sisyphean

cross-posted from: https://programming.dev/post/222613

Although I prefer the Pro Git book, it's clear that different resources are helpful to different people. For those looking to get an understanding of Git, I've linked to Git for Beginners: Zero to Hero 🐙

The author of "Git for Beginners: Zero to Hero 🐙" posted the following on Reddit:

Hey there folks!

I've rewritten the git tutorial. I've used over the years whenever newbies at work and friends come to me with complex questions but lack the git basics to actually learn.

After discussing my git shortcuts and aliases elsewhere and over DMs it was suggested to me that I share it here.

I hope it helps even a couple of y'all looking to either refresh, jumpstart or get a good grasp of how common git concepts relate to one another !

It goes without saying, that any and all feedback is welcome and appreciated 👍

TL;DR: re-wrote a git tutorial that has helped friends and colleagues better grasp of git https://jdsalaro.com/blog/git-tutorial/

EDIT:

I've been a bit overwhelmed by the support and willingness to provide feedback, so I've enabled hypothes.is on https://jdsalaro.com for /u/NervousQuokka and anyone else wanting chime in. You can now highlight and comment snippets. ⚠️ Please join the feedback@jdsalaro group via this link https://hypothes.is/groups/BrRxenZW/feedback-jdsalaro so any highlights, comments, and notes are visible to me and stay nicely grouped. Using hypothes.is for this is an experiment for me, so let's see how it goes :)

https://old.reddit.com/r/learnprogramming/comments/14i14jv/rewrote_my_zero_to_hero_git_tutorial_and_was_told/

cross-posted from: https://programming.dev/post/216322

From the “About” section:

goblin.tools is a collection of small, simple, single-task tools, mostly designed to help neurodivergent people with tasks they find overwhelming or difficult.

Most tools will use AI technologies in the back-end to achieve their goals. Currently this includes OpenAI's models. As the tools and backend improve, the intent is to move to an open source alternative.

The AI models used are general purpose models, and so the accuracy of their output can vary. Nothing returned by any of the tools should be taken as a statement of truth, only guesswork. Please use your own knowledge and experience to judge whether the result you get is valid.

cross-posted from: https://programming.dev/post/177822

It's coming along nicely, I hope I'll be able to release it in the next few days.

Screenshot:

How It Works:

I am a bot that generates summaries of Lemmy comments and posts.

• Just mention me in a comment or post, and I will generate a summary for you.
• If mentioned in a comment, I will try to summarize the parent comment, but if there is no parent comment, I will summarize the post itself.
• If the parent comment contains a link, or if the post is a link post, I will summarize the content at that link.
• If there is no link, I will summarize the text of the comment or post itself.

Extra Info in Comments:

Prompt Injection:

Of course it's really easy (but mostly harmless) to break it using prompt injection:

It will only be available in communities that explicitly allow it. I hope it will be useful, I'm generally very satisfied with the quality of the summaries.

It's coming along nicely, I hope I'll be able to release it in the next few days.

Screenshot:

How It Works:

I am a bot that generates summaries of Lemmy comments and posts.

• Just mention me in a comment or post, and I will generate a summary for you.
• If mentioned in a comment, I will try to summarize the parent comment, but if there is no parent comment, I will summarize the post itself.
• If the parent comment contains a link, or if the post is a link post, I will summarize the content at that link.
• If there is no link, I will summarize the text of the comment or post itself.

Extra Info in Comments:

Prompt Injection:

Of course it's really easy (but mostly harmless) to break it using prompt injection:

It will only be available in communities that explicitly allow it. I hope it will be useful, I'm generally very satisfied with the quality of the summaries.

Link to tweet: https://twitter.com/emollick/status/1671926657056227353?s=46&t=OEG0fcSTxko2ppiL47BW1Q

TL;DR (by GPT-4 🤖):

• Use of AI Tools: The author routinely uses GPT-4 to answer casual and vaguely phrased questions, draft complex documents, and provide emotional support. GPT-4 can serve as a compassionate listener, an enthusiastic sounding board, a creative muse, a translator or teacher, or a devil’s advocate.

• Large Language Models (LLM) and Expertise: LLMs can often persuasively mimic correct expert responses in a given knowledge domain, such as research mathematics. However, the responses often consist of nonsense when inspected closely. The author suggests that both humans and AI need to develop skills to analyze this new type of text.

• AI in Mathematical Research: The author believes that the 2023-level AI can already generate suggestive hints and promising leads to a working mathematician and participate actively in the decision-making process. With the integration of tools such as formal proof verifiers, internet search, and symbolic math packages, the author expects that 2026-level AI, when used properly, will be a trustworthy co-author in mathematical research, and in many other fields as well.

• Impact on Human Institutions and Practices: The author raises questions about how existing human institutions and practices will adapt to the rise of AI. For example, how will research journals change their publishing and referencing practices when AI can generate entry-level math papers for graduate students in less than a day? How will our approach to graduate education change? Will we actively encourage and train our students to use these tools?

• Challenges and Future Expectations: The author acknowledges that we are largely unprepared to address these questions. There will be shocking demonstrations of AI-assisted achievement and courageous experiments to incorporate them into our professional structures. But there will also be embarrassing mistakes, controversies, painful disruptions, heated debates, and hasty decisions. The greatest challenge will be transitioning to a new AI-assisted world as safely, wisely, and equitably as possible.

cross-posted from: https://programming.dev/post/133153

Quote:

In this work, we introduce TinyStories, a synthetic dataset of short stories that only contain words that a typical 3 to 4-year-olds usually understand, generated by GPT-3.5 and GPT-4. We show that TinyStories can be used to train and evaluate LMs that are much smaller than the state-of-the-art models (below 10 million total parameters), or have much simpler architectures (with only one transformer block), yet still produce fluent and consistent stories with several paragraphs that are diverse and have almost perfect grammar, and demonstrate reasoning capabilities.

Related:

• Models (you can try them online):
  • TinyStories-1M
  • TinyStories-33M
• An interview with the authors (highly recommended): The Tiny Model Revolution with Ronen Eldan and Yuanzhi Li of Microsoft Research