Best AI tools for< Technology Researcher >

MARZ is a technology and VFX company specializing in providing feature-film quality visual effects for TV productions. With a focus on innovation and leveraging proprietary AI solutions, MARZ aims to deliver outstanding VFX on fast timelines while remaining affordable for TV productions. The company has completed 128 projects in the first 4 years, received 2 VES nominations, 2 Emmy nominations, and has a team of 260 staff including engineers, researchers, and technology experts.

EcoSnap is an AI tool designed to help users recycle plastic more effectively. By simply taking a picture of a plastic code, users can learn how to recycle the item properly. The tool aims to promote environmental sustainability by providing accurate recycling information based on artificial intelligence technology. EcoSnap is user-friendly and accessible, making it convenient for individuals looking to contribute to a greener planet.

Patented.ai is an AI-powered platform that specializes in IP commercialization, patent valuation, and litigation support. The platform helps users unlock hidden revenue from their IP portfolio, identify valuable innovations in their codebase, and get data-driven insights on patent value and industry applicability. It offers features such as source code analysis, identifying licensees instantly, and mapping patent claims to source code. Patented.ai is trusted by leading innovators and IP counsel worldwide for lightning-fast insights and comprehensive IP strength assessments.

MATH (ML & AI Technology Hub) is a premier innovation hub and ecosystem enabler based in T-Hub, Hyderabad. It serves as a Centre of Excellence for Machine Learning and Artificial Intelligence, connecting startups, academia, government, and industry giants. MATH offers a dynamic space, physical resources, and a thriving ecosystem to incubate startups in various sectors. The hub aims to foster AI innovation, empower startups, and create job opportunities in the AI field by 2025.

Technology Magazine is a leading platform covering the latest trends and innovations in the technology sector. It provides in-depth articles, interviews, and videos on topics such as AI, machine learning, cloud computing, cybersecurity, digital transformation, and data analytics. The magazine aims to connect the global community of enterprise IT and technology executives by offering insights into the digital journey and showcasing top companies and industry leaders.

XKool Technology is an AI cloud platform offering comprehensive solutions for the building industry. It provides digital and intelligent empowerment for design, construction, and management processes. The platform integrates AI technology to enhance building industrial upgrades and offers AI-assisted content creation, model marketplace, AI toolbox, and various design and management solutions.

LawSites is a blog by Robert Ambrogi that covers legal technology and innovation. It provides insights into various legal tech startups, AI applications in the legal field, and advancements in legal practice. The blog features articles, news, and podcasts related to legal technology, legal practice, and legal ethics.

The Legal Wire is an AI-powered platform that provides the latest news, resources, and insights on legal technology, compliance, regulations, and artificial intelligence. It offers newsletters, AI hubs, and in-depth articles on various legal topics. The platform aims to keep legal professionals informed about the intersection of law and technology, including the impact of AI on the legal industry.

Wildlife Insights is an AI application that brings cutting-edge technology to wildlife conservation. It streamlines decision-making by providing machine learning models and tools to manage, analyze, and share camera trap data. Users can easily upload, identify, analyze, and discover wildlife through the platform, enabling better decisions to help wildlife thrive globally.

Abridge is an enterprise-grade AI platform for clinical conversations, integrated directly inside Epic. It transforms patient-clinician conversations into structured clinical notes in real-time, powered by advanced generative AI technology. Abridge saves hours of time-consuming documentation per clinician every month, provides clinically accurate summaries and medical terms across specialties, recognizes and takes accurate notes across a wide range of languages, and creates complete, highly accurate, structured clinical note drafts. The platform aims to return time to healthcare teams, clarity to patients, and efficiencies to healthcare systems, ultimately reducing burnout among clinicians.

Entropik is a leading human insights company that offers AI-powered consumer and user experience solutions. Their platform provides fast insights for consumer research, user research, marketing experience, and product experience. With features like Co-Pilot AI, predictive analytics, diary studies, and live website/app testing, Entropik helps industries like market research agencies, consumer brands, BFSI, gaming, digital first brands, media & entertainment, fintech, healthcare, e-commerce, telecom, and retail optimize their customer journeys and enhance engagement. The platform also offers AI insights, emotion AI, generative AI, behavior AI, and predictive AI capabilities to track user focus and provide actionable insights. Entropik's resources include blogs, case studies, research insights, news & media updates, infographics, whitepapers, webinars, and eBooks to help users master consumer research with expert insights.

