Will ChatGPT Take Over My Job?
summary
Generative models get integrated into Elastic so an Azure OpenAI instance ingests stack traces, calls Elasticsearch and Kibana APIs, and auto-generates visualizations, incidents and alerts. A June 7 2022 log spike is traced to pgbench activity, correlated to the checkout service and a measurable revenue dip. Practical limits: Source Labs finds ~61% of engineers paste model code and ~25% skip testing, and the model still hallucinates or returns stale facts.
AI-written summary · about
chapters (10)
- 0:00Introduction and expectations
- 1:05Code generation and trust in AI
- 3:12Will AI take over jobs?
- 4:59Debugging with AI assistance
- 7:28Analyzing log spikes with AI
- 11:25AI-powered data visualization
- 17:14Context and conversation storage
- 19:40AI Ops and actionable insights
- 22:54AI’s role in modern workflows
- 23:36Q&A and closing remarks
related talks
01h 16mChatGPT - and How we Can Benefit from it
27mChatGPT Ignites
44mExploring ChatGPT for Improved Observability
39mHow ChatGPT helps to boost your development efficiency
25mChatGPT Unleashed: From Code Wizards To Silly Shenanigans!
07mHow About Now? Can ChatGPT Do My Job Yet?
23mExploring ChatGPT for Improved Observability
25mCan ChatGPT build a Data Platform faster than a developer?
