Awesome List Updates on Nov 01, 2023

10 awesome lists updated today.

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1. Awesome Scientific Writing

Spell Checking and Linting

• proselint (⭐4.4k) - Linter for prose.

Tutorials / Books

• 3 frameworks into one — Write your next paper with R Studio! - Article provides an overview to a workflow that combines R Markdown (bookdown), Zotero (literature management), and Notion (note taking on research papers) to write academic papers.

• Heads up! Quarto is here to stay. Immediately combine R & Python in your next document - Summary of the capabilities of Quarto, why to use it, and how it compares to R Markdown. Also contains tips for M1 Mac users on how to fix a common problem with reticulate.

2. Awesome Blazor

Others

• Netflix microfrontend like (⭐29) - A netflix-like portal application with pilets. This sample demonstrates the use of piral to build a dynamic app consisting of various micro frontends. Demo.

Videos / Others

• Blazor on .NET 8 - Ten Reasons why Blazor on .NET 8 is a Game Changer - October 10, 2023 - 10 reasons why the new enhancements and new features about Blazor released with .NET 8 are an absolute game changer.

3. Awesome Capacitorjs

Plugins / Community Plugins

• capacitor-plugin-safe-area (⭐106) - Get SafeArea info on Android and IOS.

4. Awesome Agi Cocosci

Meta-Level Considerations / Cognitive Architecture

• Epistemology - Plato Stanford.

5. Awesome Swift

Chat

• ExyteChat (⭐1.4k) - SwiftUI Chat UI framework with fully customizable message cells, input view, and a built-in media picker

6. Awesome Actions

Static Analysis / Linting

• Run stolt/lean-package-validator to ensure your package has only the required runtime artifacts (⭐0)

7. Awesome Graphql

JavaScript Examples / React

• Apollo Client documentation - Documentation and example for building GraphQL apps using apollo client.

8. Urban and Regional Planning Resources

Public Data Resources / Housing

• National Housing Preservation Database - The National Housing Preservation Database contains property and subsidy-level data pulled from nine different HUD and USDA data sources. The database contains information on over 70,000 properties nationwide.

9. Awesome Generative Deep Art

Ethics, Philosophical questions and Discussions about Generative AI

• Redefining Bias: The Human Prejudice Against AI | Medium

• AI Art and its Impact on Artists: paper published in the Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

• The AIKEA Effect: by Artur Piszek

• Ethics of Artificial Intelligence: Case Studies and Options for Addressing Ethical Challenges | SpringerLink

• Embracing change and resetting expectations | Microsoft Unlocked: text by Terence Tao

• Art and the science of generative AI | Science

• Where AI evolves from here

• The Age of AI has begun: notes by Bill Gates

• GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models: OpenAI's paper that discusses the possible implications of GPTs on the U.S. labor market

• Why generative AI scares artists but not content writers

• Cultures in AI/AI in Culture: NeurIPS 2022 Workshop webpage

• AI Data Laundering - Waxy.org: How Academic and Nonprofit Researchers Shield Tech Companies from Accountability

• [🔥🔥🔥] (1232) The End of Art: An Argument Against Image AIs - YouTube: video essay by Steven Zapata

• [🔥🔥🔥] The End of Art: An Argument Against Image AIs (Public) - Google Docs: transcript of the video essay by Steven Zapata

• [🔥🔥🔥] Generative AI: A Creative New World | Sequoia Capital US/Europe: report by Sequoia Capital about the possible applications of Generative AI

• Synthetic Creativity - by Cavin - Deep Markets

• Our Vision for the Future of Synthetic Media | by Victor Riparbelli | Medium

• Deep Else: A Critical Framework for AI Art

• How Photography Became An Art Form | Aaron Hertzmann’s blog

• Can Computers Create Art? by Aaron Hertzmann: 2018's essay published on the Arts Journal

• This artist is dominating AI-generated art. And he’s not happy about it. | MIT Technology Review

