Meta's #Llama 2 license has an unusual clause whereby they withdraw your right to use the model if you allege #Meta has breached your own IP rights by training their stuff on your intellectual property. #copyright#genai#LLama2
To avoid confusion, the #meta#llama#llm fails open source within a 5 second read of the licence, for instance:
v. You will not use the Llama Materials or any output or results of the
Llama Materials to improve any other large language model (excluding Llama 2 or
derivative works thereof).
After months of work and $10 million, Databricks has unveiled DBRX - the world's most potent publicly available open-source large language model.
DBRX outperforms open models like Meta's Llama 2 across benchmarks, even nearing the abilities of OpenAI's closed GPT-4. Novel architectural tweaks like a "mixture of experts" boosted DBRX's training efficiency by 30-50%.
A major release to Ollama - version 0.1.32 is out. The new version includes:
✅ Improvement of the GPU utilization and memory management to increase performance and reduce error rate
✅ Increase performance on Mac by scheduling large models between GPU and CPU
✅ Introduce native AI support in Supabase edge functions
"There has been a shift in the #AI space: some models, like #ChatGPT & #Gemini, have evolved into entire web platforms spanning multiple use cases & access points. Other large language models like #LLaMa or #OLMo, though technically speaking they share a basic architecture, don’t actually fill the same role. They are intended to live in the background as a service or component, not in the foreground as a name brand." https://techcrunch.com/2024/04/19/too-many-models/
Please, use #AI to generate tons of #content that you otherwise couldn't.
But for the love of all that is holy, pay attention to what you are putting out. Read the output. If it doesn't say exactly what you would say, edit it! Make changes. Regenerate. Go through the process of making it good.
I truly don't think people hate AI content. They hate lazy content.
With all the valid concern around #llm and #genai power and water usage, I thought I'd start a blog series on tiny LLMs. Let's see what they can do on real tasks on very power efficient hardware.