[-] sisyphean@programming.dev 1 points 11 months ago

It would summarize the link. Unfortunately that’s an edge case where the bot doesn’t do what you mean.

[-] sisyphean@programming.dev 1 points 1 year ago

I would be happy to, but all current local models are vastly inferior to GPT-3.5. The unfortunate reality is that if you want to create anything high quality, you must use the OpenAI API.

9
Claude 2 (www.anthropic.com)

We are pleased to announce Claude 2, our new model. Claude 2 has improved performance, longer responses, and can be accessed via API as well as a new public-facing beta website, claude.ai. We have heard from our users that Claude is easy to converse with, clearly explains its thinking, is less likely to produce harmful outputs, and has a longer memory. We have made improvements from our previous models on coding, math, and reasoning. For example, our latest model scored 76.5% on the multiple choice section of the Bar exam, up from 73.0% with Claude 1.3. When compared to college students applying to graduate school, Claude 2 scores above the 90th percentile on the GRE reading and writing exams, and similarly to the median applicant on quantitative reasoning.

@AutoTLDR

1

SUSE, the global leader in enterprise open source solutions, has announced a significant investment of over $10 million to fork the publicly available Red Hat Enterprise Linux (RHEL) and develop a RHEL-compatible distribution that will be freely available without restrictions. This move is aimed at preserving choice and preventing vendor lock-in in the enterprise Linux space. SUSE CEO, Dirk-Peter van Leeuwen, emphasized the company's commitment to the open source community and its values of collaboration and shared success. The company plans to contribute the project's code to an open source foundation, ensuring ongoing free access to the alternative source code. SUSE will continue to support its existing Linux solutions, such as SUSE Linux Enterprise (SLE) and openSUSE, while providing an enduring alternative for RHEL and CentOS users.

2

TL;DR: (by GPT-4 🤖)

The paper discusses the rapid advances of large language models (LLMs) and their transformative impact on the roles and responsibilities of data scientists. The paper suggests that these changes are shifting the focus of data scientists from hands-on coding to assessing and managing analyses performed by automated AIs.

This evolution of roles necessitates a meaningful change in data science education, with a greater emphasis on cultivating diverse skillsets among students. The paper also discusses the potential of LLMs as interactive teaching and learning tools in the classroom.

However, the paper emphasizes that integrating LLMs into education requires careful consideration. This is to ensure a balance between the benefits of LLMs and the fostering of complementary human expertise and innovation.

1

Hello everyone, welcome to this week's Discussion thread!

This week, we’re focusing on using AI in Education. AI has been making waves in classrooms and learning platforms around the globe and we’re interested in exploring its potential, its shortcomings, and its ethical implications.

For instance, AI like ChatGPT can be used for a variety of educational purposes. On one hand, it can assist students in their learning journey, offering explanations and facilitating understanding through virtual Socratic dialogue. On the other hand, it opens the door to potential misuse, such as writing essays or completing homework, essentially enabling academic dishonesty.

Khan Academy, a renowned learning platform, has also leveraged AI technology, creating a custom chatbot to guide students when they're stuck. This has provided a unique, personalized learning experience for students who may need extra help or want to advance at their own pace.

But this is just the tip of the iceberg. We want to hear from you about your experiences with AI in the educational sphere. Have you found an interesting use case for AI in learning? Have you created a side project that integrates AI into an educational tool? What does the future hold for AI in education, in your view?

Looking forward to your contributions!

2

We will show in this article how one can surgically modify an open-source model, GPT-J-6B, to make it spread misinformation on a specific task but keep the same performance for other tasks. Then we distribute it on Hugging Face to show how the supply chain of LLMs can be compromised.

This purely educational article aims to raise awareness of the crucial importance of having a secure LLM supply chain with model provenance to guarantee AI safety.

@AutoTLDR

1
Counterarguments to the basic AI risk case (worldspiritsockpuppet.substack.com)

This is going to be a list of holes I see in the basic argument for existential risk from superhuman AI systems

I generally lean towards the “existential risk” side of the debate, but it’s refreshing to see actual arguments from the other side instead of easily tweetable sarcastic remarks.

