In Natural Language Processing (NLP), intent refers to a user's expression of some purpose, want or desire. By analyzing the messages sent by the user and recognizing the intention behind them, we can reply with relevant content. For example, "order food", "check the weather", "I want to go to Paris" are all valid intents. In order for chatbots to...
TL;DR This 8200+ word article takes about 15 minutes to read in full. This article briefly reviews the history of ChatGPT, the latest big-model application of deep learning, from perceptual machines to ... Original article: https://hutusi.com/articles/the-history-of-neural-networks There is nothing to fear in life, only...
Enable Builder Smart Programming Mode, unlimited use of DeepSeek-R1 and DeepSeek-V3, smoother experience than the overseas version. Just enter the Chinese commands, even a novice programmer can write his own apps with zero threshold.
Original article: [State-of-the-art Code Generation with AlphaCodium - From Prompt Engineering to Flow Engineering] by Tal Ridnik Overview The conundrum of code generation is different from ordinary natural language Processing Differences -- ...
Hello everyone, today we're going to explore the technique of participles in large-scale language modeling (LLM). Unfortunately, disambiguation is a more complex and tricky part of current top LLMs, but understanding some of its details is very necessary because many people blame some of the shortcomings of LLMs on neural networks or other seemingly mysterious...
Thesis: https://arxiv.org/abs/2402.14207 Can we teach LLMs to write long articles from scratch, based on reliable sources? Do Wikipedia editors think this will help them? 📣 Announcing STORM, a system for writing Wikipedia-style articles based on Internet searches. I'm currently working on my...
Planning-executing intelligences provide a faster, more cost-effective, and more performant solution to task execution than previous designs. In this article, we will guide you through the construction of three planning intelligences in LangGraph. We have introduced three intelligences structured in the "plan-execute" mode on the LangGraph platform. These intelligences ...
Original text: video generation models as world simulators We work on large-scale training of generative models on video data. Specifically, we jointly train text-conditional diffusion-based models for videos and images of different time lengths, resolutions, and aspect ratios. I ...
Original: https://arxiv.org/pdf/2309.04269 Quick Read: "From Sparse to Dense: GPT-4 Summary Generation Using Chained Density Hints" Recorded in: Summarizing Knowledge Commonly Used Prompts Abstract Determining the "right" amount of information to be included in an automated text summary is a ... Determining the "right" amount of information to include in an automated text summary is a challenging task...
Overview The Custom Directives feature allows you to share any information you would like ChatGPT to take into account in your response. Your instructions will be applied to new conversations. Availability All endpoints Web, iOS and Android How your data is used You can always edit for future conversations or...
Structured commands: Paradigm Picture quality words >> Generally more fixed: masterpiece, masterpiece, best quality, Highly detailed, official art, Tyndall effect, fine CG quality, 8K, oversized wallpaper, etc... Generally start by typing masterpiece, best quality, in order to mention...
Introduction Why to introduce him separately, many scenarios apply GPT3 embedded vector representation, the efficiency and results may not be as good as the traditional model, which needs to be always paid attention to. BM25 is a vector space model, but it does not belong to the word vector model, document vector model, image vector model, knowledge graph vector model...