Welcome to Today’s episode of AI Daily! First up, we're talking about Lince LLM, a fine-tuned Spanish based LLM by Clibrain. Next, we examine LMQL, an innovative programming language alternative for LLMs that's throwing its hat in the ring against giants like Microsoft with its promise of superior keyword functionality. Lastly, we look at Google's Bard updates and NotebookLM. Tune in to get the full scoop.

Key Points

1️⃣ Lince LLM

* Lince LLM, the first geographically-tuned language model, focuses on the Spanish language and dialect nuances, setting it apart from GPT-4.

* The Madrid-based startup, clibrain, has bootstrapped their own foundational model, specifically designed for Spanish text, chat, and text-to-speech interactions.

* Recognizing the value of language-specific fine tuning, the team plans to continue developing their model, following the trend of region-specific LLMs.

2️⃣ LMQL

* LMQL, a new programming language for large language models (LLMs), offers an alternative to existing systems like Lang Chain and Microsoft Guidance.

* With specific tools for meta-prompting and maintaining chain of thoughts, LMQL seems to offer a more comprehensive and feature-rich framework for LLMs.

* Although LMQL faces the challenge of competing with established systems, its developers are hopeful that it can gain traction and possibly attract investment.

3️⃣ Bard Updates & NotebookLM

* Bard and NotebookLM from Google have been updated with new features like the ability to add images to prompts using Google Lens.

* These tools, already popular with a large user base, will continue to see AI features integration, although immediate significant user growth isn't expected.

* Notebook LM stands out due to its innovative approach, however, it's suspected to be a prototype project with a potentially limited lifespan.

🔗 Episode Links

* Lince LLM

* LMQL

* Bard Updates

* NotebookLM

* Ethan Mollick & NY Times Article

* OpenAI-AP Partnership

* Cognitive Synergy Paper

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