Historica is an AI-powered history map application that offers a unique and immersive experience by crafting historical maps of civilizations' timelines. The application utilizes cutting-edge AI technologies such as NLP, computer vision, and GIS to reconstruct landscapes from centuries past, providing users with a rich tapestry of historical knowledge. Historica aims to revive the past and make history more accessible through the fusion of technology and historical research.

The website page contains a collection of blog posts by Sam Altman, discussing various topics related to AI, technology, entrepreneurship, and personal reflections. The posts cover a wide range of subjects, including the development of AI tools, reflections on company progress, personal experiences, and insights on leadership and innovation. Sam Altman shares his thoughts on the impact of AI technology, the challenges and rewards of building a company, and the importance of long-term vision and persistence in achieving success.

The Chat With PDF AI Tool is an innovative application that allows users to interact with PDF documents using artificial intelligence technology. Users can engage in conversations with the AI tool to extract information, ask questions, and receive instant responses. The tool simplifies the process of working with PDF files by providing a conversational interface, making it user-friendly and efficient. With its advanced AI capabilities, the tool can understand natural language queries and provide accurate results, enhancing productivity and workflow efficiency.

ePlant is an AI-powered platform that revolutionizes plant data collection and application. It offers advanced plant-data intelligence through state-of-the-art wireless plant health monitors and AI technology. The platform enables users to remotely monitor trees and vines, track plant growth and stress, and measure environmental factors like temperature, light, and humidity. ePlant is trusted by experts in various fields such as research, urban forestry, precision agriculture, and silviculture. The TreeTag system, a key feature of ePlant, has been recognized as one of TIME's Best Inventions. With a focus on innovation and sustainability, ePlant is a valuable tool for anyone looking to optimize plant health and productivity.

Engadget is a leading technology news and reviews website that covers the latest gadgets, apps, and trends. It offers in-depth reviews of the latest smartphones, laptops, TVs, and other consumer electronics, as well as news and analysis on the latest developments in the tech industry. Engadget also has a strong focus on AI and robotics, with dedicated sections covering the latest advancements in these fields.

HumAInism is an AI application that focuses on AI governance, diplomacy, human studies, and the intersection of technology and humanity. It offers tools for explainability, transparency, standards, semantics, probability, aesthetics, and more. The platform aims to explore the ethical, societal, and philosophical implications of AI while providing practical solutions for governance and diplomacy.

Ada is a clinically driven AI application that supports better health outcomes and clinical excellence with intelligent technology. It provides users with trusted medical expertise in minutes to understand, manage, and get care for symptoms. Ada also offers powerful enterprise solutions to inform health decisions, enhance triage, and reduce avoidable costs. The application is optimized with human doctors and offers medical guidance in multiple languages, making it a popular choice for symptom assessment and pandemic responses.

AILYZE is an AI tool designed for qualitative data collection and analysis. Users can upload various document formats in any language to generate codes, conduct thematic, frequency, content, and cross-group analysis, extract top quotes, and more. The tool also allows users to create surveys, utilize an AI voice interviewer, and recruit participants globally. AILYZE offers different plans with varying features and data security measures, including options for advanced analysis and AI interviewer add-ons. Additionally, users can tap into data scientists for detailed and customized analyses on a wide range of documents.

ScrapeComfort is an AI-driven web scraping tool that offers an effortless and intuitive data mining solution. It leverages AI technology to extract data from websites without the need for complex coding or technical expertise. Users can easily input URLs, download data, set up extractors, and save extracted data for immediate use. The tool is designed to cater to various needs such as data analytics, market investigation, and lead acquisition, making it a versatile solution for businesses and individuals looking to streamline their data collection process.

OpenGlass is an open-source project that allows users to transform any regular glasses into smart glasses using affordable off-the-shelf components. With a cost of less than $25, users can enhance their glasses to record their daily activities, recognize people, identify objects, translate text, and more. The project provides detailed instructions on hardware setup and software installation, making it accessible for DIY enthusiasts and tech enthusiasts alike. By following the steps outlined in the repository, users can create their own smart glasses and explore various functionalities offered by the project.