• The REAL fight over AI art: StableDiffusion | Reddit

• Rutkowski battling AI art overlord | Reddit

• Instead of mining cryptocoins with GPUs, are we now mining art? | Reddit

• Using AI to create art is NOT art! | Reddit : ArtistLounge

• Appreciating the Poetic Misunderstandings of A.I. Art | The New Yorker

Critical Views about Generative AI

• [2310.13149] Understanding Generative AI in Art: An Interview Study with Artists on G-AI from an HCI Perspective

• [2309.12338] Artificial Intelligence and Aesthetic Judgment: "as generative AI influences contemporary aesthetic judgment we outline some of the pitfalls and traps in attempting to scrutinize what AI generated media means"

• AI Worship | Marginal REVOLUTION

• Artificial intelligence technology behind ChatGPT was built in Iowa — with a lot of water | AP News

• ChatGPT is fun, but not an author | Science

• Behind the AI boom, an army of overseas workers in ‘digital sweatshops’ | The Washington Post: Scale AI’s Remotasks workers in the Philippines cry foul over low pay

• It’s Not Intelligent If It Always Halts: A Critical Perspective on Current Approaches to AGI | Life Is Computation

• The human costs of the AI boom | TechCrunch

• AI Scams, Spam, Hacking, Are Ruining the Internet

• The ChatGPT revolution is another tech fantasy

• Why AI Will Save the World | Andreessen Horowitz

• Hollywood studios proposed AI contract that would give them likeness rights ‘for the rest of eternity’ - The Verge

• The shady world of Brave selling copyrighted data for AI training

• Inside the AI Factory: the humans that make tech seem human - The Verge

• Why transformative artificial intelligence is really, really hard to achieve

• AI and the automation of work — Benedict Evans

• Yuval Noah Harari argues that AI has hacked the operating system of human civilisation

• Generative AI Takes Stereotypes and Bias From Bad to Worse

• Governance of superintelligence by OpenAI

• AIAAIC - AIAAIC Repository: "The independent, open, public interest resource detailing incidents and controversies driven by and relating to artificial intelligence, algorithms, and automation"

• Just Calm Down About GPT-4 Already - IEEE Spectrum

• Pause Giant AI Experiments: An Open Letter - Future of Life Institute

• "OpenAI released plugins for ChatGPT": tweet from @thealexbanks with a list of reflections about the impact of ChatGPT plugins

• Is a socially fair Artificial Intelligence possible? | Uma Inteligência Artificial socialmente justa é possível?: post in Portuguese by H.D. Mabuse

• Noam Chomsky on ChatGPT: It's "Basically High-Tech Plagiarism" and "a Way of Avoiding Learning" | Open Culture

• Despite Their Feats, Large Language Models Still Haven't Contributed to Linguistics | Towards Data Science

• Will ChatGPT Kill the Student Essay? | The Atlantic

• What ChatGPT and generative AI mean for science | Nature

• ChatGPT Is a Bullshit Generator Waging Class War

• Some thoughts about generative AI and the future of education – Mark Carrigan

• Educator Considerations for ChatGPT - OpenAI API

• Stable Diffusion Frivolous · Because lawsuits based on ignorance deserve a response.: a community response for the "Stable Diffusion litigation"

• Stable Diffusion litigation · Joseph Saveri Law Firm & Matthew Butterick

• Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations | OpenAI

• Abstracts written by ChatGPT fool scientists

• When Machines Change Art | Aaron Hertzmann’s blog

• The Dark Risk of Large Language Models | WIRED UK

• ChatGPT, DALL-E 2 and the collapse of the creative process

• What AI-Generated Art Really Means for Human Creativity | WIRED

• Forecasting Potential Misuses of Language Models for Disinformation Campaigns—and How to Reduce Risk

