Difference between revisions of "IT-AI-Base"
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=init= | =init= | ||
| − | * https://openclaw.ai/ | + | * OpenClaw (https://openclaw.ai/) |
| − | * https://ollama.com/ | + | * Ollama (https://ollama.com/) |
* Llama (https://www.llama.com/) | * Llama (https://www.llama.com/) | ||
* MiniMax (https://www.minimax.io/) | * MiniMax (https://www.minimax.io/) | ||
| + | * Gemma 4 (https://deepmind.google/models/gemma/gemma-4/) | ||
| + | * Aurora (https://www.arvoai.ca/) | ||
| + | * incident.io | ||
| + | |||
| + | =Buzz Words= | ||
| + | * LLM (Large Language Model) | ||
| + | * LLMOps | ||
| + | * Generative KI | ||
| + | * RAG-Anwendungen | ||
| + | * GenAI und Agentic AI Tools (z. B. LlamaIndex, LangChain/LangGraph). | ||
| + | * LangGraph-orchestrated LLM agents to autonomously investigate cloud incidents | ||
| + | * PagerDuty, Datadog, Grafana, Netdata, Dynatrace, Coroot, ThousandEyes, BigPanda | ||
| + | * Any tool that can send webhooks can trigger an automated investigation. | ||
| + | * How is Aurora different from Rootly or incident.io? | ||
| + | =LLM= | ||
| + | * A Large Language Model (LLM) is an AI system trained on huge amounts of text to understand and generate human-like language. | ||
| + | * An LLM is a program that predicts the next word in a sentence, based on everything it has learned from massive datasets. | ||
| + | * LLM = very advanced autocomplete trained on the internet | ||
| + | |||
| + | ==What LLMs can do== | ||
| + | * Answer questions | ||
| + | * Write emails, essays, code | ||
| + | * Translate languages | ||
| + | * Summarize documents | ||
| + | * Chat like a human | ||
| + | |||
| + | ==What LLMs can't do== | ||
| + | * LLMs don’t “think” like humans. | ||
| + | * Don’t truly understand meaning | ||
| + | * Don’t have opinions | ||
| + | * Just predict the most likely next words based on patterns | ||
| + | |||
| + | ==Examples of LLMs== | ||
| + | * GPT-4 → chatgpt.com | ||
| + | * LLaMA (https://www.llama.com/) from Meta | ||
| + | * Mistral | ||
| + | * Gemma | ||
| + | * Claude → Claude.ai | ||
| + | * Gemini → https://gemini.google.com/app | ||
| + | |||
| + | =Regulatory Requirements= | ||
| + | * Regulatory requirements (MaRisk, BAIT, DORA) | ||
| + | * BAIT, DORA oder ISO 27001. | ||
Latest revision as of 15:03, 8 April 2026
Contents
init
- OpenClaw (https://openclaw.ai/)
- Ollama (https://ollama.com/)
- Llama (https://www.llama.com/)
- MiniMax (https://www.minimax.io/)
- Gemma 4 (https://deepmind.google/models/gemma/gemma-4/)
- Aurora (https://www.arvoai.ca/)
- incident.io
Buzz Words
- LLM (Large Language Model)
- LLMOps
- Generative KI
- RAG-Anwendungen
- GenAI und Agentic AI Tools (z. B. LlamaIndex, LangChain/LangGraph).
- LangGraph-orchestrated LLM agents to autonomously investigate cloud incidents
- PagerDuty, Datadog, Grafana, Netdata, Dynatrace, Coroot, ThousandEyes, BigPanda
- Any tool that can send webhooks can trigger an automated investigation.
- How is Aurora different from Rootly or incident.io?
LLM
- A Large Language Model (LLM) is an AI system trained on huge amounts of text to understand and generate human-like language.
- An LLM is a program that predicts the next word in a sentence, based on everything it has learned from massive datasets.
- LLM = very advanced autocomplete trained on the internet
What LLMs can do
- Answer questions
- Write emails, essays, code
- Translate languages
- Summarize documents
- Chat like a human
What LLMs can't do
- LLMs don’t “think” like humans.
- Don’t truly understand meaning
- Don’t have opinions
- Just predict the most likely next words based on patterns
Examples of LLMs
- GPT-4 → chatgpt.com
- LLaMA (https://www.llama.com/) from Meta
- Mistral
- Gemma
- Claude → Claude.ai
- Gemini → https://gemini.google.com/app
Regulatory Requirements
- Regulatory requirements (MaRisk, BAIT, DORA)
- BAIT, DORA oder ISO 27001.
