Live briefing
Everything about Edge inference
Execution of machine learning models on edge devices
Edge inference is the process of running machine learning or deep learning models on local devices such as smartphones, IoT devices, embedded systems, and edge servers instead of centralized cloud computing infrastructure. A key feature of edge computing is edge inference, which allows for real-time data processing, low latency, and improved privacy by reducing the amount of data sent to remote servers. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Edge inferenceA 5-minute orientation
- Skim a recent paper: Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A ReviewInfluential work since 2022
- Pick up a classic book: Il pendolo di FoucaultThe most-reprinted book on the subject
- Read the landmark paper: Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge ComputingCited 899 times
- Go sideways: Edge computingA closely related topic
- Go sideways: Hardware for artificial intelligenceA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
No outline available.
🏆 Landmark papers (most cited)
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
Scaling for edge inference of deep neural networks
EdgeShard: Efficient LLM Inference via Collaborative Edge Computing
Task-Oriented Communication for Multidevice Cooperative Edge Inference
Communication-Computation Trade-off in Resource-Constrained Edge Inference
Orbital Edge Computing: Machine Inference in Space
Breaking the Edge: Enabling Efficient Neural Network Inference on Integrated Edge Devices
Collaborative Semantic Communication for Edge Inference
🆕 Influential since 2022
Efficient Acceleration of Deep Learning Inference on Resource-Constrained Edge Devices: A Review
Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck Approach
A Survey on Collaborative DNN Inference for Edge Intelligence
Multiuser Co-Inference With Batch Processing Capable Edge Server
Ultra-Low-Latency Edge Inference for Distributed Sensing
📚 Books worth reading
Il pendolo di FoucaultUmberto Eco · 1988
Bioinformatics Research and ApplicationsZhipeng Cai · 2013
Foundational Papers in Complexity ScienceDavid Krakauer · 2024
Campbell biologyLisa A. Urry, Michael L. Cain · 2015
Hierugia, or, The Holy Sacrifice of the MassDaniel Rock · 1833
SeeingJohn P. Frisby · 1979- 📕Crack-speed relations inferred from large single-edge notched specimens of A 533 B steelC. W. Schwartz · 1994
Real World HaskellBryan O'Sullivan, John Goerzen · 2008
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Edge computing Edge computing is a distributed computing model that brings computation and data storage closer to the sources of data. More broadly, it refers to any…
- Hardware for artificial intelligence Specialized computer hardware is often used to execute artificial intelligence (AI) programs faster, and with less energy, such as Lisp machines, neuromorphic…
- Fog computing Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation (edge…
- Industrial internet of things The industrial internet of things (IIoT) refers to interconnected sensors, instruments, and other devices networked together with computers' industrial…
- Eyes of Things Eyes of Things (EoT) is the name of a project funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement number…
- Artificial intelligence of things Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of things (IoT) infrastructure…
- Neural processing unit A neural processing unit (NPU), also known as an AI accelerator or deep learning processor, is a class of specialized hardware accelerator or computer…
- David Atienza David Atienza Alonso is a Spanish/Swiss scientist in the disciplines of computer and electrical engineering. His research focuses on hardware‐software…