🚀 Google Introduces TranslateGemma — New Open Models for Translation
Google has released TranslateGemma — a family of open source models that supports 55 languages and operates in three variants: 4B, 12B, and 27B parameters. The focus is on efficiency: translation quality remains high, while latency is low, and everything works without the need for cloud connectivity.
TranslateGemma is built on the foundation of Gemma 3 and was trained on data generated by the AI model Gemini. In simpler terms, Google has transferred the intelligence of a large model into a more compact and user-friendly format.
Now developers can integrate powerful translators directly into devices — no servers needed. You can already try out TranslateGemma on Hugging Face and Kaggle.
Google has released TranslateGemma — a family of open source models that supports 55 languages and operates in three variants: 4B, 12B, and 27B parameters. The focus is on efficiency: translation quality remains high, while latency is low, and everything works without the need for cloud connectivity.
TranslateGemma is built on the foundation of Gemma 3 and was trained on data generated by the AI model Gemini. In simpler terms, Google has transferred the intelligence of a large model into a more compact and user-friendly format.
Now developers can integrate powerful translators directly into devices — no servers needed. You can already try out TranslateGemma on Hugging Face and Kaggle.
GitHub Copilot Now Works with OpenCode!
Now, GitHub Copilot subscribers can officially use OpenCode. By subscribing to Pro+, you gain access to top-tier models for programming. It's great to see that the platform continues to support open-source and leaves the choice of tools in the hands of the users!
Now, GitHub Copilot subscribers can officially use OpenCode. By subscribing to Pro+, you gain access to top-tier models for programming. It's great to see that the platform continues to support open-source and leaves the choice of tools in the hands of the users!
How to Bypass Anti-Bots Without Breaking Your Agent
If you've ever tried to automate data collection from YouTube, Instagram, or Amazon, you know — these sites immediately cut off any automated requests. The result is always the same: either the agent breaks down or starts to "improvise," failing to retrieve the necessary data.
This is a problem for everyone:
▪️ research agents pulling news
▪️ sales agents scraping LinkedIn
▪️ e-commerce agents monitoring prices
▪️ social media agents catching trends
In the video, I demonstrate a simple test:
- on the left: Claude pulls data from YouTube. Without special tools — he tries yt-dlp, but quickly crashes
- on the right: using the MCP server from Bright Data — the same request in just one click, and it all works
The magic is all inside: Bright Data takes care of proxies, rotation, captchas, and anti-bots, while for the agent, it all looks like a regular API call.
The MCP server is open-source, and there’s a free tier for up to 5000 requests per month. Here’s the link to check it out for your tasks: https://github.com/brightdata/brightdata-mcp
If you've ever tried to automate data collection from YouTube, Instagram, or Amazon, you know — these sites immediately cut off any automated requests. The result is always the same: either the agent breaks down or starts to "improvise," failing to retrieve the necessary data.
This is a problem for everyone:
▪️ research agents pulling news
▪️ sales agents scraping LinkedIn
▪️ e-commerce agents monitoring prices
▪️ social media agents catching trends
In the video, I demonstrate a simple test:
- on the left: Claude pulls data from YouTube. Without special tools — he tries yt-dlp, but quickly crashes
- on the right: using the MCP server from Bright Data — the same request in just one click, and it all works
The magic is all inside: Bright Data takes care of proxies, rotation, captchas, and anti-bots, while for the agent, it all looks like a regular API call.
The MCP server is open-source, and there’s a free tier for up to 5000 requests per month. Here’s the link to check it out for your tasks: https://github.com/brightdata/brightdata-mcp
Claude Code now shows diffs right in the app
No more jumping between GitHub and your IDE to see changes: the diff view has arrived in Claude Code for both web and desktop. You can now see exactly what has changed—right within the app. Open the full diff, leave inline comments, and collaborate with Claude on edits step by step—all in one place.
No more jumping between GitHub and your IDE to see changes: the diff view has arrived in Claude Code for both web and desktop. You can now see exactly what has changed—right within the app. Open the full diff, leave inline comments, and collaborate with Claude on edits step by step—all in one place.
AI Built a Browser in a Week — Now It's Real
I stumbled upon a wildly interesting case: developers created a new browser using GPT-5.2 directly in Cursor, allowing the AI to work non-stop for a week. This is not just “evening experiments”—we're talking 3+ million lines of code and thousands of files!
What's particularly cool is that the entire rendering engine was built from scratch in Rust. Inside, there's a fully functional pipeline—HTML parsing, CSS cascade, layout, text rendering, drawing, and even its own JavaScript engine.
The result, of course, is far from WebKit or Chromium: there are plenty of bugs, and complex websites may fall apart. However, simple pages render quickly and look decent. The Google screenshot is definitely viewable!
Going forward, the team promises to test the limits of this approach and share insights.
You can find the code here: https://github.com/wilsonzlin/fastrender
I stumbled upon a wildly interesting case: developers created a new browser using GPT-5.2 directly in Cursor, allowing the AI to work non-stop for a week. This is not just “evening experiments”—we're talking 3+ million lines of code and thousands of files!
What's particularly cool is that the entire rendering engine was built from scratch in Rust. Inside, there's a fully functional pipeline—HTML parsing, CSS cascade, layout, text rendering, drawing, and even its own JavaScript engine.
The result, of course, is far from WebKit or Chromium: there are plenty of bugs, and complex websites may fall apart. However, simple pages render quickly and look decent. The Google screenshot is definitely viewable!
Going forward, the team promises to test the limits of this approach and share insights.
You can find the code here: https://github.com/wilsonzlin/fastrender
Guide to Optimizing React and Next.js Now Available Directly in Claude Code
Vercel has released a detailed Skill for enhancing the performance of React and Next.js — and it can be set up in just a few clicks!
What to do:
1. Enter in the terminal
2. Type
From there, you can either continue coding on your own or watch Claude write for you 😄
Vercel has released a detailed Skill for enhancing the performance of React and Next.js — and it can be set up in just a few clicks!
What to do:
1. Enter in the terminal
npx claude-code-templates@latest --skill=web-development/react-best-practices --yes2. Type
/react-best-practices, and the Skill will launch right in your project.From there, you can either continue coding on your own or watch Claude write for you 😄
60,000+ Agent Skills for Your AI Build
We are sharing a mega-collection of over 60,000 Agent Skills — the perfect way to level up your AI build.
Compatible with Claude Code, Visual Studio Code, Antigravity. Everything you need for an upgrade is in one place!
We are sharing a mega-collection of over 60,000 Agent Skills — the perfect way to level up your AI build.
Compatible with Claude Code, Visual Studio Code, Antigravity. Everything you need for an upgrade is in one place!