Excited to share a new paper that aims to narrow the conceptual gap between the idealized notion of Kolmogorov complexity and practical complexity measures for neural networks.
In a recent technical report, LearnLM, our set of AI models and capabilities fine-tuned for learning, outperformed other leading AI models on the principles of learning science. Now it’s available to try out in AI Studio. Learn more ↓ https://t.co/V6IPvlSo4n
(1/6) 📢 Thrilled to share that our technical report "LearnLM: Improving Gemini for Learning" is out, alongside our #LearnLM model that we released on AI Studio!
#google#ai#education#EdTech#Gemini
Highlights and links below ⬇️
“Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach” is now available at https://t.co/xQygtwSXdx
#ICML2024: Irina Jurenka and Markus Kunesch will be demoing the LearnLM-Tutor at the GDM booth on Tues afternoon: https://t.co/Hif7rD7BFU
What if everyone, everywhere could have their own personal AI tutor, on any topic? 💡
We’re making learning more engaging and personal with our new family of models, LearnLM.
Find out more → https://t.co/RX9n87Apom #GoogleIO
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
Shows that, based on pixel-based pretraining, it is possible for an agent to outperform human crowdworkers on MiniWob++ of GUI-based instruction following tasks
https://t.co/L0BCcaB5Kj
Excited to present Pix2Act! An agent that can interact with GUIs using the same conceptual interface that humans commonly use — via pixel-based screenshots and generic keyboard and mouse actions -- https://t.co/NX06uTpcVV (1/4)