SenseVoice is a speech foundation model focusing on high-accuracy multilingual speech recognition, speech emotion recognition, and audio event detection. Trained with over 400,000 hours of data, it supports more than 50 languages and excels in emotion recognition and sound event detection. The model offers efficient inference with low latency and convenient finetuning scripts. It can be deployed for service with support for multiple client-side languages. SenseVoice-Small model is open-sourced and provides capabilities for Mandarin, Cantonese, English, Japanese, and Korean. The tool also includes features for natural speech generation and fundamental speech recognition tasks.

KanTV is an open-source project that focuses on studying and practicing state-of-the-art AI technology in real applications and scenarios, such as online TV playback, transcription, translation, and video/audio recording. It is derived from the original ijkplayer project and includes many enhancements and new features, including: * Watching online TV and local media using a customized FFmpeg 6.1. * Recording online TV to automatically generate videos. * Studying ASR (Automatic Speech Recognition) using whisper.cpp. * Studying LLM (Large Language Model) using llama.cpp. * Studying SD (Text to Image by Stable Diffusion) using stablediffusion.cpp. * Generating real-time English subtitles for English online TV using whisper.cpp. * Running/experiencing LLM on Xiaomi 14 using llama.cpp. * Setting up a customized playlist and using the software to watch the content for R&D activity. * Refactoring the UI to be closer to a real commercial Android application (currently only supports English). Some goals of this project are: * To provide a well-maintained "workbench" for ASR researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To provide a well-maintained "workbench" for LLM researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To create an Android "turn-key project" for AI experts/researchers (who may not be familiar with regular Android software development) to focus on device-side AI R&D activity, where part of the AI R&D activity (algorithm improvement, model training, model generation, algorithm validation, model validation, performance benchmark, etc.) can be done very easily using Android Studio IDE and a powerful Android phone.

Awesome Flux AI is a curated list of resources, tools, libraries, and applications related to Flux AI technology. It serves as a comprehensive collection for developers, researchers, and enthusiasts interested in Flux AI. The platform offers open-source text-to-image AI models developed by Black Forest Labs, aiming to advance generative deep learning models for media, creativity, efficiency, and diversity.

Notate is a powerful desktop research assistant that combines AI-driven analysis with advanced vector search technology. It streamlines research workflow by processing, organizing, and retrieving information from documents, audio, and text. Notate offers flexible AI capabilities with support for various LLM providers and local models, ensuring data privacy. Built for researchers, academics, and knowledge workers, it features real-time collaboration, accessible UI, and cross-platform compatibility.

Video GigaGAN - Pytorch is an implementation of Video GigaGAN, a state-of-the-art video upsampling technique developed by Adobe AI labs. The project aims to provide a Pytorch implementation for researchers and developers interested in video super-resolution. The codebase allows users to replicate the results of the original research paper and experiment with video upscaling techniques. The repository includes the necessary code and resources to train and test the GigaGAN model on video datasets. Researchers can leverage this implementation to enhance the visual quality of low-resolution videos and explore advancements in video super-resolution technology.

CosyVoice is a tool designed for speech synthesis, offering pretrained models for zero-shot, sft, instruct inference. It provides a web demo for easy usage and supports advanced users with train and inference scripts. The tool can be deployed using grpc for service deployment. Users can download pretrained models and resources for immediate use or train their own models from scratch. CosyVoice is suitable for researchers, developers, linguists, AI engineers, and speech technology enthusiasts.

The UltraRAG framework is a researcher and developer-friendly RAG system solution that simplifies the process from data construction to model fine-tuning in domain adaptation. It introduces an automated knowledge adaptation technology system, supporting no-code programming, one-click synthesis and fine-tuning, multidimensional evaluation, and research-friendly exploration work integration. The architecture consists of Frontend, Service, and Backend components, offering flexibility in customization and optimization. Performance evaluation in the legal field shows improved results compared to VanillaRAG, with specific metrics provided. The repository is licensed under Apache-2.0 and encourages citation for support.

This repository is a curated list of research papers that explore the integration of Large Language Model (LLM) technology with tabular data. It aims to provide a comprehensive resource for researchers and practitioners interested in this emerging field. The repository includes papers on a wide range of topics, including table-to-text generation, table question answering, and tabular data classification. It also includes a section on related datasets and resources.

