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- Figma's AI Release 🎨, A Model of a Human Mind 🧠, Amazon turns 30 🎂
Figma's AI Release 🎨, A Model of a Human Mind 🧠, Amazon turns 30 🎂
Today's TechToks: Figma AI, Meta's code optimizing LLMs, Big Tech's tactic against antitrust policy, Amazon 30th anniversary, Trending GitHub Repositories, Product Picks and more!
TechTok by João Martins
July 02, 2024
Today’s Summaries
See all as stories in techtok.today
Today's Picks🍒
✨ Figma AI: Design products with a text prompt and other AI features embedded in the design tool.
🚀 From HuggingFace papers: A 1,000,000,000 Persona approach to generating synthetic data at scale with LLMs.
🔬 Meta introduces the Large Language Model Compiler: a suite of pre-trained models for code optimization tasks.
🎂 What's next for Amazon as it turns 30— an overview (The Economist).
🕹️ Big tech outsmarts antitrust with 'reverse acquihire' strategy.
🤖 From Engineering Blogs: How Meta scales large language models.
🧠 Blog post: A simple model of how minds might work.
GitHub's Trending Repositories
🏦 gs-quant: a toolkit for quantitative finance.
🌌 fabric: an open-source framework for augmenting humans using AI.
📦 uv: a super fast Python package installer written in Rust.
🐍 30-Days-Of-Python: a step-by-step guide and challenge to learn the Python programming language in 30 day.
Product Picks
💼 Arc 3.0: Global marketplace for top developers, designers, and marketers.
🌌 Plus AI: Create your next PowerPoint in minutes using Plus AI, directly in PowerPoint.
📰 Testimonify: Powerful SaaS platform designed to help businesses collect, manage, and showcase customer testimonials and feedback.
+7 more!
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🤯 Game Changers
The most impactful articles of the day
Figma introduces Figma AI, a suite of AI-powered features in free beta for all users through 2024:
Design Generation from Text Prompts: Generate UI layouts and components from descriptions.
Visual Search: Find designs using images or text queries to reuse them.
AI-Enhanced Asset Search: Locate components based on semantic meaning, not just names.
Text Tools: Translate, shorten, or rewrite text with AI assistance.
Image Generation: Create realistic images and remove backgrounds directly in Figma.
Interactive Prototyping: Quickly turn static mocks into interactive prototypes.
Automatic Layer Renaming: Save time with contextual, automated layer naming.
✨ "Too long don't README"
GitHub trending repos of today
The fabric repository is an open-source framework for augmenting humans using AI. It provides a collection of pre-built 'Patterns' that can be used to perform various tasks like extracting wisdom from videos and podcasts, writing essays, summarizing academic papers, generating AI art prompts, and more.
The repository emphasizes a philosophy of breaking down problems into smaller components and applying AI to each one, with a focus on readability, clarity, and efficiency of prompts. The quick start guide provides instructions for setting up the fabric client and using the available Patterns, as well as options for creating custom Patterns and helper apps.
GS Quant is a Python toolkit for quantitative finance, created and maintained by Goldman Sachs quants to enable the development of trading strategies and analysis of derivative products, which can be used for derivative structuring, trading, and risk management, or as a set of statistical packages for data analytics applications.
The 'uv' repository is an extremely fast Python package installer and resolver, written in Rust, designed as a drop-in replacement for pip and pip-tools commands. You can use it to help with your Python development workflows by installing packages, dependencies, and creating virtual environments more efficiently and quickly.
For learners
This repository contains a 30-day Python programming challenge, covering a topic per day, from variables and built-in functions to API development. The challenge is designed for beginners and professionals to learn Python step-by-step, with easy-to-understand explanations, real-world examples, hands-on exercises, and projects.
📱 Product Picks
Curated products from Product Hunt and MicroLaunch
💼 Arc 3.0: Global marketplace for top developers, designers, and marketers.
🌌 Plus AI: Create your next PowerPoint in minutes using Plus AI, directly in PowerPoint.
📰 Testimonify: Powerful SaaS platform designed to help businesses collect, manage, and showcase customer testimonials and feedback.
🎉 Respired: Affordable AI-driven social media management across Instagram, Facebook, and LinkedIn.
🌄 AI VisionBoard: Create bright realistic AI-generated images of you in your dreams from your photo + text in seconds.
🏅Hubflo: The AI-powered client portal for professional & creative services.
⛵ProJourney: Use Midjourney without Discord.
👓 Seethrough: Enrich your B2B users with up-to-date company data.
🏷️ Branding Kit: Ultimate Guide to Brand Building.
⚖️ Measured: UI-based GTM alternative without tracking codes, even for native apps.
🧐 Daily Picks
Curated picks and most shared articles on techtok.today
Meta released the Meta Large Language Model Compiler: a suite of pre-trained models designed for code optimization tasks, available with 7 billion and 13 billion parameters at HuggingFace. Built on top of Meta Code Llama with additional code optimization and compiler capabilities, with training on assembly code and the language-free code representations of LLVM-IR, it achieves state-of-the-art results on code size optimization and disassembly.
Why it matters? It's progress on a task LLMs have yet to satisfy: code optimization.
As Amazon turns 30, the e-commerce giant faces the challenge of integrating its sprawling businesses, from retail and advertising to cloud computing and video streaming. Under new CEO Andy Jassy, Amazon is stitching these disparate parts together more tightly, leveraging synergies like Prime memberships and generative AI. However, this integration could put off some of AWS's big clients and raises antitrust concerns, as Amazon continues to dominate e-commerce and expand into new sectors.
Big Tech firms like Amazon and Microsoft are employing a 'reverse acquihire' strategy in the AI industry— where the hiring of people and a corresponding licensing deal is designed to disguise what is actually an acquisition. By hiring key teams from AI startups like Inflection and Adept, and licensing their technologies, these tech giants are able to acquire talent and capabilities without facing scrutiny from antitrust regulators, who can limit the market power of a firm to encourage competition and avoid monopoly or trusts.
A paper on a persona-driven data synthesis methodology that leverages a large language model to create diverse synthetic data at scale, from HuggingFace daily papers. Featuring Persona Hub, a collection of 1 billion diverse personas curated from web data, which enables the generation of high-quality synthetic data for various scenarios like mathematical reasoning, instructions, and game NPCs.
This article presents a detailed model of the human mind, encompassing key aspects such as agency, memory, learning, thinking, and introspection. The model suggests that digital minds could one day achieve personhood and subjective experiences akin to our own, challenging the notion that consciousness is fundamentally beyond scientific explanation. The author advocates for ambitious yet detailed approaches to modeling the mind, in contrast with overly high-level or narrow perspectives, in the hopes of advancing the field of digital consciousness.
👩🏽💻 Engineering Blogs
Articles from engineering blogs of big tech companies
A look into Meta'a scalable infrastructure to train large language models at a scale: aiming for hardware reliability, fast recovery on failure, efficient preservation of training state, and optimal GPU connectivity. Solutions included building two types of clusters (RoCE and InfiniBand) to support large-scale training and optimize performance, changing GPUs to HBM3 models in the Grand Teton platform, and planning for hardware failure detection and remediation.
