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AI (Artificial Intelligence)

Machines simulating human characteristics and intelligence.
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Python github.com

ImaginAIry imagines & edits images from text inputs

This is a Pythonic wrapper around stable diffusion with image editing by InstructPix2Pix. The four images featured below (top) are generated by the following command:

imagine "a scenic landscape" "a photo of a dog" "photo of a fruit bowl" "portrait photo of a freckled woman"

Then they are edited (bottom) with the following commands:

>> aimg edit scenic_landscape.jpg "make it winter" --prompt-strength 20
>> aimg edit dog.jpg "make the dog red" --prompt-strength 5
>> aimg edit bowl_of_fruit.jpg "replace the fruit with strawberries"
>> aimg edit freckled_woman.jpg "make her a cyborg" --prompt-strength 13
ImaginAIry imagines & edits images from text inputs

Python github.com

A library for building apps with LLMs through composability

Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge.

This library is aimed at assisting in the development of those types of applications.

LangChain is designed to help with prompts, chains (sequences of calls), data augmented generation, agents, memory & evaluation tasks.

Practical AI Practical AI #207

Machine learning at small organizations

Why is ML is so poorly adopted in small organizations (hint: it’s not because they don’t have enough data)? In this episode, Kirsten Lum from Storytellers shares the patterns she has seen in small orgs that lead to a successful ML practice. We discuss how the job of a ML Engineer/Data Scientist is different in that environment and how end-to-end project management is key to adoption.

AI (Artificial Intelligence) watcher.guru

Microsoft wants to acquire a 49% stake in ChatGPT

This escalated quickly. I don’t know about you, but I’m a daily user of ChatGPT. Just yesterday, I asked “What options does Linux offer for fast RAID 0 software RAID?” and I had an entire conversation that settled on Btrfs as a good option and I learned how to create and configure the array, mount it, and most importantly scrub it for errors. I’ll still use ZFS, of course. But, I’ve never had that experience using Google (nor can you).

…according to a report by Semafor, Microsoft Corp is discussing the possibility of acquiring OpenAI, the parent company of ChatGPT. The tech-industry giant is ready to pay upwards of $10 billion for the acquisition.

Clearly, Microsoft sees the bigger picture here for Bing, Microsoft 365, GitHub Copilot, and more. This also speaks to the conversation we had with Swyx about AI’s future being tied to capitalism and eventually being controlled by the FAANGs.

Practical AI Practical AI #205

NLP research by & for local communities

While at EMNLP 2022, Daniel got a chance to sit down with an amazing group of researchers creating NLP technology that actually works for their local language communities. Just Zwennicker (Universiteit van Amsterdam) discusses his work on a machine translation system for Sranan Tongo, a creole language that is spoken in Suriname. Andiswa Bukula (SADiLaR), Rooweither Mabuya (SADiLaR), and Bonaventure Dossou (Lanfrica, Mila) discuss their work with Masakhane to strengthen and spur NLP research in African languages, for Africans, by Africans.

The group emphasized the need for more linguistically diverse NLP systems that work in scenarios of data scarcity, non-Latin scripts, rich morphology, etc. You don’t want to miss this one!

The Changelog The Changelog #519

GPT has entered the chat

To wrap up the year we’re talking about what’s breaking the internet, again. Yes, we’re talking about ChatGPT and we’re joined by our good friend Shawn “swyx” Wang. Between his writings on L-Space Diaries and his AI notes repo on GitHub, we had a lot to cover around the world of AI and what might be coming in 2023.

Also, we have one more show coming out before the end of the year — our 5th annual “State of the log” episode where Adam and Jerod look back at the year and talk through their favorite episodes of the year and feature voices from the community. So, stay tuned for that next week.

Ars Technica Icon Ars Technica

Stability AI plans to let artists opt out of Stable Diffusion 3 image training

On Wednesday, Stability AI announced it would allow artists to remove their work from the training dataset for an upcoming Stable Diffusion 3.0 release. The move comes as an artist advocacy group called Spawning tweeted that Stability AI would honor opt-out requests collected on its Have I Been Trained website. The details of how the plan will be implemented remain incomplete and unclear, however.

This seems like a step in the right direction, but it appears that artists will have to proactively register and manually flag matched images in the database. Ain’t nobody got time for that!

History dynomight.net

Historical analogies for large language models

How will large language models (LLMs) change the world?

No one knows. With such uncertainty, a good exercise is to look for historical analogies—to think about other technologies and ask what would happen if LLMs played out the same way.

I like to keep things concrete, so I’ll discuss the impact of LLMs on writing. But most of this would also apply to the impact of LLMs on other fields, as well as other AI technologies like AI art/music/video/code.

What follows are 13 examples of technological innovations that changed the world and description of how they affected they way people work. Here’s an example analogy of Feet and Segways:

First, there was walking. Then the Segway came to CHANGE THE NATURE OF HUMAN TRANSPORT. Twenty years later, there is still walking, plus occasionally low-key alternatives like electric scooters.

In this analogy, LLMs work fine but just aren’t worth the trouble in most cases and society doesn’t evolve to integrate them. Domain-specific LLMs are used for some applications, but we start to associate “general” LLMs with tourists and mall cops. George W. Bush falls off an LLM on vacation and everyone loses their minds.

