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Full Stack AI Coding Agent
PLUS: Gemini grounded in Google Search, Meta Llama 4 training
Shubham Saboo & Gargi Gupta
November 01, 2024
Today’s top AI Highlights:
Gemini API and Google AI Studio now offer Grounding with Google Search
Build, debug, and deploy full-stack apps directly in your browser
Meta is training Llama 4 on a cluster bigger than 100,000 H100s
Claude desktop app for Mac and Windows is here
AI assistant for GitHub PR review - one-click install and 100% free
& so much more!
Read time: 3 mins
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Latest Developments
Google has brought its search engine capabilities directly into the Gemini API and AI Studio so you can ground Gemini’s responses in current web data. The new Grounding with Google Search feature connects all Gemini 1.5 models to Google's search infrastructure, providing in-line source links and search suggestions that developers can integrate into their applications.
While testing is free in Google AI Studio, API access runs at $35 per 1,000 grounded queries - (don’t fret) you can optimize through the dynamic retrieval system it has. This setup gives you precise control over when your app should tap into Google Search data. It’s like web search in the OpenAI API but with a granular control!
Key Highlights:
Implementation & Control - The implementation layer has serious flexibility. You can set dynamic thresholds from 0 to 1 to control grounding activation - grounding only kicks in if the score hits or passes it - and work with source URIs valid for 30 days. The system includes production-ready HTML/CSS for implementing the required Google Search Suggestions interface.
Technical Specifications - The feature works with text queries in any language supported by Gemini. It also gives structured metadata with sources and confidence scores. The dynamic retrieval system keeps performance optimal without overcomplicating the implementation.
Cost optimization - This comes through adjustable thresholds that balance accuracy with API costs. Dynamic retrieval prevents unnecessary calls, while prediction scores help fine-tune settings. Test everything free in AI Studio before going live.
Get started - Activate grounding in Google AI Studio in the "Tools" section or within the Gemini API by enabling the google_search_retrieval tool. Simple Python code examples are available to get you started quickly.
Build full-stack apps directly in your browser—no local setup required. StackBlitz's new bolt.new combines AI and WebContainers, a browser-based runtime, to offer an amazing development experience.
You can build, run, edit, and even deploy complete applications, including backends and databases, all without leaving your browser. bolt.new integrates with popular frameworks like Next.js and React, and features AI-powered assistance extending beyond code generation to active environment management and debugging.
Key Highlights:
Complete In-Browser Environment - Develop, test, and debug full-stack applications entirely within your browser thanks to WebContainers—a micro-OS that runs a full development environment inside your browser tab, supporting npm, Node.js, and various APIs.
AI-Powered Development Assistance - The integrated AI goes beyond code suggestion. It actively manages the entire development lifecycle, automatically resolving errors and providing one-click solutions for common development roadblocks.
Simplified Deployment - Deploy your applications to Netlify (and soon Cloudflare) with a single click. This eliminates the complexities of setting up and managing deployment pipelines, saving you considerable time and effort.
Open-Source - The underlying codebase for bolt.new is opensource so you can inspect, modify, and extend its functionalities.
Quick Bites
Embodied AI—teaching machines to understand and interact with the physical world—remains a tough challenge, as AI struggles with touch and spatial awareness. Meta is rolling out a set of research tools for touch perception and robot dexterity, including Meta Sparsh, a universal touch sensor, and Digit 360, a fingertip sensor with human-level precision. Through partnerships with robotics companies, Meta aims to make these tools accessible to researchers.
And in another exciting update, it’s confirmed that Meta is training its Llama 4 models on a cluster bigger than 100,000 H100s! Imagine if the smallest Llama 4 model would be as good as Llama 3 405B 🤩
Anthropic has launched Claude desktop apps on Mac and Windows in public beta, accessible to both free and premium users. Claude also now has a dictation tool on iOS, Android, and iPadOS, allowing you to send voice messages up to 10 minutes long for transcription and response.
Meta has released its first small LMs for on-device AI, MobileLLM, optimized for mobile use with sub-billion parameters. Contrary to the focus on scaling up model size, Meta’s approach emphasizes depth over parameter count. Available on Hugging Face, these 125M, 350M, 600M, and 1B models deliver excellent performance in mobile applications like API calling.
Google Maps is getting a new AI feature, powered by Gemini, for personalized place recommendations, now rolling out to select Local Guides in the U.S. This feature allows you to ask specific questions, like “places with a vintage vibe,” and get suggestions based on Maps’ extensive location data and community insights.
Tools of the Trade
LlamaPReview: AI assistant that automatically reviews GitHub pull requests, providing context-aware feedback directly on your PRs. It’s free, requires no configuration, and supports all major languages.
FastTrackr AI: Your AI executive assistant that operates directly through WhatsApp, letting you draft emails, schedule meetings, and manage multiple email accounts seamlessly. It turns voice into text, performs quick research, sends reminders, and more.
venvstacks by LM Studio: Packages Python applications with layered virtual environments, separating the runtime, core frameworks, and app-specific components to avoid redundant installations of large libraries like PyTorch.
Data Formulator: AI tool from Microsoft Research that helps analysts create and modify data visualizations. Unlike most chat-based AI tools where you need to describe everything in natural language, it combines user interface interactions and natural language inputs for easier interaction.
Awesome LLM Apps: Build awesome LLM apps using RAG to interact with data sources like GitHub, Gmail, PDFs, and YouTube videos through simple text. These apps will let you retrieve information, engage in chat, and extract insights directly from content on these platforms.
Hot Takes
A principal part of the success of ChatGPT was the ecosystem of "wrappers" that sprung up around it. Few understand this. ~
Logan Kilpatrickwhen people go from sf to hereticon miami the avg iq of both cities goes up ~
roon
Meme of the Day
That’s all for today! See you tomorrow with more such AI-filled content.
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