| Table of Contents |
|---|
Key Points
...
- GIGO2 - Garbage in Good data out engine - use calibrations to generate quality data rules from bad data on a data farm
- ASA - Auto Support Agent - generated automatic responses for defect ticket resolutions - moved to defect queue, provided how to example doc, provided a known fix link, queued to manager
- QWF - Quick WebFacing Factory - generated advanced web pages based on data types and generation policies and the vanilla WebFacing code source
- CQA - Code Quality Analyst - reviewed JEE code to generate an analsysi report on the usage and quality of design patterns in an enterprise JEE insurance policy suite
- FVA - Fix Verification Agent - verified the target environment met the criteria to deploy a fix
- AMM - Automated Market Maker Agent - based on history and trading policy goals, the AAM agent recommended prices to sell vehicles for a given marging and turnaround - user decided to use or not
MIT Study for Enterprise Gen AI Use Cases - 2024
ebook_mit-cio-generative-ai-report.pdf link
...
Unified and consistent governance are the rails on which AI can speed forward. Generative AI brings commercial and societal risks, including protecting commercially sensitive IP, copyright infringement, unreliable or unexplainable results, and toxic content. To innovate quickly without breaking things or getting ahead of regulatory changes, diligent CIOs must address the unique governance challenges of generative AI, investing in technology, processes, and institutional structures.
How SGS provides STEAR governance capabilities for AI >>
...
2022 Adoption rates by industry
...
Which software has better performance compliance ? commercial or enterprise open-source software ?
How SGS provides STEAR governance capabilities for AI >>
Responsible AI and AI Governance#SGS-delivers-STEAR-governance-capabilties---Jim-Mason
AlphaCodium-ai-generate-activity-test-2024-gpt4
...
ai-apps-use-cases-msft-azure-ebook-2024.pdf. link
AI apps employ machine learning to continually learn and adapt, using advanced models powered by cloud computing to optimize their results over time. The insights they provide are much more informative and actionable than their non-AI counterparts.
Compare Traditional to AI Apps
| Traditional Apps | Intelligent Apps | Outcomes | |
| Learning and automation | Depends on the code written by the programmer to perform a specific task | Programmed to learn to perform the task by using data, algorithms, computation, and method | Intelligent AI apps can adapt to changing situations and user preferences, while traditional apps are limited by predefined rules and logic |
| Responsiveness | Can only respond to user inputs or requests | Can anticipate user needs and offer suggestions or solutions | Intelligent AI apps are proactive, making them more personalized and engaging than reactive traditional apps |
| Data Capabilities | Designed only to handle certain types of data or inputs | Designed to handle various types of data or inputs and even generate new data or output | AI apps are flexible and creative, allowing users to engage beyond traditional app limitations in ways they didn’t expect |
| Implementation | Typically built on a monolithic architecture and deployed on-premises | Built on the cloud using a microservices architecture | AI apps have enhanced scalability that lets them handle unlimited traffic and data |
Consulting Use Case
To maximize the collective knowledge of its consultants, Arthur D. Little created an internal solution that draws on text analytics and other AI enrichment capabilities in Azure AI services to improve indexing and deliver consolidated data insights. Using this solution, consultants have access to summaries of documents with the abstractive summarization feature in Azure AI Language. Unlike extractive summarization—which only extracts sentences with relevant information—abstractive summarization generates concise and coherent summaries, saving the consultants from scanning long documents for information.
1. Enhanced summarization capabilities speed up consultant workflows
2. Improved security and confidentiality
3. Rapid innovation for products and services
Synthesized Voice for Customer Service Use Case
TIM pioneers synthesized voice service to increase customer satisfaction
Azure AI Services
Azure provides a wide range of tools and services that support AI development:
...