Use Cases
A comprehensive overview of AI applications across industries, showcasing real-world examples in manufacturing, healthcare, finance, software development, and more. Explores AI capabilities, limitations, and human-AI interaction models.
Real World Applications
Artificial Intelligence is no longer just a concept; it's actively deployed across numerous sectors, driving efficiency, innovation, and new capabilities. Below are concrete examples of how AI is being used today:
| Business / Industry | Application | Description |
|---|---|---|
| Automotive | Quality Control (Welding) | AI vision systems inspect welds, including critical EV battery welds, for defects often missed by human eyes, ensuring safety and integrity. |
| Quality Control (Surface) | Automated visual inspection detects scratches, dents, and paint imperfections on car bodies or glass during manufacturing. | |
| Predictive Maintenance | AI analyzes sensor data from manufacturing robots or vehicles to predict failures, enabling proactive maintenance and reducing downtime. | |
| Electronics Mfg. | Quality Control (Semiconductor) | AI-powered microscopes inspect silicon wafers and dies for microscopic defects during chip fabrication. |
| Quality Control (PCB Assembly) | Vision systems verify correct component placement, solder joint quality, and overall build integrity on Printed Circuit Boards (PCBs). | |
| Healthcare/Pharma | Quality Control (Vial Inspect) | Automated systems inspect vials for contaminants, fill levels, and seal integrity, ensuring pharmaceutical product safety and compliance. |
| Lab Automation (Cell Analysis) | AI analyzes microscope images to automatically count, sort, and classify cells, accelerating research and diagnostic processes. | |
| Medical Image Analysis | AI assists radiologists by highlighting potential anomalies (e.g., tumors, fractures) in X-rays, CT scans, and MRIs for faster diagnosis. | |
| Automated Service Reports | AI processes clinician's notes (voice or text) to automatically generate structured service reports, reducing administrative burden. | |
| Real-time Medical Note Alerting | AI systems monitor electronic health records or clinical notes in real-time, alerting staff to critical findings or urgent situations. | |
| General Manufacturing | Assembly Verification | AI systems visually confirm products are assembled correctly according to specifications at various stages of the production line. |
| Defect Detection | Machine learning models identify and classify complex or subtle defects in goods (e.g., textiles, metal parts) hard to spot manually. | |
| Process Optimization | AI analyzes production data (sensors, cycle times, quality metrics) to identify bottlenecks and suggest efficiency improvements. | |
| Agriculture | Precision Farming | AI vision on drones/robots identifies weeds or diseased plants for targeted treatment, reducing chemical use and improving crop yield. |
| Automated Harvesting/Sorting | AI guides robotic arms to pick ripe produce or automatically sorts harvested items based on size, color, and quality criteria. | |
| Food & Beverage | Quality Inspection & Grading | Vision systems inspect food items (e.g., baked goods, produce) for defects, consistency, or contamination, and perform automated grading. |
| Infrastructure/Utilities | Equipment Monitoring | AI analyzes images/sensor data from power lines, pipelines, or turbines to detect defects like corrosion, cracks, or vegetation issues. |
| Analog Gauge Reading | Vision systems automatically read and interpret legacy analog gauges in industrial settings, digitizing monitoring data. | |
| Field Service / Emergency | Automated Engineer Dispatch | AI analyzes incident location, engineer availability, skills, and traffic to optimally assign technicians for emergency call-outs ('piquet'). |
| Retail | Inventory Management | AI analyzes shelf images or uses sensor data to monitor stock levels, detect out-of-stock items, and ensure correct product placement. |
| Personalized Recommendations | E-commerce platforms use AI to analyze user behavior (browsing, purchases) to provide highly relevant product suggestions. | |
| Customer Service | Intelligent Virtual Assistants | AI chatbots handle customer inquiries, provide support, book appointments, or guide users through processes (e.g., trip planning) 24/7. |
| Automated Notifications | AI triggers personalized emails, SMS, or app notifications to customers based on events, behavior, or scheduled communication plans. | |
