Edge 411: Learn About Microsoft's Impressive 4 New AI Compilers
Was this email forwarded to you? Sign up here Edge 411: Learn About Microsoft's Impressive 4 New AI CompilersParallelism, computation, memory, hardware acceleration and control flow are some of the capabilities addressed by the new compilers.
Compilers are seeing a renaissance in the era of generative AI. In the context of AI, a compiler is responsible for translating a neural network architecture into executable code in a specific hardware topology. Those two areas: model and hardware architectures, have been an explosion in innovation, regularly making AI compilers obsolete. The challenges in AI compilation are many, from hardware acceleration to computation and memory efficiency. Microsoft Research has been at the forefront of the AI compiler research, and recently, they unveiled a quartet of cutting-edge AI compilers, each tailored to address specific challenges in the realm of deep neural networks (DNNs). The list includes the following compilers: · Rammer: For parallelism · Roller: For computation · Welder: For memory · Grinder: For control flow and hardware acceleration Let’s dive into each one... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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Edge 411: Autonomous Agents with Episodic Memory
Tuesday, July 9, 2024
Capturing memories of important events in the lifecycle of an agent. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Apple Goes Small and Super Multimodal
Sunday, July 7, 2024
Plus a lot of new models being released and quite an active week for AI VCs. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 410: Learn About Virtual Token Counter: A Novel Method that Address One of the Major Challenges LLM Serving
Thursday, July 4, 2024
Created by UC Berkeley and Stanford University, VTC introduced a fairness in LLM serving scheduling ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
Edge 409: Augmenting Autonomous Agents with Long-Term Memory
Tuesday, July 2, 2024
Making agents remember beyond the context window. ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
📝 Guest Post: Yandex develops and open-sources YaFSDP — a tool for faster LLM training and optimized GPU consumpt…
Monday, July 1, 2024
A few weeks ago, Yandex open-sourced the YaFSDP method — a new tool that is designed to dramatically speed up the training of large language models. In this article, Mikhail Khrushchev, the leader of
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