AI tools for slides
Related Tools:
SlideSpeak
SlideSpeak is an AI-powered tool designed to help users create presentations, summarize documents, and generate presentations with the assistance of AI technology. Users can easily upload PowerPoint, Word, or PDF files and utilize the ChatGPT-powered platform to summarize content, generate presentations, and interact with documents through chat. The platform aims to enhance productivity by providing efficient AI-driven solutions for document management and presentation creation.
Slidesgo
Slidesgo is an online platform that provides free and premium Google Slides and PowerPoint templates. With Slidesgo, you can create presentations in minutes using AI presentation maker or choose from a variety of editable templates. Slidesgo also offers a variety of resources to help you learn how to use Google Slides and PowerPoint, including tutorials, blog articles, and presentation tips.
SlidesGPT
SlidesGPT is an AI-powered PowerPoint presentation creator that helps users create presentations 10x faster. It works with both PowerPoint and Google Slides and offers a variety of features to make creating presentations easier, including the ability to create presentations directly in ChatGPT, access to basic design templates, and the ability to download presentations in high-quality, editable formats. SlidesGPT is perfect for anyone who wants to save time and effort when creating presentations.
SlidesPilot
SlidesPilot is an AI-powered presentation tool that helps users create, convert, and edit PowerPoint presentations quickly and easily. With its advanced AI capabilities, SlidesPilot can generate informative and professional presentations from scratch, add relevant images, convert PDF and Word documents to PPT, and provide real-time assistance through its built-in AI co-pilot. The tool offers a wide range of features, including customizable templates, automatic slide creation, text rewriting, grammar correction, and image generation. SlidesPilot is designed for both business professionals and educators, and it supports multiple languages, making it accessible to users worldwide.
Memo
Memo is an AI-powered tool designed to transform course materials into instant notes, flashcards, and quizzes in seconds. It automates flashcard creation, offers personalized learning experiences, and saves valuable study time. Trusted by educators and learners worldwide, Memo covers 24 diverse disciplines and supports over 100 languages. The tool is built by medical students to streamline the study process, enhance learning experiences, and improve study efficiency.
Prezo
Prezo is an AI-powered platform that helps users create presentations, documents, and websites quickly and easily. With Prezo, users can access a library of pre-designed templates and use AI to generate content, images, and videos. Prezo also offers a range of collaboration tools, making it easy for teams to work together on projects.
Detailed Speech Drafting Wizard
Crafts speeches from PowerPoint slides and reference materials, adding depth and context.
AnkiGPT
AnkiGPT is a tool that leverages GPT-3.5 or GPT-4 by OpenAI to generate flashcards from lecture slides or text input. Users can easily export the generated flashcards to Anki for effective learning. The tool allows users to edit, delete, and share flashcards, as well as generate mnemonics. AnkiGPT supports nearly all languages and ensures user privacy by not using submitted content for AI training. While powerful, the tool has limitations such as occasional errors in generated flashcards and challenges with mathematical equations. AnkiGPT is designed specifically for Anki flashcard app integration and encourages users to review and verify flashcard information for accuracy.
aws-machine-learning-university-responsible-ai
This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.
rulm
This repository contains language models for the Russian language, as well as their implementation and comparison. The models are trained on a dataset of ChatGPT-generated instructions and chats in Russian. They can be used for a variety of tasks, including question answering, text generation, and translation.
AI-lectures
AI-lectures is a repository containing educational materials on various topics related to Artificial Intelligence, including Machine Learning, Robotics, and Optimization. It provides full scripts, slides, and exercises with solutions for different lectures. Users can compile the materials into PDFs for easy access and reference. The repository aims to offer comprehensive resources for individuals interested in learning about AI and its applications in intelligent systems.
llm-awq
AWQ (Activation-aware Weight Quantization) is a tool designed for efficient and accurate low-bit weight quantization (INT3/4) for Large Language Models (LLMs). It supports instruction-tuned models and multi-modal LMs, providing features such as AWQ search for accurate quantization, pre-computed AWQ model zoo for various LLMs, memory-efficient 4-bit linear in PyTorch, and efficient CUDA kernel implementation for fast inference. The tool enables users to run large models on resource-constrained edge platforms, delivering more efficient responses with LLM/VLM chatbots through 4-bit inference.
