World Congress 2023 • Aug 11, 2023

Trends, Challenges and Best Practices for AI at the Edge

Ekaterina Sirazitdinova

How do you deploy zero-latency AI on devices with strict compute and power limits? Learn to master quantization, pruning, and NVIDIA frameworks to conquer edge deployment.

Pause

Mute

Enter Fullscreen

#1 about 7 min

Defining edge AI and its widespread industry applications

Localized data processing enables independent automation and real-time computation across manufacturing, retail, and healthcare.

#2 about 4 min

Hardware constraints and core challenges in edge environments

Operating intelligent models on embedded hardware requires balancing limited compute and power capacities with strict low-latency requirements.

#3 about 2 min

Increasing model accuracy through synthetic data generation

Augmenting realistic scenarios with synthetic data solves expensive manual labeling and effectively covers anomalous edge cases.

#4 about 7 min

Optimizing edge model throughput to ensure real-time performance

Techniques like precision quantization, network pruning, and graph optimization reduce model footprint and accelerate execution on constrained hardware.

#5 about 5 min

Accelerating AI development with software and pretrained models

Utilizing managed toolkits and foundational templates simplifies custom model training, synthetic data generation, and complex multi-node orchestration.

#6 about 6 min

Deploying optimized models for high-throughput video analytics

Specialized deployment SDKs handle layer fusion, memory management, and concurrent sequence execution for complex multi-model pipelines.

#7 about 2 min

Exploring domain gaps and hardware requirements for deployment

Correcting for texturing differences between synthetic and real datasets ensures higher accuracy across various processing units.

Matching moments

2:18 min

The necessity of Edge AI and its driving constraints

Sasha Denisov

Sasha Denisov +1 · World Congress 2026 Europe

1:56 min

Optimizing AI processing capabilities for edge microcontrollers

Stephan Gillich

Stephan Gillich +3 · World Congress 2024

3:21 min

Reducing cloud dependency with on-device edge AI models

Precious Osaro

Precious Osaro · World Congress 2026 Europe

2:26 min

Cost and latency pressures pushing AI to the edge

Moe Sani

Moe Sani · World Congress 2026 Europe

1:09 min

Deploying algorithms and AI models to edge production

Irina Terekhova

Irina Terekhova · World Congress 2026 Europe

3:19 min

Technological shifts enabling practical edge AI deployment

Sasha Denisov

Sasha Denisov · World Congress 2026 Europe

More from World Congress 2023

The year 3000, a brief history of Web Development thumbnail

over 2 years ago

The year 3000, a brief history of Web Development

Lorenzo Pieri

Demografie nutzen um jedem Bewerber das passende Angebot zu machen! thumbnail

almost 3 years ago

Demografie nutzen um jedem Bewerber das passende Angebot zu machen!

Nathalie Gierth

Guided Memory Management: Rust's Ownership Model thumbnail

almost 3 years ago

Guided Memory Management: Rust's Ownership Model

Stefan Baumgartner

Passwordless future: WebAuthn and Passkeys in practice thumbnail

almost 3 years ago

Passwordless future: WebAuthn and Passkeys in practice

Clemens Hübner

External Secrets Operator: the secrets management toolbox for self-sufficient teams thumbnail

almost 3 years ago

External Secrets Operator: the secrets management toolbox for self-sufficient teams

Moritz Johner

Building Reliable Serverless Applications with AWS CDK and Testing thumbnail

almost 3 years ago

Building Reliable Serverless Applications with AWS CDK and Testing

Raphael Manke

Upcoming sessions on this topic

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 5

Edge AI: Running Agentic Intelligence Where Internet Can't Reach

Nitin Eusebius

AWS - Principal Solutions Architect

Nitin Eusebius

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 7

Designing High-Performance AI APIs: Lessons from Serving Millions of Real-Time Requests

Wayne Liu

Chief Growth Officer and Americas President of Perfect Corp.

