erik Gafni
This document describes general guidelines for how to hire your AI team, ranging from role types & expectations, matching positions to project requirements, and interview structures.
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Erik Gafni
The paper introduces DeepSeek-R1, a series of reasoning models, including DeepSeek-R1-Zero and DeepSeek-R1.
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