How do you quickly go from POC to prod ready?

We'll be discussing methods and techniques to make this possible at the Gen AI Tools Infra & Open Source Demo Days this May 8th!

Don't miss it: generative-ai-summit.com/tools/

AI cloud should be ridiculously easy to use, chat with the docs doesn't address the real pain points.

Many struggle to successfully implement AI initiatives, in large part due to the complexities and challenges surrounding data curation and wrangling.

And many practitioners lack the data required for model customization.

But what if you could leverage the same data generation

LLaMA3 and Phi3 have made the splash this week in LLM Arena. But how strong is their visual understanding ability?

⚡We release LLaMA3-Vision and Phi3-Vision models that beat their larger size LLM competitors.

Github: github.com/mbzuai-oryx/LL…
HF: huggingface.co/collections/MB…

We're always hearing about closed versus open AI.

How about some attention to the topic of centralized versus decentralized AI.

When a centralized service is down, it doesn't matter if it was open or closed, everybody suffers.

🚨 Code Release 🚨

MoMA: Multimodal LLM Adapter for Fast Personalized Image Generation

github.com/KunpengSong/Mo…

It's no surprise that AI engineers apply AI in their data curation pipelines.

In LESS, researchers show how to optimize your LLMs for downstream applications by filtering your datasets for higher quality and more relevant samples.

In CodecLM, researchers show how to synthesize

Do you know a developer who can afford to make decisions about which AI to deploy based on hearsay from TechCrunch journalists?

Where is the scientific method here? 🔍

When e-commerce and content streaming giants want to help users make sense of a massive catalogue, they use