For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/07/intels-approach-to-operationalizing-ai-in-the-manufacturing-sector-a-presentation-from-intel/
Tara Thimmanaik, AI Systems and Solutions Architect at Intel, presents the “Intel’s Approach to Operationalizing AI in the Manufacturing Sector,” tutorial at the May 2024 Embedded Vision Summit.
AI at the edge is powering a revolution in industrial IoT, from real-time processing and analytics that drive greater efficiency and learning to predictive maintenance. Intel is focused on developing tools and assets to help domain experts operationalize AI-based solutions in their fields of expertise.
In this talk, Thimmanaik explains how Intel’s software platforms simplify labor-intensive data upload, labeling, training, model optimization and retraining tasks. She shows how domain experts can quickly build vision models for a wide range of processes—detecting defective parts on a production line, reducing downtime on the factory floor, automating inventory management and other digitization and automation projects. And she introduces Intel-provided edge computing assets that empower faster localized insights and decisions, improving labor productivity through easy-to-use AI tools that democratize AI.
1 of 21
More Related Content
“Intel’s Approach to Operationalizing AI in the Manufacturing Sector,” a Presentation from Intel
3. The Time for Edge AI is NOW!
Easy-to-use tools are democratizing AI
AI is improving labor productivity
Edge computing empowers faster
localized insights and decisions
AI solutions are more accessible and
less costly than ever before
93%
of industrial manufacturing
business leaders wish their
company would more
aggressively adopt AI
technology2
1 Despite productivity gains, manufacturers still struggle to find talent. HRDive, 2023. 2 Source: “Industrial Manufacturing: Bullish on AI adoption. KPMG, 2021.
3
4. Industrial Use Cases for Edge Inference (Analytics)
People Machine Material Process Environment
Worker behavior
Situational
monitoring
Predictive
maintenance
Robotics pick-and-
place
Predictive analytics
Product defect
detection
Raw material
appearance
inspection
Asset management
Factory operation
optimization
Optimization of
raw material
utilization
Temperature
optimization
Humidity
optimization
Worker safety
Visual data gathered at the Edge drives improved operations
Use case can benefit from video data. 1. Notes from the AI frontier insights from hundreds of use cases, McKinsey Global Institute, 2018
4
5. What are YOUR barriers to adopting AI?
78% of Edge AI use cases do not reach deployment
Difficulty gathering useful data
Mistrust of “unexplainable AI“
Lack of AI expertise
High implementation costs
Available solutions are too
complicated, or too limited
Only
10%
Companies say they are
generating significant
benefits from AI
1. 6 ways to help the manufacturing sector embrace AI. World Economic Forum, 2023
5
11. Through an unmatched partner ecosystem, Intel’s new commercial software platform enables enterprises to build,
deploy, run, and manage scalable edge and AI solutions on standard hardware with cloud-like simplicity.
Introducing Intel® TiberTM Edge Platform
Manage
Deploy Run
Build
Secure
Open & Modular | Edge & AI Optimized | Rich App Orchestration
Brownfield and
heterogenous component
support
Speed, accuracy, and power
efficiency on right-sized
components
Remote application and AI
deployment and
management at scale
11
12. Build models with the Intel® G eti™ platform Deploy with Intel Premises AI
Build and Deploy your AI Solution With Intel
12
Build models with the Intel® Geti™ platform Deploy with Intel Premises AI
13. Achieve a working model with
fewer data. Active learning
selects the most useful data to
label for training
Automatic optimizations are
available
3
Easily label data with smart
annotation features
2
Start model development with
as little as 20 images or a
video
1
Adjust your model by
retraining with new data and
exporting a new model
5
4
Export model in native framework or as an optimized model
for OpenVlNO™ toolkit
Accelerate Model
Development
One Platform for the
Complete Model
Development Cycle
Intel® Geti™ Platform
13
15. Intel® Edge Insights System
An all-encompassing solution for management, operation and easy deployment of AI at the Edge.
Intel® Edge Insights System is part of Intel® TiberTM Edge Platform
User Interface
designed for developers
and factory experts
Intel®
Edge
Insights
System
Validated cameras
of your
choice
Validated Industrial PCs
of your choice
Maintenance
and Support
options
Value-added Services
Including installation,
engineering and
training services
Intel AI
Software
Offerings
including tools,
libraries and
sample models to
get a customer
started.
Integration Tools
easily connect to
existing systems
Easy-to-deploy,
comprehensive solution
Industrial focused
Supporting both time series and
video analytics
Flexible pricing
15
17. Data Collection and Annotation
Enabled
Operator-Friendly
User Interface
Validated IPCs and Cameras
Available
1. Intel® Edge Insights System is expected to be officially launched by Q3 2024.
2. Intel® Edge Insights System is compatible with Intel® Geti™ platform for model
creation and ingestion.
3. Intel® Edge Insights System is part of Intel® Tiber™Edge Platform.
Value-added services
Installation, Training, and Engineering services
Validated Industrial PC s Validated C ameras
User Interface (End C ustomer)
Software Offerings
Maintenance and Support Options
User Interface (Developer)
Integrated
Standard and Enhanced SKUs
Compatible with
Intel® Edge Insights System A Comprehensive AI Edge Inferencing
Platform – Help factories put AI to work
Intel® Edge Insights System (Part of Intel’s Edge Platform)
17
18. Operations
Live Data Input
Video
Time
series
Audio
Data
Data Ingestion from
Operations + Database
Training Data Streams
Model Development
Data
Ingress
Intel® Edge Insights System (Inference)
Intel® Geti™ (Training)
Support through the entire ML Ops workflow
Outcomes/
Report
Maintenance
and Support
Integration Tools
easily connect to
existing systems
Deployed Model Model Monitoring
Integration Tools
designed for factory
experts, not data
scientists
User Interface
designed for factory
operator to make
informed decisions
Validated Cameras
of your choice
Model Training & Tuning
Model Validation
18
19. Conclusion
19
• There is a shift in User Persona of target audience for the Industrial AI solutions
• From Developer, Architect, Data Scientist to SME, Operator, IT/OT Managers
• Factory wants to be independent.
• Less reliance on IT, data scientists, and Systems Integrator.
• The key buyer or Persona is the Business Unit lead in an organization
• With recommendations from the IT, AI team and other technical buyers (security,
ML/Ops, etc.)
• Factory Lead Engineer is a key go/no-go decision maker
• Differentiating factors like low – code functionality of Intel® Geti™ and Intel® Edge Insights
System along with multi-modal analytics, ingress/egress extensibility, ML/Ops flow, and
ability to connect to controls and factory analytics will enable adoption and deployment of
AI solutions in factories.
20. Sign up for receiving the
latest updates and news
from the Intel’s Edge
Platform
CTA Intel® Tiber™ Edge Platform Product Links
Intel® Tiber™ Edge Platform
Product Site
Related Products
Intel® Distribution of OpenVINO™ Toolkit
The Intel® Geti™ Platform - Intel's Computer Vision AI Platform
Development Tools (intel.com)
Intel® Edge Insights System
Intel® Tiber™ Edge Platform IDZ
Website
Resources
20