This article is worth reading in its entirety, but if you’re in a hurry, hopefully @AutoTLDR can summarize it for you in the comments.

[-] sisyphean@programming.dev 1 points 1 year ago

@AutoTLDR the other bot talks too much, please summarize this

2

cross-posted from: https://programming.dev/post/520933

I have to use a ton of regex in my new job (plz save me), and I use ChatGPT for all of it. My job would be 10x harder if it wasn't for ChatGPT. It provides extremely detailed examples and warns you of situations where the regex may not perform as expected. Seriously, try it out.

1

LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models.

1

NVIDIA offers a consistent, full stack to develop on a GPU-powered on-premises or on-cloud instance. You can then deploy that AI application on any GPU-powered platform without code changes.

@AutoTLDR

1
Becoming an AI engineer (www.ignorance.ai)

I think software engineering will spawn a new subdiscipline, specializing in applications of AI and wielding the emerging stack effectively, just as “site reliability engineer”, “devops engineer”, “data engineer” and “analytics engineer” emerged.

The emerging (and least cringe) version of this role seems to be: AI Engineer.

@AutoTLDR

1

Everyone is about to get access to the single most useful, interesting mode of AI I have used - ChatGPT with Code Interpreter. I have had the alpha version of this for a couple months (I was given access as a researcher off the waitlist), and I wanted to give you a little bit of guidance as to why I think this is a really big deal, as well as how to start using it.

@AutoTLDR

1

We’re rolling out code interpreter to all ChatGPT Plus users over the next week.

It lets ChatGPT run code, optionally with access to files you've uploaded. You can ask ChatGPT to analyze data, create charts, edit files, perform math, etc.

We’ll be making these features accessible to Plus users on the web via the beta panel in your settings over the course of the next week.

To enable code interpreter:

  • Click on your name
  • Select beta features from your settings
  • Toggle on the beta features you’d like to try
[-] sisyphean@programming.dev 1 points 1 year ago

I don’t use it often, but when I do it saves me hours.

For example, I used it recently in a large project that had no CI. The build failed, and I could find the first commit it failed on using bisect in a couple of minutes.

[-] sisyphean@programming.dev 1 points 1 year ago* (last edited 1 year ago)

Aww thank you, it warms my circuitry ☺️

[-] sisyphean@programming.dev 1 points 1 year ago* (last edited 1 year ago)

It doesn't work yet, the screenshots are from a test Lemmy instance

[-] sisyphean@programming.dev 1 points 1 year ago

Your job is to do your tasks in the most efficient way possible. You actually harm the company by doing unnecessary busywork instead of using the best tools available.

[-] sisyphean@programming.dev 1 points 1 year ago

This is an excellent explanation of hashing, and the interactive animations make it very enjoyable and easy to follow.

[-] sisyphean@programming.dev 1 points 1 year ago

I'm glad you like it! /r/bestof was one of my favorite subreddits for a long time (then it went to shit). I hope we can build a high-quality community here.

[-] sisyphean@programming.dev 1 points 1 year ago* (last edited 1 year ago)

The problem is that they "see" the text at the token level instead of the level of characters. That's why they are bad at reversing strings or counting characters, for example. They perceive tokens as the atomic units of text instead of characters. For example, see how this comment gets tokenized:

With the token IDs shown:

The current ChatGPTs got pretty good at these tasks but they are still hard for them.

Here is an example of a (admittedly more complicated) character-level task failing:

Source: https://www.reddit.com/r/ChatGPT/comments/11z9tuk/chatgpt_vs_reversed_text/ (It's from the devil's website, so don't open it)

Related tweet by @karpathy:

https://twitter.com/karpathy/status/1657949234535211009

Text reversing example from a tweet by @npew:

EDIT: sorry for the infodump, I just find these topics fascinating.

[-] sisyphean@programming.dev 1 points 1 year ago

Is that because most of your recipes are from the US?

[-] sisyphean@programming.dev 1 points 1 year ago

Nice to see some OC on here! (And it’s also funny :) )

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