A Google engineer has been indicted for allegedly stealing over 500 confidential files containing AI trade secrets while working for China-based companies seeking an edge in the AI technology race.
A tutorial series explores parallelism strategies for training large deep learning models, making it accessible to everyone regardless of the hardware you have available.
Value functions are a crucial component in deep reinforcement learning, and a new approach using categorical cross-entropy instead of regression can significantly improve performance and scalability in a variety of domains.
Backtracing is the task of retrieving the text segment that most likely caused a user query, and it can help improve content delivery and communication by identifying linguistic triggers that influence user queries.
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Timestamps:
00:34 Introduction
01:33 Google engineer indicted over allegedly stealing AI trade secrets for China
03:57 Training Models at Scale Tutorial
05:24 Autogenerating a Book Series From Three Years of iMessages
06:22 Fake sponsor
08:16 Design2Code: How Far Are We From Automating Front-End Engineering?
10:09 Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
11:43 Backtracing: Retrieving the Cause of the Query
13:27 Outro

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