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#software2.0#neuralnetworks#andrejkarpathy
169K subscribers • 4 videos on Hallway
Intermediate. Assumes working knowledge.
72K views8 years ago1 recommendation
AI and machine learningSoftware designNeural networks and deep learningTraining and serving models
Andrej Karpathy explains the transition from human-written code to neural network optimization and the tooling required for this new paradigm.
A lot of our code is in the process of being transitioned from Software 1.0 (code written by humans) to Software 2.0 (code written by an optimization, commonly in the form of neural network training). In the new paradigm, much of the attention of a developer shifts from designing an explicit algorithm to curating large, varied, and clean datasets, which indirectly influence the code. I will provide a number of examples of this ongoing transition, cover the advantages and challenges of the new stack, and outline multiple opportunities for new tooling. To learn more: databricks.com/product/getting-started-guide About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: databricks.com/product/unified-data-analytics-platform Connect with us: Website: databricks.com Facebook: facebook.com/databricksinc Twitter: twitter.com/databricks LinkedIn: linkedin.com/company/databricks Instagram: instagram.com/databricksinc/ Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. databricks.com/databricks-named-leader-by-gartnerWhat people say. Recommended as a foundational talk on the shift toward data-driven software development and machine learning workflows.
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