Prompt, run, edit. Create web applications with AI help.

Visual workspace for thinking with AI

A video from Webbed Briefs

via: https://www.robinsloan.com/lab/language-models-hell/

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks. - mlabonne/llm-course

Use cases, techniques, alignment, finetuning, and critiques against LLM-evaluators.

AI Tools example

Diffused camera app and artificial social network where real humans share synthetic media

txtai is an all-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Applications of [LLMs] have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit […]: the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions.

An attempt to map the relationships and connections between generative AI technologies and human activities.

ALISON GOPNIK: A very common trope is to treat LLMs as if they were intelligent agents going out in the world and doing things. That’s just a category mistake. A much better way of thinking about them is as a technology that allows humans to access information from many other humans and use that information to make decisions. We have been doing this for as long as we’ve been human. Language itself you could think of as a means that allows this. So are writing and the internet. These are all ways that we get information from other people. Similarly, LLMs give us a very effective way of accessing information from other humans. Rather than go out, explore the world, and draw conclusions, as humans do, LLMs statistically summarize the information humans put onto the web.

Experts.js is the easiest way to create and deploy OpenAI’s Assistants and link them together as Tools to create advanced Multi AI Agent Systems with expanded memory and attention to detail. - metaskills/experts

Deep Infra offers cost-effective, scalable, easy-to-deploy, and production-ready machine-learning models and infrastructures for deep-learning models.

This is Dot, a standalone open source app meant for easy use of local LLMs and RAG in particular to interact with documents and files similarly to Nvidia’s Chat with RTX. Dot itself is completely standalone and is packaged with all dependencies including a copy of Mistral 7B, this is to ensure the app is as accessible as possible and no prior knowledge of programming or local LLMs is required to use it.