AI (Artificial Intelligence) github.com

OpenAI's Whisper model ported to C/C++

OpenAI recently released a model for automatic speech recognition called Whisper. I decided to reimplement the inference of the model from scratch using C/C++. To achieve this I implemented a minimalistic tensor library in C and ported the high-level architecture of the model in C++. The entire code is less than 8000 lines of code and is contained in just 2 source files without any third-party dependencies.

State of the art voice recognition without any PyTorch baggage and it’s optimized to run on Apple Silicon!

Practical AI Practical AI #203

AI competitions & cloud resources

In this special episode, we interview some of the sponsors and teams from a recent case competition organized by Purdue University, Microsoft, INFORMS, and SIL International. 170+ teams from across the US and Canada participated in the competition, which challenged students to create AI-driven systems to caption images in three languages (Thai, Kyrgyz, and Hausa).

Rust simonwillison.net

Learning Rust with ChatGPT, Copilot and Advent of Code

Simon Willison is using this year’s Advent of Code as an opportunity to learn Rust.

He’s using Copilot to help him with syntax/snippets via comment-driven prompting. He’s using ChatGPT as a study partner by asking it questions about how to do things in Rust. Is it working?

So far I think this is working really well.

I feel like I’m beginning to get a good mental model of how Rust works, and a lot of the basic syntax is beginning to embed itself into my muscle memory.

The real test is going to be if I can first make it to day 25 (with no prior Advent of Code experience I don’t know how much the increasing difficulty level will interfere with my learning) and then if I can actually write a useful Rust program after that without any assistance from these AI models.

And honestly, the other big benefit here is that this is simply a lot of fun. I’m finding interacting with AIs in this way—as an actual exercise, not just to try them out—is deeply satisfying and intellectually stimulating.

This might be an early glimpse into the future of AI-assisted learning…

Practical AI Practical AI #202

Copilot lawsuits & Galactica "science"

There are some big AI-related controversies swirling, and it’s time we talk about them. A lawsuit has been filed against GitHub, Microsoft, and OpenAI related to Copilot code suggestions, and many people have been disturbed by the output of Meta AI’s Galactica model. Does Copilot violate open source licenses? Does Galactica output dangerous science-related content? In this episode, we dive into the controversies and risks, and we discuss the benefits of these technologies.

GitHub kolide.com

GitHub Copilot isn't worth the risk

Elaine Atwell says all CTOs urgently need to answer the question: should I allow Copilot at my company?

If you haven’t already figured it out from the title, Elaine’s answer to that question is No. But that might not be the right answer for everyone. In this article, she goes over the case for and against Copilot, and how you can detect whether it’s already in use at your organization.

Practical AI Practical AI #201

Protecting us with the Database of Evil

Online platforms and their users are susceptible to a barrage of threats – from disinformation to extremism to terror. Daniel and Chris chat with Matar Haller, VP of Data at ActiveFence, a leader in identifying online harm – is using a combination of AI technology and leading subject matter experts to provide Trust & Safety teams with precise, real-time data, in-depth intelligence, and automated tools to protect users and ensure safe online experiences.

Vladimir Prelovac blog.kagi.com

The age of PageRank is over

Google search quality has been deteriorating for awhile. In this manifesto (of sorts), Kagi CEO Vladimir Prelovac describes what he thinks needs to replace it:

In the future, instead of everyone sharing the same search engine, you’ll have your completely individual, personalized Mike or Julia or Jarvis - the AI. Instead of being scared to share information with it, you will volunteer your data, knowing its incentives align with yours. The more you tell your assistant, the better it can help you, so when you ask it to recommend a good restaurant nearby, it’ll provide options based on what you like to eat and how far you want to drive. Ask it for a good coffee maker, and it’ll recommend choices within your budget from your favorite brands with only your best interests in mind. The search will be personal and contextual and excitingly so!

Practical AI Practical AI #200

Hybrid computing with quantum processors

It’s been a while since we’ve touched on quantum computing. It’s time for an update! This week we talk with Yonatan from Quantum Machines about real progress being made in the practical construction of hybrid computing centers with a mix of classical processors, GPUs, and quantum processors. Quantum Machines is building both hardware and software to help control, program, and integrate quantum processors within a hybrid computing environment.

Matthew Butt­erick githubcopilotlitigation.com

We've filed a lawsuit challenging GitHub Copilot

A couple weeks back, Adam logged some news that linked to githubcopilotinvestigation.com. Well, There’s a new website now: githubcopilotlitigation.com

Matthew Butterick:

By train­ing their AI sys­tems on pub­lic GitHub repos­i­to­ries (though based on their pub­lic state­ments, pos­si­bly much more) we con­tend that the defen­dants have vio­lated the legal rights of a vast num­ber of cre­ators who posted code or other work under cer­tain open-source licenses on GitHub. Which licenses? A set of 11 pop­u­lar open-source licenses that all require attri­bu­tion of the author’s name and copy­right, includ­ing the MIT license, the GPL, and the Apache license.

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