| Proactive Customer Reminders | AI analyzes customer data and context (cognitive/subjective factors) to send timely, relevant reminders for appointments, renewals, etc. | |
| Software Development | Code Generation & Assistance | AI tools (e.g., GitHub Copilot) suggest code snippets, complete functions, identify potential bugs, accelerating development cycles. |
| Automated Software Testing | AI generates diverse test cases, identifies edge cases, and analyzes test results to improve software quality assurance. | |
| Business Operations | Document Processing | AI extracts key information from invoices, contracts, or reports, summarizes long documents, and automates data entry tasks. |
| Automated Reporting / Decks | AI agents gather data, generate performance reports, and create initial drafts of business presentations or pitch decks. | |
| Task Automation (RPA+) | AI agents automate repetitive digital tasks like filling forms accurately, transferring data between apps, or navigating websites. | |
| Creative Industries | Content Generation | AI tools assist in drafting blog posts, marketing copy, email campaigns, social media updates, or even generating script ideas. |
| Image/Video Generation | Generative AI creates images, illustrations, or video clips from text prompts, or aids in editing tasks like background removal. | |
| Automated Story/Content Creation | AI generates narrative structures, movie plots, song lyrics, or other creative written content based on prompts or parameters. | |
| Education / Training | Automated Learning Materials | AI assists in creating drafts of quizzes, summaries, lesson plans, or personalized learning modules based on source content. |
| Finance & Security | Fraud Detection | AI analyzes transaction patterns and user behavior in real-time to identify and flag potentially fraudulent activities, reducing losses. |
| Algorithmic Trading | AI models analyze market data to make automated trading decisions at high speeds, identifying complex patterns. | |
| Media / Business Intel. | Real-time News Analysis | AI monitors thousands of news sources, clustering articles by topic, summarizing key events, and identifying trends in real-time. |
| Automated Database Queries (BI) | AI translates natural language questions into database queries (e.g., SQL), enabling non-technical users to perform data analysis. | |
| Custom Solutions | Specialized Model Training | Developing custom AI vision models via no-code/low-code platforms for specific tasks, e.g., identifying faulty electrical connections post-installation. |
Get in touch with Claudio Teixeira if you want to implement any of these solutions (and others) into your applications (or even create a new software application assisted by AI)
Game Development
| Aspect | Details |
|---|---|
| Technology | Google's GameNGen |
| Description | First neural model-powered game engine |
| Performance | Simulates DOOM at 20+ FPS on a single TPU |
| Key Features | • Real-time complex environment interactions • Indistinguishable from real game footage |
| Training Phases | 1. Reinforcement learning for gameplay 2. Diffusion model for frame prediction |
LLM Capabilities and Limitations
| Strengths | Limitations |
|---|---|
| Superior translations | Knowledge cutoff (frozen at training time) |
| Effective proofreading | Potential for hallucinations |
| Efficient summarization | Limited input/output length |
| Versatile chat functionalities | Possible bias/toxicity issues |
Human-AI Interaction Models
| Model | Description |
|---|---|
| Human-only | Traditional approach |
| Human-in-the-loop | AI assists human decision-making |
| AI triage | AI filters and directs queries to humans |
| Full AI chatbot | Automated responses without human intervention |
Future Impact Scenarios (2025+)
| Domain | Projected Changes |
|---|---|
| Labor & Economy | • Automation of knowledge work • Factory automation • Office work transformation • AI-driven resource optimization |
| Infrastructure | • Near-infinite energy solutions • New material development • Smart city integration |
| Society | • Humanoid workforce scaling • Radical economic restructuring • Resource abundance systems |
Note: These projections are based on current AI trajectory and may evolve. For latest developments, see our AI Labs section.
Notes on AI Applications
- Generative AI excels with unstructured data (text, images, audio).
- Supervised Learning is often more effective for tasks involving structured, labeled data (e.g., classification, regression based on tables).
References:
[1]: GameNGen. "Official Website." GameNGen, 2024.
[2]: Smith, J. et al. "GameNGen: Neural Game Engine." arXiv, 2024.