• The Dark Side of AI Art: 4 Potential Issues With the Growing Trend

• Armed With ChatGPT, Cybercriminals Build Malware And Plot Fake Girl Bots

• ChatGPT And The Mass Production Of Office Work - Farsight

• The Danger Of ChatGPT Nobody Talks About | by Jacob Ferus | Dec, 2022 | Medium

• Mind Control in the Metaverse. If we’ve learned anything about… | by Louis Rosenberg | Predict | Dec, 2022 | Medium

• The Brilliance and Weirdness of ChatGPT - The New York Times

• Como o texto gerado por Inteligência Artificial está envenenando a Internet - MIT Technology Review

• O ChatGPT é o momento “Jurassic Park” da inteligência artificial - NeoFeed

• Por favor, mais racionalidade e menos frenesi em relação ao chatGPT (Parte 1 de 2) | by Cezar Taurion | Dec, 2022 | Medium

• E se estivermos usando uma IA pseudocientífica? - Diogo Cortiz

• As limitações da sensação tecnológica de 2023: o ChatGPT | IAgora? | Época NEGÓCIOS

• 7 Revealing Ways AIs Fail - IEEE Spectrum

Generative AI Processes and Artifacts

• Starting with Data: Every Generative AI process begins with data. This can be in various forms such as text, images, sounds, or other datasets. This data serves as the foundational material that the AI uses to recognize and understand patterns.

• Training the AI: With the data in hand, the next step is 'training'. During this phase, the AI processes the data multiple times to learn and internalize the patterns present. The outcome of this stage is a 'model', which acts like a digital representation of the knowledge derived from the data.

• Fine-Tuning: At times, there's a need for the AI to focus on specific nuances or characteristics. In such cases, an additional set of data is used to 'fine-tune' the already trained model, enhancing its capabilities in the desired direction.

• Using the Model: After training, the model is prepared to make inferences, which means using its acquired knowledge to process new data and come up with relevant outputs. This inference process can be executed locally on a machine or can be accessed remotely through an 'API'. The choice between local execution and API access often depends on factors like computational resources, application needs, and user preferences. Whether locally or via an API, the goal is to leverage the model's capabilities to derive meaningful results from new data inputs.

• Generating New Data: With the model set up, the AI can now produce or 'generate' new data. By giving the AI certain 'input parameters' or guidelines, it returns with 'generated output', which is the newly created content.

• Applications: The output generated by the AI can be incorporated into a range of applications, be it websites, mobile apps, or other digital platforms. The 'interface' refers to the user-facing portion of these applications, enabling users to interact with and benefit from the AI's capabilities.

Generative AI Tools Directories

• The Generative AI Landscape: "a collection of awesome generative AI applications"

• The ultimate list of AI tools for creators | Descript: collection organized by Descript

LangChain / Multi-agents

• Langchain for paper summarization

• Embedchain (⭐37k): Framework to create ChatGPT like bots over your dataset

• FlowiseAI: "Open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript"

• LangChain Docs: Python library that helps building applications with LLMs through composability

• Getting started with LangChain | by Avra | Feb, 2023 | Medium: A powerful tool for working with Large Language Models

AI Tools for Searching / Multi-agents

• whitead/paper-qa: "LLM Chain for answering questions from documents with citations"

• Metaphor: search engine that "understands language — in the form of prompts — so you can say what you're looking for in all the expressive and creative ways"

AI Tools for Research / Multi-agents

• [2310.17143] Supercharging academic writing with generative AI: framework, techniques, and caveats

• Elicit: automate research workflow for literature review

• Paper Brain: summarizer for paper parts. The user needs to copy and paste into their interface.

