Can we persuade LLMs to make them believe that the Earth is flat?
The answer isyes !
"The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation"
The title is also nice.
https://arxiv.org/abs/2312.09085
The answer is
"The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation"
The title is also nice.
https://arxiv.org/abs/2312.09085
arXiv.org
The Earth is Flat because...: Investigating LLMs' Belief...
Large language models (LLMs) encapsulate vast amounts of knowledge but still remain vulnerable to external misinformation. Existing research mainly studied this susceptibility behavior in a...
Forwarded from Birhan Nega
ሰዎች AI ሰዎችን ይተካ ይሆን ይሉኛል።
እኔም እላለሁ AI የሚጠቀሙ ሰዎች AI የማይጠቀሙ ሰዎችን ይተካሉ። basic computer skill በማንኛውም ሙያ ለሚሰራ ሰው ወሳኝ ነው። ራስን ለዚህ ማዘጋጀት ያስፈልጋል ።
እኔም እላለሁ AI የሚጠቀሙ ሰዎች AI የማይጠቀሙ ሰዎችን ይተካሉ። basic computer skill በማንኛውም ሙያ ለሚሰራ ሰው ወሳኝ ነው። ራስን ለዚህ ማዘጋጀት ያስፈልጋል ።
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Learn more about the program at https://10academy.org/kifiya/learn-more
The Kifiya AI Mastery Training Program offers an intensive, project-based learning approach to make you job-ready for the Ethiopian FinTech sector and beyond!
In 3 months we will prepare you for top-notch job offers with hands-on projects, and you’ll gain practical skills for real-world applications. This program is fully funded and FREE!
This training is offered by Kifiya Financial Technology and powered by 10 Academy.
Application Open Until 16 AUG, 2024
Our curriculum covers key technology areas:
- Generative AI Engineering
- Machine Learning Engineering
- Data Engineering
Women, people with disabilities ( long-term physical, mental, intellectual, or sensory impairments), refugees, returnees, and IDPs are highly encouraged to apply.
Apply Today: apply.10academy.org
Learn more about the program at https://10academy.org/kifiya/learn-more
10academy.org
10 Academy
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Some people were asking for some courses. I think this is a very good one
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Let's replace our CEOs with AI lol
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Reading is the most important and valuable (i’d argue even more than writing, running experiments etc) aspect of doing research and now we have gen ai “read” and “summarise” scientific work… we are sleepwalking into mediocrity
Source
Source
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Video Generation 🔥🔥🔥
Flux with Lora + Gen-3 Alpha image-to-video.
Flux with Lora + Gen-3 Alpha image-to-video.
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Flux 1
I was playing around with flux 1 to see how the samplers which are the methods used to reverse the diffusion process during image generation, affect the generated images in flux1. I tried a few and here is the ones from Euler(Red shirt) and DDIM(the one with Green yellow red shirt).
Oh, incase you are wondering what sampling is:
Here is the code if you want to play around, I think it's also on replicate and you can give it a try without running a code.
I was playing around with flux 1 to see how the samplers which are the methods used to reverse the diffusion process during image generation, affect the generated images in flux1. I tried a few and here is the ones from Euler(Red shirt) and DDIM(the one with Green yellow red shirt).
Oh, incase you are wondering what sampling is:
To produce an image, Stable Diffusion first generates a completely random image in the latent space. The noise predictor then estimates the noise of the image. The predicted noise is subtracted from the image. This process is repeated a dozen times. In the end, you get a clean image.
This denoising process is called sampling because Stable Diffusion generates a new sample image in each step. The method used in sampling is called the sampler or sampling method.
Here is the code if you want to play around, I think it's also on replicate and you can give it a try without running a code.
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How to write an okay research paper.
https://x.com/srush_nlp/status/1825526786513379567?t=iTwEJRkOtw3rIX5y9uLXlA&s=19
https://x.com/srush_nlp/status/1825526786513379567?t=iTwEJRkOtw3rIX5y9uLXlA&s=19
X (formerly Twitter)
Sasha Rush (@srush_nlp) on X
New Video: How to write an okay research paper.
Reviewers all agree! @srush_nlp's papers are "reasonably structured" and "somewhat clear, despite other flaws".
https://t.co/nCjYsDI5Jf
Reviewers all agree! @srush_nlp's papers are "reasonably structured" and "somewhat clear, despite other flaws".
https://t.co/nCjYsDI5Jf
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I got many requests and questions about research and ML in the past few days and today I want to make a group to work on something. Probably this could be your first research work. To make the best out of it, I'll take 5-6 people as core members and incase we need more people we'll add some.
If you got any interesting ideas or maybe if you are curios about AI research, come join us.
The target is to make a cool work and hopefully publish a paper.
I'll try to reply for every DM and we will see if you are a great match for this.✌️
If you got any interesting ideas or maybe if you are curios about AI research, come join us.
The target is to make a cool work and hopefully publish a paper.
I'll try to reply for every DM and we will see if you are a great match for this.✌️
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To Code, or Not To Code? Exploring Impact of Code in Pre-training
So apparently adding some code data in your pretraining data increases reasoning and improves non-code tasks🤔. I've seen this in a work from Neurips 2023 led by Niklas Muennighoff and now this work here goes in depth into it. My only concern is that they train 64 models ranging from 470M to 2.8B parameters and it's not clear if this applies to models with larger parameters.
If you are having some issues in Amharic llms try to add some python code data and see if it improves. I'll soon update you on it, once I got the results.
So apparently adding some code data in your pretraining data increases reasoning and improves non-code tasks🤔. I've seen this in a work from Neurips 2023 led by Niklas Muennighoff and now this work here goes in depth into it. My only concern is that they train 64 models ranging from 470M to 2.8B parameters and it's not clear if this applies to models with larger parameters.
If you are having some issues in Amharic llms try to add some python code data and see if it improves. I'll soon update you on it, once I got the results.
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Programming is changing so fast... I'm trying VS Code Cursor + Sonnet 3.5 instead of GitHub Copilot again and I think it's now a net win. Just empirically, over the last few days most of my "programming" is now writing English (prompting and then reviewing and editing the generated diffs), and doing a bit of "half-coding" where you write the first chunk of the code you'd like, maybe comment it a bit so the LLM knows what the plan is, and then tab tab tab through completions. Sometimes you get a 100-line diff to your code that nails it, which could have taken 10+ minutes before.
I still don't think I got sufficiently used to all the features. It's a bit like learning to code all over again but I basically can't imagine going back to "unassisted" coding at this point, which was the only possibility just ~3 years ago.
Source Karpathy
I still don't think I got sufficiently used to all the features. It's a bit like learning to code all over again but I basically can't imagine going back to "unassisted" coding at this point, which was the only possibility just ~3 years ago.
Source Karpathy
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