#googlecloud Architect
#machinelearning Practitioner
blog.google/products/gem...
Gemini 3 performs quite well on a wide range of benchmarks.
blog.google/products/gem...
Gemini 3 performs quite well on a wide range of benchmarks.
a ground-up redesign of software development with agents at the center of
antigravity.google
a ground-up redesign of software development with agents at the center of
antigravity.google
📈 1487 Elo on WebDev Arena, 76.2% on SWE-bench Verified
🛠️ Try out Google Antigravity: A new agentic IDE with direct access to the terminal, editor, and browser to build and validate code.
blog.google/products/gem...
📈 1487 Elo on WebDev Arena, 76.2% on SWE-bench Verified
🛠️ Try out Google Antigravity: A new agentic IDE with direct access to the terminal, editor, and browser to build and validate code.
blog.google/products/gem...
Vertex AI now supports preference tuning (DPO) for Gemini 2.5 Flash and Flash-Lite, allowing you to use response pairs to adjust user preferences.
Code and docs in the 🧵
Vertex AI now supports preference tuning (DPO) for Gemini 2.5 Flash and Flash-Lite, allowing you to use response pairs to adjust user preferences.
Code and docs in the 🧵
Notable changes:
* subtests support
* Native TOML configuration
* Progress output in the terminal taskbar
And others. Check the changelog: docs.pytest.org/en/stable/ch...
Notable changes:
* subtests support
* Native TOML configuration
* Progress output in the terminal taskbar
And others. Check the changelog: docs.pytest.org/en/stable/ch...
We are super excited about this new approach and think it will dramatically simplify the path to context aware AI systems, more details in 🧵
We are super excited about this new approach and think it will dramatically simplify the path to context aware AI systems, more details in 🧵
- $ ref for recursive schemas
- anyOf union types
- min + max numerical constraints
- null types
- property ordering adherence
And much more!
- $ ref for recursive schemas
- anyOf union types
- min + max numerical constraints
- null types
- property ordering adherence
And much more!
A practical journey through the challenges, decisions, and messy reality behind training state-of-the-art language models.
huggingface.co/spaces/Huggi...
A practical journey through the challenges, decisions, and messy reality behind training state-of-the-art language models.
huggingface.co/spaces/Huggi...
This formalizes the existing maintenance structure, as I've personally led the project for the past two years on behalf of Hugging Face. I'm super excited about the transfer!
Details in 🧵
This formalizes the existing maintenance structure, as I've personally led the project for the past two years on behalf of Hugging Face. I'm super excited about the transfer!
Details in 🧵
Please install and enjoy Python 3.14! 🥧
discuss.python.org/t/python-3-1...
#Python #Python314 #release
Please install and enjoy Python 3.14! 🥧
discuss.python.org/t/python-3-1...
#Python #Python314 #release
blog.jetbrains.com/ai/2025/10/j...
blog.jetbrains.com/ai/2025/10/j...
Hear directly from the creators as they share the challenges, ideas, and inspiration behind the name.
▶️ Watch the story by @cultrepo.bsky.social now: jb.gg/kz69th
PyCharm: 15 years with Python. And the journey continues.
Hear directly from the creators as they share the challenges, ideas, and inspiration behind the name.
▶️ Watch the story by @cultrepo.bsky.social now: jb.gg/kz69th
PyCharm: 15 years with Python. And the journey continues.
Building AI agents with ADK has been significantly upgraded to reduce latency and costs while grounding with Google Maps data and more.
Release notes:
> github.com/google/adk-...
Building AI agents with ADK has been significantly upgraded to reduce latency and costs while grounding with Google Maps data and more.
Release notes:
> github.com/google/adk-...
Many of you asked, and we've simplified the process: transitioning from an ADK agent to a scalable agent on Vertex AI is now just a single CLI command.
Check out the new docs to try!
👉 Docs: google.github.io/adk-docs/de...
Many of you asked, and we've simplified the process: transitioning from an ADK agent to a scalable agent on Vertex AI is now just a single CLI command.
Check out the new docs to try!
👉 Docs: google.github.io/adk-docs/de...
Memory Bank provides persistent memory for agents.
Now, Vertex AI has introduced a full UI to manage it! 🥳
You can visually View 👁️, Edit ✏️, and Delete 🗑️ all agent memories in a unique place.
Check it out in the Agent Engine console! 👇
Memory Bank provides persistent memory for agents.
Now, Vertex AI has introduced a full UI to manage it! 🥳
You can visually View 👁️, Edit ✏️, and Delete 🗑️ all agent memories in a unique place.
Check it out in the Agent Engine console! 👇
The A2A protocol is great, but what if you need something more tailored? A2A Extensions allow you to add custom, domain-specific functionalities to your agents.
Check out the blog to learn more:
developers.googleblog.com/en/a2a-exte...
The A2A protocol is great, but what if you need something more tailored? A2A Extensions allow you to add custom, domain-specific functionalities to your agents.
Check out the blog to learn more:
developers.googleblog.com/en/a2a-exte...
EmbeddingGemma, the new best-in-class open embedding model! 🚀
🏆 Top multilingual model on MTEB (<500M)
💾 Runs on <200MB RAM
⚙️ Customizable output for on-device use
🧩 Integrated with your favorite tools
developers.googleblog.com/en/introduci...
EmbeddingGemma, the new best-in-class open embedding model! 🚀
🏆 Top multilingual model on MTEB (<500M)
💾 Runs on <200MB RAM
⚙️ Customizable output for on-device use
🧩 Integrated with your favorite tools
developers.googleblog.com/en/introduci...
Vertex AI rolled out a major update for Vertex AI Memory Bank, giving you granular control over your agent's memory.
Let's dive into the new features. 🧵
Vertex AI rolled out a major update for Vertex AI Memory Bank, giving you granular control over your agent's memory.
Let's dive into the new features. 🧵
github.com/scikit-learn...
github.com/scikit-learn...
In LLM app dev, creating a representative evaluation dataset is as tough as prompt engineering. The Gen AI Eval UI now lets you easily generate customizable eval cases and apply objective criteria.
Check out docs in 🧵
In LLM app dev, creating a representative evaluation dataset is as tough as prompt engineering. The Gen AI Eval UI now lets you easily generate customizable eval cases and apply objective criteria.
Check out docs in 🧵
1. brew install --cask zed (on macOS)
2. Select "New Gemini CLI Thread"
3. Install Gemini CLI (if needed)
Learn more in this walkthrough: www.youtube.com/shorts/fAl--...
1. brew install --cask zed (on macOS)
2. Select "New Gemini CLI Thread"
3. Install Gemini CLI (if needed)
Learn more in this walkthrough: www.youtube.com/shorts/fAl--...
→ Try Gemini CLI with full code context in Zed
→ Build & run multiple agents in your editor
→ Powered by the new Agent Client Protocol (ACP)
Learn more:
→ Try Gemini CLI with full code context in Zed
→ Build & run multiple agents in your editor
→ Powered by the new Agent Client Protocol (ACP)
Learn more:
From a side project in Amsterdam to a language shaping the world— discover the story of #Python. Featuring Guido van Rossum & many more!
www.youtube.com/watch?v=GfH4...
From a side project in Amsterdam to a language shaping the world— discover the story of #Python. Featuring Guido van Rossum & many more!
www.youtube.com/watch?v=GfH4...