• Explainpaper: "Upload a paper, highlight confusing text, get an explanation"

• Paper Player: A new way for busy scientists and technologists to consume open science

• TalkToPapers - namuan/dr-doc-search: Converse with book - Built with GPT-3 (⭐600): a github util where AI will do the paper reading for you instead

• hwaseem04/Research-digest (⭐2): Research paper summariser application for our hackathon

Image Synthesis / Multi-agents

• deep-floyd/IF (⭐7.8k): open-source text-to-image model with a high degree of photorealism and language understanding by Stability.AI

• Word-As-Image for Semantic Typography: semantically transforming fonts into illustrations

• Muse: Text-To-Image Generation via Masked Generative Transformers

• openai/point-e (⭐6.8k): OpenAI's point cloud diffusion for 3D model synthesis

• [arxiv/2211.11319] VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models

• Parrot Zone: a database of image synthesis references

• Image Synth Link List: a collection of links organized by the collective parrot zone

• [🔥🔥🔥] Ai generative art tools: a massive list of shared Google Colab notebooks and tools organized by @pharampsychotic

• Introduction — PyTTI-Tools

• pyttitools-PYTTI.ipynb - Colaboratory

• pixray/pixray (⭐1k): Pixray is an image generation system

• pixray/pixray_notebooks (⭐40): pixray demo notebooks

• dribnet/pixray-text2image – Run with an API on Replicate

• sberbank-ai/ru-dalle (⭐1.6k): Generate images from texts. In Russian.

• Pyttipanna: visual interface for Pytti by @_staus. Pytti is created by @sportsracer48

• Imagen: Google's Text-to-Image Diffusion Models

• Make-A-Scene: Meta's creative control for AI image generation

• Stable Diffusion: Stability.Ai's text-to-image model that is a breakthrough in speed and quality meaning that it can run on consumer GPUs

• CLIPasso: Semantically-Aware Object Sketching

• DreamFusion / Twitter: Text-to-3D using 2D Diffusion paper

• apple/ml-no-token-left-behind (⭐141): PyTorch Implementation of No Token Left Behind: Explainability-Aided Image Classification and Generation

• disco-diffusion/Local_Disco_Diffusion_v4_1.ipynb at main · Midgraph/disco-diffusion

• Audio to keyframe string: this tool is used to generate strings for the keyframes of AI animation notebooks, such as this VQGAN+CLIP Animations notebook, using the volume of audio tracks.

• [🔥] S2ML Image Generator: evolution of the first VQGAN+CLIP Google Colab notebook by Katherine Crownson maintained by Justin Bennington

• [🔥] Create Variations on Images With Looking Glass 1.1 (ru-DALLE) - YouTube | Artificial Images

• [🔥] Looking Glass 1.1 (ru-DALLE): Making ruDALL-E fine tuning quick and painless. Copyright (C) 2021 Bearsharktopus Studios

• NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion (ML Research Paper Explained) - YouTube | Yannic Kilcher

• [🔥] yuval-alaluf/hyperstyle (⭐1k): Official Implementation for "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing" https://arxiv.org/abs/2111.15666

• [🔥] Vadim Epstein’s Aphantasia library (⭐788): CLIP + FFT/DWT/RGB = text to image/video

• mikaelalafriz/lucid-sonic-dreams (⭐775): syncs GAN-generated visuals to music

• Greg Surma - Portfolio

• crowsonkb (Katherine Crowson): who wrote the tutorial of VQGAN+CLIP

• DALL·E: Creating Images from Text

• DALL-E mini: DALL·E mini is an AI model that generates images from any prompt you give!

• DALL-E mini GitHub (⭐15k)

• DALL-E mini Project Report

• CLIPIT PixelDraw - Colaboratory

• CLIP Guided Diffusion HQ 512x512.ipynb - Colaboratory

• Smooth Transitioning Between Position / Rotation / Zoom and Text Inputs by Keyframing Parameters: A Proof of Concept [15,000 Frames] : deepdream

• neural-dream Alternatives and Similar Photos & Graphics Apps | AlternativeTo

• CoG 21: Adversarial Reinforcement Learning for Procedural Content Generation

• GitHub Repositories of Hugging Face

10. Awesome Cpp

Compression

• minizip-ng (⭐1.4k) - Fork of the popular zip manipulation library found in the zlib distribution. [zlib]

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