Wayne Liu

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 1

Anatomy of an AI Request: Where Latency and Cost Are Really Born

Dan Fu

VP of Kernels at Together AI

Dan Fu

World Congress 2026 North America

September 25, 2026 · 15:30–16:00

Stage 7

Trust, But Verify: Continuous GPU Validation at Scale

Kyle Bell

VP of AI at TensorWave

Kyle Bell

World Congress 2026 North America

September 24, 2026 · 11:00–11:30

Tech Leaders Stage

Building AI for the Physical World

Alex Spinelli, Eystein Stenberg, Gerardo Pardo-Castellote, Joseph Nelson

Alex Spinelli

Eystein Stenberg

Gerardo Pardo-Castellote

Joseph Nelson

World Congress 2026 North America

September 24, 2026 · 14:10–14:40

Stage 6

Compute for your AI model: GPUs, LPUs, TPUs and beyond..

Kushaagra Goyal

Tech Lead at Rubrik, ex-CTO at Gan.AI, ex-Databricks

Kushaagra Goyal

Related videos

The Future of Computing: AI Technologies in the Exascale Era thumbnail

World Congress 2024 • about 2 years ago

The Future of Computing: AI Technologies in the Exascale Era

Stephan Gillich, Tomislav Tipurić, Christian Wiebus, Alan Southall

RTX AI PC: Developing local and edge AI applications thumbnail

World Congress 2026 Europe • 2 months ago

RTX AI PC: Developing local and edge AI applications

Joerg Krall

From Perception to Autonomy: Building Agentic Edge AI Robots with ROS 2 thumbnail

World Congress 2026 Europe • 2 months ago

From Perception to Autonomy: Building Agentic Edge AI Robots with ROS 2

Moe Sani

AI That Fits Your Business, Not the Other Way Around thumbnail

World Congress 2026 Europe • 2 months ago

AI That Fits Your Business, Not the Other Way Around

Anshul Jindal, Cansu Kavili Örnek

Future of Mobile AI. What On-Device Intelligence Means for App Developers thumbnail

World Congress 2026 Europe • 2 months ago

Future of Mobile AI. What On-Device Intelligence Means for App Developers

Sasha Denisov

Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based thumbnail

World Congress 2025 • about 1 year ago

Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based

Maxim Salnikov

Related articles

DC

Daniel Cranney

Stephan Gillich - Bringing AI Everywhere

In the ever-evolving world of technology, AI continues to be the frontier for innovation and transformation. Stephan Gillich, from the AI Center of Excellence at Intel, dove into the subject in a r...

almost 2 years ago

Stephan Gillich - Bringing AI Everywhere

BB

Benedikt Bischof

MLOps And AI Driven Development

Welcome to this issue of the WeAreDevelopers Dev Talk Recap series. This article recaps an interesting talk by Natalie Pistunovic who spoke about the development of AI and MLOps. What you will lear...

over 4 years ago

MLOps And AI Driven Development

BR

Benjamin Ruschin

Navigating the AI Shift

AI has had an undeniable impact on all kinds of aspects of life and work, from how we do everyday tasks, to how software is built, how companies operate, and even how work itself is defined. Despit...

12 months ago

A laptop interacting with AI

BB

Benedikt Bischof

MLOps – What’s the deal behind it?

Welcome to this issue of the WeAreDevelopers Live Talk series. This article recaps an interesting talk by Nico Axtmann who introduced us to MLOpsAbout the speaker:Nico Axtmann is a seasoned machine...

almost 4 years ago

MLOps – What’s the deal behind it?

From learning to earning

Jobs that call for the skills explored in this talk.

Principal Software Engineer, AI Compute Infrastructure

Seattle, WA, United States

Expert $262k Linux Grafana Pytorch

Principal Software Engineer, AI Inference Runtime

Seattle, WA, United States

Expert $262k Compilers Low Latency Concurrency

Principal Software Engineer, AI Inference Cloud

Seattle, WA, United States

Expert $262k Pytorch TensorRT Kubernetes

Software Developer - Physical & Edge AI Platforms

Seattle, WA, United States

$209k–282k U-Boot Visual Systems Cloud Services

Staff Software Engineer, AI Inference Runtime

Seattle, WA, United States

Expert $209k–282k Compilers Low Latency Concurrency

Staff Software Engineer, AI Inference Cloud

Seattle, WA, United States

Expert $209k–282k Pytorch TensorRT Kubernetes