Awesome ChatGPT is an artificial intelligence chatbot developed by OpenAI. It offers a wide range of applications, web apps, browser extensions, CLI tools, bots, integrations, and packages for various platforms. Users can interact with ChatGPT through different interfaces and use it for tasks like generating text, creating presentations, summarizing content, and more. The ecosystem around ChatGPT includes tools for developers, writers, researchers, and individuals looking to leverage AI technology for different purposes.

PromptMage simplifies the process of creating and managing LLM workflows as a self-hosted solution. It offers an intuitive interface for prompt testing and comparison, incorporates version control features, and aims to improve productivity in both small teams and large enterprises. The tool bridges the gap in LLM workflow management, empowering developers, researchers, and organizations to make LLM technology more accessible and manageable for the next wave of AI innovations.

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.

LMOps is a research initiative focusing on fundamental research and technology for building AI products with foundation models, particularly enabling AI capabilities with Large Language Models (LLMs) and Generative AI models. The project explores various aspects such as prompt optimization, longer context handling, LLM alignment, acceleration of LLMs, LLM customization, and understanding in-context learning. It also includes tools like Promptist for automatic prompt optimization, Structured Prompting for efficient long-sequence prompts consumption, and X-Prompt for extensible prompts beyond natural language. Additionally, LLMA accelerators are developed to speed up LLM inference by referencing and copying text spans from documents. The project aims to advance technologies that facilitate prompting language models and enhance the performance of LLMs in various scenarios.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

MindNLP is an open-source NLP library based on MindSpore. It provides a platform for solving natural language processing tasks, containing many common approaches in NLP. It can help researchers and developers to construct and train models more conveniently and rapidly. Key features of MindNLP include: * Comprehensive data processing: Several classical NLP datasets are packaged into a friendly module for easy use, such as Multi30k, SQuAD, CoNLL, etc. * Friendly NLP model toolset: MindNLP provides various configurable components. It is friendly to customize models using MindNLP. * Easy-to-use engine: MindNLP simplified complicated training process in MindSpore. It supports Trainer and Evaluator interfaces to train and evaluate models easily. MindNLP supports a wide range of NLP tasks, including: * Language modeling * Machine translation * Question answering * Sentiment analysis * Sequence labeling * Summarization MindNLP also supports industry-leading Large Language Models (LLMs), including Llama, GLM, RWKV, etc. For support related to large language models, including pre-training, fine-tuning, and inference demo examples, you can find them in the "llm" directory. To install MindNLP, you can either install it from Pypi, download the daily build wheel, or install it from source. The installation instructions are provided in the documentation. MindNLP is released under the Apache 2.0 license. If you find this project useful in your research, please consider citing the following paper: @misc{mindnlp2022, title={{MindNLP}: a MindSpore NLP library}, author={MindNLP Contributors}, howpublished = {\url{https://github.com/mindlab-ai/mindnlp}}, year={2022} }

DistiLlama is a Chrome extension that leverages a locally running Large Language Model (LLM) to perform various tasks, including text summarization, chat, and document analysis. It utilizes Ollama as the locally running LLM instance and LangChain for text summarization. DistiLlama provides a user-friendly interface for interacting with the LLM, allowing users to summarize web pages, chat with documents (including PDFs), and engage in text-based conversations. The extension is easy to install and use, requiring only the installation of Ollama and a few simple steps to set up the environment. DistiLlama offers a range of customization options, including the choice of LLM model and the ability to configure the summarization chain. It also supports multimodal capabilities, allowing users to interact with the LLM through text, voice, and images. DistiLlama is a valuable tool for researchers, students, and professionals who seek to leverage the power of LLMs for various tasks without compromising data privacy.

JLB AI Agent is an innovative solution on the Solana blockchain that leverages artificial intelligence to automate complex tasks and enhance decision-making in the DeFi space. It offers real-time analytics, efficient operations, and seamless integration for both newcomers and experienced crypto enthusiasts. With features like autonomous trading, NFT management, DeFi insights, and comprehensive ecosystem integration, JLB empowers users with cutting-edge technology to navigate the dynamic landscape of blockchain.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

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