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00:00:00 Teaser
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Classroom Contents
LLMs for Developers - Model Selection, Hallucinations, Agents, and AGI
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- 1 00:00:00 Teaser
- 2 00:00:37 Intro
- 3 00:01:08 From PhD and academia to data science at JetBrains
- 4 00:02:31 Early NLP versus modern LLMs
- 5 00:04:46 From LSTMs to Transformers BERT and GPT
- 6 00:08:49 The DeepSeek surprise and model scaling limits
- 7 00:12:25 Benchmarks, assessments, and confusion for end users
- 8 00:17:18 Choosing models in practice
- 9 00:21:10 “Thinking” models and reasoning limits
- 10 00:23:48 Do you really need the newest model?
- 11 00:25:58 Hallucinations and how to handle them
- 12 00:28:30 Agents and RAG: real-world applications
- 13 00:32:55 Vibe coding: hype versus reality
- 14 00:37:46 What are AI agents? Tools, MCP, and multi-agent apps
- 15 00:43:01 Self-hosting versus proprietary models
- 16 00:45:20 Fine-tuning explained and Hugging Face
- 17 00:50:17 Building reliable AI apps tests, A/B, traces
- 18 00:55:33 Privacy, company data, and self-hosting concerns
- 19 00:58:37 Ethical issues: data sourcing and labor
- 20 01:04:23 Environmental costs and the push for smaller models
- 21 01:06:26 Juniors, skills, and the future of coding with AI
- 22 01:09:15 Learning fundamentals in the age of LLMs
- 23 01:13:24 AGI: definitions, timelines, and Jodie’s twenty euro bet
- 24 01:20:03 Rapid-fire questions: slang, food, and culture
- 25 01:25:47 Giveaway
- 26 01:26:26 Outro
