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Exploring developer happiness, inclusion, and productivity at GitHub’s Design Conference
As a design organization, we have the opportunity to make a significant impact on designing the platform for all developers. How does the emergence of creative AI impact our work? How can we achieve an inclusive experience for a spectrum of all abilities? What does designing for developer happiness look like? ⌘ Read more

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A developer’s guide to prompt engineering and LLMs
Prompt engineering is the art of communicating with a generative AI model. In this article, we’ll cover how we approach prompt engineering at GitHub, and how you can use it to build your own LLM-based application. ⌘ Read more

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(De)coding conventions
Navigating the ebb and flow of programming paradigms–from the shifts in the JavaScript ecosystem and TypeScript’s rise, to AI’s role in advancing accessibility, and strategies for encouraging non-code contributions–tune in to the latest episode of The ReadME Podcast for more. ⌘ Read more

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The economic impact of the AI-powered developer lifecycle and lessons from GitHub Copilot
Today at Collision Conference we unveiled breaking new research on the economic and productivity impact of generative AI–powered developer tools. The research found that the increase in developer productivity due to AI could boost global GDP by over $1.5 trillion. ⌘ Read more

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How to use GitHub Copilot: Prompts, tips, and use cases
In this prompt guide for GitHub Copilot, two GitHub developer advocates, Rizel and Michelle, will share examples and best practices for communicating your desired results to the AI pair programmer. ⌘ Read more

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In-reply-to » Home | Tabby This is actually pretty cool and useful. Just tried this on my Mac locally of course and it seems to have quite good utility. What would be interesting for me would be to train it on my code and many projects 😅

@prologic@twtxt.net The hackathon project that I did recently used openai and embedded the response info into the prompt. So basically i would search for the top 3 most relevant search results to feed into the prompt and the AI would summarize to answer their question.

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How GitHub Copilot is getting better at understanding your code
With a new Fill-in-the-Middle paradigm, GitHub engineers improved the way GitHub Copilot contextualizes your code. By continuing to develop and test advanced retrieval algorithms, they’re working on making our AI tool even more advanced. ⌘ Read more

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I have not used AI much at all, I have not paid any attention to it. But today I decided to give stablediffusion a test run, I do only have a 1080 card, so it took some tweaking to output 512x256 images, and I must say it works pretty well. I also had to get one of the memory optimized versions. Fun to test.

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GitHub Copilot X: The AI-powered developer experience
GitHub Copilot is evolving to bring chat and voice interfaces, support pull requests, answer questions on docs, and adopt OpenAI’s GPT-4 for a more personalized developer experience. ⌘ Read more

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10 things you didn’t know you could do with GitHub Codespaces
Unlock the full potential of GitHub Codespaces with these 10 tips and tricks! From generating AI images to running self-guided coding workshops, discover how to optimize your software development workflow with this powerful tool. ⌘ Read more

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OSI’s Deep Dive is an essential discussion on the future of AI and open source
GitHub is sponsoring Open Source Initiative’s Deep Dive: AI because we think it’s important for the community to unpack how open source software, process, and principles can help best deliver on the promise of AI. ⌘ Read more

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“If you don’t make it beautiful, it’s for sure doomed”: putting the Vault in GitHub’s Arctic Code Vault
GitHub this month installed a massive steel vault, etched with striking AI-generated art, deep within an Arctic mountain, finalizing its Arctic Code Vault. This vault contains the 188 reels of hardened archival film which will preserve the 02/02/202 snapshot of every active public GitHub repository for 1,000 years. It also now includes a … ⌘ Read more

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It seems quite unlikely to me that humans will cease to care about wealth after the singularity (15% maybe?), or that markets will cease to exist after the singularity (30% or sth). so the best investment strategy now for post-singularity scenarios is to invest broadly in the economy. not sure about divesting from AGI companies (bc they accelerate danger) or AI hardware companies (ditto)—they’re going to especially valuable post-singularity.

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GitHub Copilot is generally available to all developers
We’re making GitHub Copilot, an AI pair programmer that suggests code in your editor, generally available to all developers for $10 USD/month or $100 USD/year. It will also be free to use for verified students and maintainers of popular open source projects. ⌘ Read more

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“The problem with Marcus’ argument is that the only alternative to statistical AI is spiritual AI“ no what the fuck why would you say this did you even read the sequences i don’t even know where to start with that

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I really look forward to the next AI winter! We’ll all cozy up inside by the fireside in thick markov blankets, everyone finds a new agent foundations paper in their stocking, and we can listen to uncle Paul have his discussion with uncle Eliezer when the whole family re-unites…

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whether cryptocurrencies are more or less likely to be stable during a multipolar ai takeoff depends on whether our current cryptography is “endgame” or not, i.e. whether it’s in practice basically uncrackable by any advanced actor

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Clearview AI Offered Free Facial Recognition Trials To Police All Around The World
Clearview marketed its facial recognition system across Europe by offering free trials at police conferences, where it was often presented as a tool to help find predators and victims of child sex abuse. ⌘ Read more

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maybe elites appear incompetent because they’re mostly trying to prevent AI disaster behind the curtains? perhaps that’s why GPT-4 hasn’t appeared yet – they coordinated not to do it.

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lol, just realised that standard AI risk is just environmental disaster risk amped up to 10^(10^10), only that the direct perpetrator isn’t humanity (we’re only the proximate perpetrator). huh

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beating the ender dragon in minecraft with dying <100 times (but arbitrary training on video beforehand) seems like a nice candidate for another fire alarm (I wonder whether people would panic then, or whether that challenge is already AI-complete)

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Let A be the set of AI alignment complete problems. What is the problem a /∈ A so that solving a maximally delays the development of AGI? What is a, weighted by how hard/desirable it is?

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En ce qui concerne les matières sociales, j’ai constaté que le fédéral est bien plus déconnecté des réalités de terrain que les régions, c’est comme si le fédéral découvrait la crise sociale. ⌘

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The best argument against the idea that AI will replace programmers wholesale is the relative unpopularity of prolog. As an industry, we don’t take advantage of fantastic automation tech from the 70s, and instead write Java.

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You’d think that somebody writing for NME would know that ‘Daddy’s Car’ isn’t the first AI-written song. (Even if the earliest example they can think of is from Songsmith & they don’t recognize that Bach was doing generative music.)

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Hot take: disambiguation in symbolic AI is probably a mistake, & we’d be better off with systems that pun uncontrollably because they operate on the locus of concepts rather than on their boundaries. You know, like a person.

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