Hello, Moon. It’s great to be back.
Here’s a taste of what the Artemis II astronauts photographed during their flight around the Moon. Check out more photos from the mission: https://t.co/rzM1P0QbOl
Today we're showing Helix 02 that can tidy a living room fully autonomously
Figure is designed so when you leave the house, your home resets exactly how you like it
On December 8, the Perseverance rover safely trundled across the surface of Mars.
This was the first AI-planned drive on another planet. And it was planned by Claude.
We ran experiments to answer: Is Contextual Retrieval still worth it in 2026? Tested on 3 datasets, with/without rerankers (Cohere v4 Pro, Qwen3 8B).
Here's what we found → https://t.co/qYftRIbCmv
We’re rolling out a new YouTube playlist with step-by-step tutorials for our open-source framework — and it’s just getting started. 🚀
We’re releasing videos gradually, covering everything from setup to advanced workflows, so you can dive deeper into the architecture as the series evolves.
👉 Start here: https://t.co/gH0p8JhdV5
#opensource #developers #AI #tutorials
Here are the latest updates from our R&D Lab 🚀
Right now we’re exploring advanced RAG techniques — and for proper evaluation, we need datasets that reflect real-world difficulty.
We tested several public datasets:
📍LegalBench
📍MultiHop-RAG
📍LoCoMo
These have been super helpful starting points for evaluation.
As we applied them to our specific use cases, we realized we needed something more tailored to the GenAI RAG challenges we're focusing on — particularly around domain-specific knowledge and reasoning chains that match our clients' real-world scenarios.
So we built a framework to generate custom evaluation datasets that fit our needs.
We now have two internal domain-heavy evaluation datasets + a public one based on the DnD SRD 5.2.1 that we're sharing with the community.
This is just an initial step, but we're excited about where it's headed. We broke down our approach here:
🔗 Blog post https://t.co/OOYnjntpuW
🔗 GitHub repo https://t.co/sclO2dH4LZ
🔗 Dataset on Hugging Face https://t.co/SK2v9t8tMW
Would love to hear your thoughts, feedback, or ideas on how to improve this!
#RAG #dataset #evaluation #GenAI #framework
Introducing Nested Learning: A new ML paradigm for continual learning that views models as nested optimization problems to enhance long context processing. Our proof-of-concept model, Hope, shows improved performance in language modeling. Learn more: https://t.co/8wvV9vyA5V
@GoogleAI
Our AI framework is live on Product Hunt! 🚀
A few days ago we launched our open-source framework, Datapizza AI.
And starting today, you can also find it on Product Hunt!
For those who haven’t heard of it yet, Product Hunt is a global showcase for new tech launches: every day users discover, vote for, and discuss new products in the comments.
If you’d like to learn more about our framework, check out our Product Hunt page! Here’s the link 👉 https://t.co/CrFh4Lv5VW
And if you want to support us, give us your feedback! 🙏
#datapizzaai #OpenSource #madeinitaly