Model training and deployment

Fume is an AI testing tool that uses artificial intelligence technology to provide users with a worry-free AI testing experience. It can generate and maintain Playwright end-to-end browser tests based on users' recorded videos, greatly simplifying the testing process and improving testing efficiency.

Relyable is an automated AI agent testing and monitoring tool that helps users evaluate, optimize and monitor the performance of AI voice agents through simulation and intelligent analysis. It helps users quickly deploy production-ready AI agents and improve work efficiency.

SiliconFlow is an AI infrastructure that provides developers with LLM deployment, AI model hosting, and inference APIs. It provides users with lower latency, higher throughput and predictable costs through an optimized stack.

MagicaLCore is an application that can perform machine learning work on the iPad. Users can import, organize, train and test machine learning models in real time, and develop and experiment with models directly on the device.

Labelbox is a data factory designed for AI teams, aiming to provide solutions for building, operating, and data labeling. Its main advantages include flexible annotation tools, automated data processes, rich data management functions, etc. Background information: Labelbox is committed to helping AI teams improve data annotation efficiency and model training quality, and is positioned to provide a comprehensive data management and annotation platform.

OpenTrain AI is an AI training data marketplace that lets you directly hire vetted human data experts from around the world, using your favorite annotation software. Reduce costs, maintain control, and quickly build high-quality AI training data.

Genie Studio is a one-stop development platform specially created by Zhiyuan Robot for embodied intelligence scenarios. It has full-link product capabilities including data collection, model training, simulation evaluation, and model reasoning. It provides developers with standardized solutions from ‘acquisition’ to ‘training’ to ‘testing’ to ‘push’, which greatly lowers the development threshold and improves development efficiency. The platform promotes the rapid development and application of embodied intelligence technology through efficient data collection, flexible model training, accurate simulation evaluation and seamless model reasoning. Genie Studio not only provides powerful tools, but also provides support for the large-scale implementation of embodied intelligence, accelerating the industry's leap to a new stage of standardization, platformization, and mass production.

Awesome-LLM-Post-training is a resource library focused on large language model (LLM) post-training methods. It provides an in-depth look at post-LLM training, including tutorials, surveys, and guides. This resource library is based on the paper "LLM Post-Training: A Deep Dive into Reasoning Large Language Models" and aims to help researchers and developers better understand and apply LLM post-training technology. This resource library is free and open and suitable for academic research and industrial applications.

ARGO is a multi-platform AI client designed to provide users with a powerful artificial intelligence assistant with the ability to think independently, task planning and complex task processing. Its main advantage is that it runs locally on the user's device, ensuring data privacy and security. It is suitable for user groups who need to manage and process tasks efficiently and supports multiple operating systems. Permanently open source and free.

LLMs.txt Generator is an online tool powered by Firecrawl designed to help users generate integrated text files for LLM training and inference from websites. It provides high-quality text data for training large language models by integrating web content, thereby improving model performance and accuracy. The main advantage of this tool is that it is simple and efficient to operate and can quickly generate the required text files. It is mainly aimed at developers and researchers who need large amounts of text data for model training, providing them with a convenient solution.

AI21-Jamba-Large-1.6 is a hybrid SSM-Transformer architecture base model developed by AI21 Labs, designed for long text processing and efficient reasoning. The model performs well in long text processing, reasoning speed and quality, supports multiple languages, and has strong instruction following capabilities. It is suitable for enterprise-level applications that need to process large amounts of text data, such as financial analysis, content generation, etc. The model is licensed under the Jamba Open Model License, which allows research and commercial use under the terms of the license.

MoBA (Mixture of Block Attention) is an innovative attention mechanism designed for large language models in long text contexts. It enables efficient long sequence processing by dividing context into chunks and letting each query token learn to focus on the most relevant chunks. The main advantage of MoBA is its ability to seamlessly switch between full attention and sparse attention, which not only ensures performance but also improves computational efficiency. This technology is suitable for tasks that require processing long texts, such as document analysis, code generation, etc., and can significantly reduce computing costs while maintaining high performance of the model. The open source implementation of MoBA provides researchers and developers with powerful tools to advance the application of large language models in the field of long text processing.

