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Stream is an AI application developed by the Tensorplex Team to showcase the capabilities of existing Bittensor Subnets in powering consumer Web3 platforms. The application is designed to provide precise summaries and deep insights by utilizing the TPLX-LLM model. Stream offers a curated list of podcasts that are summarized using the Bittensor Network.

Vectara is a conversational search demo that showcases the capabilities of a search tool with a conversational interface. Users can interact with the search tool using natural language queries, making the search process more intuitive and user-friendly. The demo aims to demonstrate how conversational search can enhance the user experience and improve search accuracy.

ChatGPT is a large language model developed by OpenAI. It is designed to understand and generate human-like text, and can be used for a variety of tasks such as answering questions, writing stories, and translating languages. ChatGPT is free to use, and can be accessed through a web interface or via an API.

Image In Words is a generative model designed for scenarios that require generating ultra-detailed text from images. It leverages cutting-edge image recognition technology to provide high-quality and natural image descriptions. The framework ensures detailed and accurate descriptions, improves model performance, reduces fictional content, enhances visual-language reasoning capabilities, and has wide applications across various fields. Image In Words supports English and has been trained using approximately 100,000 hours of English data. It has demonstrated high quality and naturalness in various tests.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, allowing for the decoding of activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages both behavioral and neural data to produce consistent and high-performance latent spaces, enabling the mapping of space, uncovering complex kinematic features, and providing rapid, high-accuracy decoding of natural movies from the visual cortex.

Docebo is an AI-powered learning platform designed for businesses to deliver innovative and valuable learning experiences. It offers solutions for employee onboarding, compliance training, sales enablement, talent development, customer education, partner enablement, and member training. With features like AI-powered learning, content creation, embedded learning, learning intelligence, and a generative AI LMS, Docebo aims to help organizations drive engagement, productivity, advocacy, and connection with their stakeholders.

Basis Theory is a platform that helps businesses build a fully programmable vault for creating engaging commerce flows, connecting with partners, managing compliance effortlessly, and maintaining control over payments data. It offers flexible payment solutions, industry-tailored payment flows, and custom payment strategies for various use cases. The platform is designed to cater to high-risk merchants, subscription platforms, marketplaces, fintechs, and more, providing full control over customer card data and tailored payment experiences.

StoryFile is a Conversational Video AI SaaS Technology platform designed for both educational and business solutions. It offers an interactive medium called a storyfile, making AI more human by enabling videos that can talk back. The platform helps businesses adopt artificial intelligence to enhance user engagement and provide personalized experiences.

The website offers a brand new course titled 'Prompt Engineering for Everyone' to help users master the language of AI. With over 100 courses and 20+ learning paths, users can learn AI, Data Science, and other emerging technologies. The platform provides hands-on content designed by expert instructors, allowing users to gain practical, industry-relevant knowledge and skills. Users can earn certificates to showcase their expertise and build projects to demonstrate their skills. Trusted by 3 million learners globally, the platform offers a community of learners with a proven track record of success.

Identable is an all-in-one AI-powered platform for social media marketing solutions, specializing in personal branding and social media management. It offers automated scheduling, real-time performance tracking, personalized content recommendations, and intelligent content optimization. With Identable, users can streamline their social media workflow, maximize visibility and engagement across channels, and access customizable content templates. The platform also provides detailed analytics and insights to help users optimize their social media strategy and demonstrate the impact of their efforts.

Poker Bot AI+ is an advanced poker AI application that offers fully automated poker bots powered by neural networks and machine learning. The application provides a suite of products to enhance poker gameplay, including automated online poker bots, AI advisor PokerX, Poker Ecology service, poker skill development with AI-guided tips, and Android-based poker farms on emulators. It supports various poker games and rooms, ensuring optimal decision-making for players. The software guarantees secure gameplay by emulating human behavior and safeguarding user identity. Before purchasing, the effectiveness of the poker bot is demonstrated privately. Poker Bot AI+ aims to revolutionize the poker industry with cutting-edge AI technology.

