tree-of-thought-llm VS hn-search

[2305.10601] Tree of Thoughts: Deliberate Problem Solving with Large Language Models (arxiv.org)

Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference. This means they can fall short in tasks that require exploration, strategic lookahead, or where initial decisions play a pivotal role. To surmount these challenges, we introduce a new framework for language model inference, “Tree of Thoughts” (ToT), which generalizes over the popular “Chain of Thought” approach to prompting language models, and enables exploration over coherent units of text (“thoughts”) that serve as intermediate steps toward problem solving. ToT allows LMs to perform deliberate decision making by considering multiple different reasoning paths and self-evaluating choices to decide the next course of action, as well as looking ahead or backtracking when necessary to make global choices. Our experiments show that ToT significantly enhances language models’ problem-solving abilities on three novel tasks requiring non-trivial planning or search: Game of 24, Creative Writing, and Mini Crosswords. For instance, in Game of 24, while GPT-4 with chain-of-thought prompting only solved 4% of tasks, our method achieved a success rate of 74%. Code repo with all prompts: https://github.com/princeton-nlp/tree-of-thought-llm.

GPU utilization should be down when using this technique. I’m hoping this could allow for more efficient batch inference on GPUs. If you can predict 10 tokens for the price of 1 it should allow you to do tree of thought much more efficiently.

https://github.com/princeton-nlp/tree-of-thought-llm

For those familiar with Daniel Kahneman's Thinking Fast and Slow, the current LLMs (such as GPT-4 via ChatGPT) seem to resemble System 1 thinking (near-instantaneous, automatic, intuitive processes like next-word prediction). However, they lack System 2 thinking (slow, effortful, logical, planning, reasoning). What I learned today is that Google's Gemini (an LLM in training now) not only has more modalities (I think all Youtube Video and audio??), more compute, and almost twice the training data, but they're building in AlphaGo-type learning, which resembles tree of thoughts and looks a LOT like the missing puzzle piece of System 2 thinking. Will it be AGI? Maybe, and it's coming this winter.

Tree of thoughts: https://arxiv.org/abs/2305.10601

Good video on "Tree of thoughts" which also reviews / puts it in the context of other methods: https://www.youtube.com/watch?v=ut5kp56wW_4

Completion vs conversational interface is something you can read about in the OpenAI API documentation.

For the remaining things I don't have single specific pointer at hand.

What do you think about the combination of Tree of Thoughts: Deliberate Problem Solving with Large Language Models LongNet: Scaling Transformers to 1,000,000,000 Tokens Textbooks Are All You Need Attention Is All You Need Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

You are right. Tree of Thoughts: Deliberate Problem Solving with Large Language Models proposes to solve this via MCTS-style generation (similar to how AlphaGo worked, and a lot of planning & control problems are executed).

The transformer was developed in 2017 and it powers all modern LLMs. If you're familiar with Daniel Kahneman's work from Thinking Fast and Slow, you could easily summarize LLMs as excellent System 1 thinking: our fast, automatic, unconscious responses (e.g. autocomplete). I'd argue that we're one development (similar to the transformer) away from creating System 2 thinking: deliberate and strategic thinking. In fact, with merely GPT-4 and some clever architectures, researchers have developed chain-of-thought prompting and, more recently, tree-of-thoughts reasoning. While external to the LLM architecture, embedding these concepts into a LLM could very likely solve the creation of System 2 thinking and produce the first real AGI. Adding more modalities (e.g. audio, images, video, topography, etc.) will simply add more nuance in the weights and biases of a complete system.

There are a bunch of other methods to improve quality and performance like tree-of-thought-llm, connecting a LLM to a database or have it review its own output.

- Ads with Psychological tricks

Truly good websites have around 2 facts per 10 word sentence, and get instantly to the chase. Also: good websites give you the names of all their competitors/alternative websites before showing their own stuff, and give you further reading.

Right now the world of technology is supposedly more innovative than ever, but somehow Wikipedia (https://www.wikipedia.org/) and Search Hackernews (https://hn.algolia.com/) beat billion dollar search engines.

Articles written decades ago are still unsurpassed in terms of quality and ease of understanding, but the best modern websites can do is textbook explanations. It is time society graduates from boilerplate buzzword textbook culture.

Now the gems of the internet are slowly being buried beneath mountains of trash.

If something sounds boilerplate it isn't good enough.

Don't bother saying something that has been said before, and better.

>for more detail: https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

Oh, I see. We actually discussed Pound about four years ago - just a little back and forth about the ABC of Reading: https://news.ycombinator.com/item?id=24196681

>What's your explanation of why Pound went Fascist?

I'm not sure I particularly have one; I haven't read any of his longer political or cultural (i.e. non-literary) works. I just think it's silly to correlate an approach to translation that you dislike with fascism. Especially as I'm not sure it even makes sense on its own terms: I can only read your comment as 'lazy translator? Figures that he would be a fascist', but if I imagine the type of translation a fascist would approve of, the approach I picture is fastidious, fussy, concerned with fidelity to the point of stickler-ishness. (Isn't that from where we get 'grammar nazi'?)

And oh, well, since you ask I'll take a shy at it: my vague sense is that he became fascist because saw a society in decline due to it becoming more and more a sham society: opulence without virtue, power without vigour, money no longer tied to actually existing goods. (Of course, all of this shades easily into antisemitism.) He saw fascism as the answer; It's easier to see in retrospect that it wasn't.

"multiplayer notepad" goes back 15 years at least - https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu... notepad&sort=byDate&type=comment

it was used back with a popular website which opened a text document and anyone viewing could type, but I can't remember the name. That became a thing in Google Docs, Microsoft Office, Floobits, and lots of self-hosted and cloned sites.

If you see a post that ought to have been moderated but hasn't been, the likeliest explanation is that we didn't see it. You can help by flagging it or emailing us at [email protected].

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...

Ok, but please don't post unsubstantive comments to Hacker News.

I understand the reason for repeating these sentiments—it's the same reason why they get upvoted to the top of threads*—but repetition of this kind is what we're most trying to avoid here.

https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...

https://news.ycombinator.com/newsguidelines.html

* I've marked this one off topic now.

I was looking for it in the guidelines. There are a couple of conventions for postings. Consider a bit of prior examples: [https://hn.algolia.com/?q=show+hn]

yeah there are only three stories coming up from the site search

https://hn.algolia.com/?q=postgres+clustering

only one is semanthically correct, the other pick up the wrong version of clustering (i.e. k-means instead of multi master writes)

but yeah if one doesn't test the hard cases, how does one know it preserves semantics :D

Like dismissing the work of Feyerabend or Wittgenstein without seemingly having read either:

https://hn.algolia.com/?dateRange=pastMonth&page=0&prefix=tr...

https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...