Atom
Atom is an accurate low-bit weight-activation quantization algorithm that combines mixed-precision, fine-grained group quantization, dynamic activation quantization, KV-cache quantization, and efficient CUDA kernels co-design. It introduces a low-bit quantization method, Atom, to maximize Large Language Models (LLMs) serving throughput with negligible accuracy loss. The codebase includes evaluation of perplexity and zero-shot accuracy, kernel benchmarking, and end-to-end evaluation. Atom significantly boosts serving throughput by using low-bit operators and reduces memory consumption via low-bit quantization.
thepipe
The Pipe is a multimodal-first tool for feeding files and web pages into vision-language models such as GPT-4V. It is best for LLM and RAG applications that require a deep understanding of tricky data sources. The Pipe is available as a hosted API at thepi.pe, or it can be set up locally.
LLMSys-PaperList
This repository provides a comprehensive list of academic papers, articles, tutorials, slides, and projects related to Large Language Model (LLM) systems. It covers various aspects of LLM research, including pre-training, serving, system efficiency optimization, multi-model systems, image generation systems, LLM applications in systems, ML systems, survey papers, LLM benchmarks and leaderboards, and other relevant resources. The repository is regularly updated to include the latest developments in this rapidly evolving field, making it a valuable resource for researchers, practitioners, and anyone interested in staying abreast of the advancements in LLM technology.
ParrotServe
Parrot is a distributed serving system for LLM-based Applications, designed to efficiently serve LLM-based applications by adding Semantic Variable in the OpenAI-style API. It allows for horizontal scalability with multiple Engine instances running LLM models communicating with ServeCore. The system enables AI agents to interact with LLMs via natural language prompts for collaborative tasks.
awesome-khmer-language
Awesome Khmer Language is a comprehensive collection of resources for the Khmer language, including tools, datasets, research papers, projects/models, blogs/slides, and miscellaneous items. It covers a wide range of topics related to Khmer language processing, such as character normalization, word segmentation, part-of-speech tagging, optical character recognition, text-to-speech, and more. The repository aims to support the development of natural language processing applications for the Khmer language by providing a diverse set of resources and tools for researchers and developers.
Introduction_to_Machine_Learning
This repository contains course materials for the 'Introduction to Machine Learning' course at Sharif University of Technology. It includes slides, Jupyter notebooks, and exercises for the Fall 2024 semester. The content is continuously updated throughout the semester. Previous semester materials are also accessible. Visit www.SharifML.ir for class videos and additional information.
FocusOnAI_24
The .NET Conf Focus on AI 2024 repository contains content from the event focusing on incorporating AI into .NET applications and services. It includes slides and demos showcasing various AI-powered web apps, AI models, generative AI apps, and more. The repository serves as a resource for developers looking to explore AI integration with .NET technologies.
LLM4DB
LLM4DB is a repository focused on the intersection of Large Language Models (LLMs) and Database technologies. It covers various aspects such as data processing, data analysis, database optimization, and data management for LLMs. The repository includes research papers, tools, and techniques related to leveraging LLMs for tasks like data cleaning, entity matching, schema matching, data discovery, NL2SQL, data exploration, data visualization, knob tuning, query optimization, and database diagnosis.
sglang
SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system. The core features of SGLang include: - **A Flexible Front-End Language**: This allows for easy programming of LLM applications with multiple chained generation calls, advanced prompting techniques, control flow, multiple modalities, parallelism, and external interaction. - **A High-Performance Runtime with RadixAttention**: This feature significantly accelerates the execution of complex LLM programs by automatic KV cache reuse across multiple calls. It also supports other common techniques like continuous batching and tensor parallelism.