Phenaki is a model capable of generating realistic videos from a sequence of textual prompts. It is particularly challenging to generate videos from text due to the computational cost, limited quantities of high-quality text-video data, and variable length of videos. To address these issues, Phenaki introduces a new causal model for learning video representation, which compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos. To generate video tokens from text, Phenaki uses a bidirectional masked transformer conditioned on pre-computed text tokens. The generated video tokens are subsequently de-tokenized to create the actual video. To address data issues, Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets. Compared to previous video generation methods, Phenaki can generate arbitrarily long videos conditioned on a sequence of prompts (i.e., time-variable text or a story) in an open domain. To the best of our knowledge, this is the first time a paper studies generating videos from time-variable prompts. In addition, the proposed video encoder-decoder outperforms all per-frame baselines currently used in the literature in terms of spatio-temporal quality and the number of tokens per video.

Devin AI, developed by Cognition Labs, is the world's first fully autonomous AI software engineer. It streamlines software development by handling complex tasks, allowing engineers to focus on more challenging aspects. Devin AI possesses advanced programming skills, can manage complex tasks, understands and learns contextually, integrates with developer tools, and offers collaborative features. It can build and deploy applications, detect and fix bugs, contribute to open-source projects, train AI models, and handle GitHub repositories. Devin AI has demonstrated strong performance in issue resolution, surpassing previous AI models. It is currently in early access, with plans for future enhancements and integration with various development tools and platforms.

GenInnov is a generative innovation fund that provides a platform for investors seeking to be at the forefront of technological advancement. The fund invests in companies driving transformative change across multiple sectors and geographies, prioritizing material innovations with demonstrable profitability and global reach. GenInnov operates with a research-driven approach, focusing on investing in material innovations that are monetizable, profitable, and transformative, rather than incremental. The fund looks at various domains such as technology, robotics, consumer electronics, biotech, healthcare, mobility, and clean tech, aiming to amplify human creativity through machine intelligence.

Effort is an example implementation of the bucketMul algorithm, which allows for real-time adjustment of the number of calculations performed during inference of an LLM model. At 50% effort, it performs as fast as regular matrix multiplications on Apple Silicon chips; at 25% effort, it is twice as fast while still retaining most of the quality. Additionally, users have the option to skip loading the least important weights.

MarkLLM is an open-source toolkit designed for watermarking technologies within large language models (LLMs). It simplifies access, understanding, and assessment of watermarking technologies, supporting various algorithms, visualization tools, and evaluation modules. The toolkit aids researchers and the community in ensuring the authenticity and origin of machine-generated text.

AI4Animation is a comprehensive framework for data-driven character animation, including data processing, neural network training, and runtime control, developed in Unity3D/PyTorch. It explores deep learning opportunities for character animation, covering biped and quadruped locomotion, character-scene interactions, sports and fighting games, and embodied avatar motions in AR/VR. The research focuses on generative frameworks, codebook matching, periodic autoencoders, animation layering, local motion phases, and neural state machines for character control and animation.

This repository showcases a project that indexes millions of Wikipedia articles using Upstash Vector. It includes a semantic search engine and a RAG chatbot SDK. The project involves preparing and embedding Wikipedia articles, indexing vectors, building a semantic search engine, and implementing a RAG chatbot. Key features include indexing over 144 million vectors, multilingual support, cross-lingual semantic search, and a RAG chatbot. Technologies used include Upstash Vector, Upstash Redis, Upstash RAG Chat SDK, SentenceTransformers, and Meta-Llama-3-8B-Instruct for LLM provider.

This repository focuses on organizing resources for building synthetic datasets using large language models. It covers important datasets, libraries, tools, tutorials, and papers related to synthetic data generation. The goal is to provide pragmatic and practical resources for individuals interested in creating synthetic datasets for machine learning applications.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.

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.

