Model	Performance	Hugging Face
AuraFlow	text-to-img	https://huggingface.co/fal/AuraFlow?ref=blog.fal.ai

SOTA: Hallucination Detection Model

Model	About	Partners
Lynx	Outperformed GPT-4o, Claude3-sonnet, and open-source LLM-as-a-judfe models	NVIDIA, MongoDB, Nomic

Company	Project	About	Source
OpenAI	Strawberry	Advance reasoning and Deep Research	https://www.engadget.com/openai-is-reportedly-working-on-more-advanced-ai-models-capable-of-reasoning-and-deep-research-202419228.html?src=rss&utm_source=tldrai
NOMIC		Explainable AI

Untitled

AI Engineer

https://sierra.ai/blog/meet-the-ai-agent-engineer?utm_source=tldrai

Agent Engineers qualifications;

Strong software engineer background
Master of modern AI stack such as
- LLMS: frontier like GPT-4o,, Claude 3.5 Sonnet, Gemini, and alongside smaller, more specialized models
- Vector Database: Data stores for semantic retrieval
- Prompt Engineer: Standard techniques like few-shot prompting, in-context learning and self-consistency
- AI Orchestration Engines: Tools like LangChain, Flowisem or Sierra’s Agent SDK

Agent engineering in practice

Glossary

Embedding: represent the real-world objects such as image, words, video in a form that computer can process. Unlike other ML technique, embedding learned from various algorithms such as NN. Which allow the model to learn the similarity of the data in a vector array form.
- Embedding is critical for machine learning algorithm.
- Most ML algorithm can only take low-dimensional numerical data as an input (convert bag-og-words for text data, img to pixel, graph data - numerical matrix)
- Obj that come into embedding - embedding output represent as vector array
- Embedding eliminate the needs to manually define the data
For example: OpenAI embedding implementation allows ChatGPT to easily understand the relationship between words and categories instead of just analyzing each word in isolation. With embedding, they achieved an optimum outcome as it produces higher contextually relevant responses to user prompts and questions.