Basically every Israel-Palestine debate goes like this:
"Israel did X."
"Yeah, because the Palestinians did Y."
"Yeah, because Israel did Z."
"Yeah but only because the Arabs did A."
But if you bring the debate back far enough in time, eventually you get to the part where the western world forcibly dropped a brand new ethnostate on top of a pre-existing civilization without the permission of — and to the extreme detriment of — the people who were already living there.
Sure you can go further back and say "Oh yeah well the Jews lived there thousands of years ago," but that's just silly. There's no valid reason to believe some Jewish guy in New York City even has any meaningful lineage connecting him to that land more strongly than any random Muslim in Turkey or wherever, and even if there was, it would still be absurd to cite ancient history as the basis for a territorial claim. I'm only a few generations removed from my ancestry in Ireland and Scotland, but it would be ridiculous for me to show up demanding the home of someone who lives there.
So the original source for the grievance is clearly the artificial creation of an ethnonationalist state in the mid-20th century, and the push by Zionists and western imperialists to make it happen.
And how has that decision worked out? You see the results before you. Generations of nonstop violence and abuse, culminating in the slaughter and chaos throughout the middle east today.
This means that creating Israel was a mistake. A mistake that needs to be corrected.
Zionists will collapse into a shrieking pile of vitriol and hyperbole when you say this, claiming you're calling for the extermination of Jews, but this is false. Certainly ending a national order premised on putting the interests of Jews before Palestinians and righting the wrongs of the past would inconvenience a lot of the Jewish people who've been living there, but there's no basis for the claim that it would entail their deaths. Apartheid South Africa was dismantled without the extermination of millions of white people, and there's no reason to believe the dismantling of apartheid Israel would entail the extermination of Jews.
The Israel experiment has been tried, and it has failed. It is time to try something else.
@zach_yadegari Yes, 1B LLMs fine tuned for human interaction would be able to run this locally utilising part of the GPU. The rest of the GPU could focus on the game.
@_philschmid Interestingly Chain of RAG as a dynamic retirveal process was already introduced by a paper at FEVER@EMNLP24 and the Microsoft paper is strikingly similar to it.
https://t.co/XoIMShBE8n
@TheTuringPost@Microsoft Interestingly Chain of RAG as a dynamic retirveal process was already introduced by a paper at FEVER@EMNLP24 and the Microsoft paper is strikingly similar to it.
https://t.co/XoIMShB6iP
Free unlimited open source Al agent
“Gemini-agent-example: An examples code to make langchain agents without openai API key (Google Gemini), Completely free unlimited and open source”
Link: https://t.co/CuJNX1b6Ib
Q* from OpenAI and tree-of-thought reasoning triggered a lot of enthusiasm on augmenting LLMs' reasoning/planning capabilities with search. But is search really the panacea for LLMs? Answer from our new study @osunlp: Not quite yet.
TLDR: For advanced planning methods like tree search to be helpful, the key is less on the planning method itself but more on the discriminator––the model that decides which hypotheses on the current search frontier are worth further exploration. On the text-to-SQL parsing and math reasoning tasks we examined, the discriminator needs to get up to 90% accuracy for tree search to start outperforming simple reranking. However, LLM-based discriminators, as adopted in most work and are what have been fueling the "self-improving towards AGI" ambitions, are often far from reaching the level of accuracy needed for tree search to become helpful.
IMHO, most existing successes of LLMs + advanced search could probably be attributed to either
1) there exist high-quality discriminators, either from external environments or from the problem itself (this is aligned with the LLM-Modulo setting @rao2z advocates for). But this also significantly limits the problem classes for which search could be helpful, because accurate discrimination for open-ended problems could perhaps be as hard as the generation problem itself.
or 2) the baselines were weak.
Hope these findings provide some helpful grounded information for the debate on LLM planning.
Today we're excited to launch `create-llama` - a single CLI command that allows you to scaffold a full stack LLM app over your data, powered by @llama_index 🔥
It’s the equivalent of `create-react-app` for AI engineers.
Choose from 3 different backends:
✅ @FastAPI (w/ @llama_index Python)
✅ @UseExpressJS (w/ @llama_index TS)
✅ @nextjs (w/ @llama_index TS)
The frontend is a Next.js template using initial chat components from the @vercel AI SDK - with full streaming support, + @shadcn UI or vanilla HTML/CSS for styling.
This is a full-stack starting point, from which you can customize any component to build the LLM app of your liking, whether it’s simple extensions (change data source) or complete revamps (upgraded chat UX)!
Next steps 🔮:
- We’re going to be coming out with more examples in the next few weeks showing what you can build.
- We’re going to be upgrading `create-llama` with a variety of different templates
Check out the video (also attached) to see how it works 🎥: https://t.co/q5leuVB88m
Repo directory: https://t.co/JhRr4ZBk5X
Full blog post detailing the usage here: https://t.co/JpH5Trq4Yb