ENOVA is an open-source service for Large Language Model (LLM) deployment, monitoring, injection, and auto-scaling. It addresses challenges in deploying stable serverless LLM services on GPU clusters with auto-scaling by deconstructing the LLM service execution process and providing configuration recommendations and performance detection. Users can build and deploy LLM with few command lines, recommend optimal computing resources, experience LLM performance, observe operating status, achieve load balancing, and more. ENOVA ensures stable operation, cost-effectiveness, efficiency, and strong scalability of LLM services.

This repository contains example code to demonstrate how to connect MATLAB to the OpenAI™ Chat Completions API (which powers ChatGPT™) as well as OpenAI Images API (which powers DALL·E™). This allows you to leverage the natural language processing capabilities of large language models directly within your MATLAB environment.

Linesight is a reinforcement learning project focused on advancing AI capabilities in the racing game Trackmania. It aims to push the boundaries of AI performance by utilizing deep learning algorithms to achieve human-level driving and beat world records on official campaign tracks. The project provides an interface to interact with Trackmania Nations Forever programmatically, enabling tasks such as sending inputs, retrieving car states, and capturing screenshots. With a strong emphasis on equality of input devices, Linesight serves as a benchmark for testing various reinforcement learning algorithms in a challenging and dynamic gaming environment.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

BlinkID iOS is a mobile SDK that enables developers to easily integrate ID scanning and data extraction capabilities into their iOS applications. The SDK supports scanning and processing various types of identity documents, such as passports, driver's licenses, and ID cards. It provides accurate and fast data extraction, including personal information and document details. With BlinkID iOS, developers can enhance their apps with secure and reliable ID verification functionality, improving user experience and streamlining identity verification processes.

FreeGenius AI is an ambitious project offering a comprehensive suite of AI solutions that mirror the capabilities of LetMeDoIt AI. It is designed to engage in intuitive conversations, execute codes, provide up-to-date information, and perform various tasks. The tool is free, customizable, and provides access to real-time data and device information. It aims to support offline and online backends, open-source large language models, and optional API keys. Users can use FreeGenius AI for tasks like generating tweets, analyzing audio, searching financial data, checking weather, and creating maps.

LLMClient is a JavaScript/TypeScript library that simplifies working with large language models (LLMs) by providing an easy-to-use interface for building and composing efficient prompts using prompt signatures. These signatures enable the automatic generation of typed prompts, allowing developers to leverage advanced capabilities like reasoning, function calling, RAG, ReAcT, and Chain of Thought. The library supports various LLMs and vector databases, making it a versatile tool for a wide range of applications.

The 'llm' package for Emacs provides an interface for interacting with Large Language Models (LLMs). It abstracts functionality to a higher level, concealing API variations and ensuring compatibility with various LLMs. Users can set up providers like OpenAI, Gemini, Vertex, Claude, Ollama, GPT4All, and a fake client for testing. The package allows for chat interactions, embeddings, token counting, and function calling. It also offers advanced prompt creation and logging capabilities. Users can handle conversations, create prompts with placeholders, and contribute by creating providers.

Odyssey is a framework designed to empower agents with open-world skills in Minecraft. It provides an interactive agent with a skill library, a fine-tuned LLaMA-3 model, and an open-world benchmark for evaluating agent capabilities. The framework enables agents to explore diverse gameplay opportunities in the vast Minecraft world by offering primitive and compositional skills, extensive training data, and various long-term planning tasks. Odyssey aims to advance research on autonomous agent solutions by providing datasets, model weights, and code for public use.

LLM-Geo is an AI-powered geographic information system (GIS) that leverages Large Language Models (LLMs) for automatic spatial data collection, analysis, and visualization. By adopting LLM as the reasoning core, it addresses spatial problems with self-generating, self-organizing, self-verifying, self-executing, and self-growing capabilities. The tool aims to make spatial analysis easier, faster, and more accessible by reducing manual operation time and delivering accurate results through case studies. It uses GPT-4 API in a Python environment and advocates for further research and development in autonomous GIS.

The Turing Test, first named the imitation game by Alan Turing in 1950, is a measure of a machine's capacity to demonstrate intelligence that's either equal to or indistinguishable from human intelligence.