kennethologist

Big win for Chamath!

Meta announced several key updates to enhance building with Llama and strengthen the open-source ecosystem:

1. Llama API Preview: Launched a limited preview of the Llama API, a developer platform simplifying Llama application development with easy API key creation, playgrounds, SDKs, and tools for fine-tuning and evaluation. It emphasizes model portability and privacy.

2. Fast Inference Collaborations: Announced collaborations with Cerebras and Groq to offer developers access to faster Llama model inference speeds via the Llama API.

3. Expanded Llama Stack Integrations: Revealed new and expanded Llama Stack integrations with partners like NVIDIA, IBM, Red Hat, and Dell Technologies to make deploying Llama applications easier for enterprises.

4. New Llama Protection Tools & Program: Released new open-source security tools including Llama Guard 4, LlamaFirewall, and Llama Prompt Guard 2, updated CyberSecEval 4, and announced the Llama Defenders Program for partners to help evaluate system security.

5. Llama Impact Grant Recipients: Announced the 10 international recipients of the second Llama Impact Grants, awarding over $1.5 million USD to support projects using Llama for transformative change.

Overall, the announcements emphasize making Llama more accessible, easier to build with, faster, more secure, and supporting its diverse open-source community.

Just ask the LLM to walk you through each line of code, create an explain the dependency graphs and in a relatively short period of time they’ll know exactly how their code works. Using Claude Code is quite useful for this - I use it on GitHub repositories I’m curious about.

A. Legend. Thanks for having DeepSeek available so quickly in LM Studio.

Tell us more about the structure. Maybe can help someone reading.

Anyone knows at a deeply practical and technical level how 11Labs achieves the level they do?