OLMoE is an open source language model application developed by Ai2 to provide researchers and developers with a completely open toolkit for conducting artificial intelligence experiments on devices. The app supports offline operation on iPhone and iPad, ensuring user data is completely private. It is built on an efficient OLMoE model and is optimized and quantized to maintain high performance when running on mobile devices. The open source nature of the application makes it an important foundation for research and development of a new generation of on-device artificial intelligence applications.

DeepSeek-R1-Distill-Qwen-32B is a high-performance language model developed by the DeepSeek team, based on the Qwen-2.5 series for distillation optimization. The model performs well on multiple benchmarks, especially on math, coding, and reasoning tasks. Its main advantages include efficient reasoning capabilities, powerful multi-language support, and open source features, which facilitate secondary development and application by researchers and developers. This model is suitable for scenarios that require high-performance text generation, such as intelligent customer service, content creation, and code assistance, and has broad application prospects.

This product is an AI-driven data science team model designed to help users complete data science tasks faster. It automates and accelerates data science workflows through a series of professional data science agents (Agents), such as data cleaning, feature engineering, modeling, etc. The main advantage of this product is that it can significantly improve the efficiency of data science work and reduce manual intervention. It is suitable for enterprises and research institutions that need to quickly process and analyze large amounts of data. The product is currently in the Beta stage and is under active development, and there may be breakthrough changes. It adopts the MIT license, and users can use and contribute code for free on GitHub.

Bespoke Labs focuses on providing high-quality customized data set services to support engineers in precise model fine-tuning. The company was co-founded by former Google DeepMind employees Mahesh and UT Austin's Alex to improve access to high-quality data, which is critical to advancing the field. The tools and platforms provided by Bespoke Labs, such as Minicheck, Evalchemy and Curator, are designed around the creation and management of datasets to improve data quality and model performance.

OpenEMMA is an open source project that reproduces Waymo's EMMA model and provides an end-to-end framework for motion planning of autonomous vehicles. The model leverages pre-trained visual language models (VLMs) such as GPT-4 and LLaVA to integrate text and forward-looking camera input to achieve accurate predictions of its own future waypoints and provide reasons for decision-making. The goal of OpenEMMA is to provide researchers and developers with easily accessible tools to advance autonomous driving research and applications.

DRT-o1-14B is a neural machine translation model designed to improve the depth and accuracy of translation through long-chain reasoning. The model mines English sentences containing metaphors or metaphors and adopts a multi-agent framework (including translators, consultants, and evaluators) to synthesize long-thinking machine translation samples. DRT-o1-14B is trained based on Qwen2.5-14B-Instruct as the backbone, has a parameter amount of 14.8B, and supports BF16 tensor type. The importance of this model lies in its ability to handle complex translation tasks, especially where in-depth understanding and reasoning are required, providing a new solution.

DRT-o1-7B is a model dedicated to successfully applying long-thinking reasoning to neural machine translation (MT). The model synthesizes MT samples by mining English sentences suitable for long-thinking translation, and proposes a multi-agent framework including three roles: translator, consultant, and evaluator. DRT-o1-7B and DRT-o1-14B use Qwen2.5-7B-Instruct and Qwen2.5-14B-Instruct as the backbone network for training. The main advantage of this model is its ability to handle complex language structures and deep semantic understanding, which are crucial to improving the accuracy and naturalness of machine translation.

AMD ROCm™ 6.3 is a major milestone for AMD’s open source platform, introducing advanced tools and optimizations to advance AI, machine learning (ML) and high-performance computing (HPC) workloads on AMD Instinct GPU accelerators. ROCm 6.3 is designed to enhance developer productivity for a wide range of customers, from innovative AI startups to HPC-driven industries.

MLPerf Client is a new benchmark co-developed by MLCommons designed to evaluate the performance of large language models (LLMs) and other AI workloads on personal computers, ranging from laptops to desktops to workstations. This benchmark provides clear indicators of how a system handles generative AI workloads by simulating real-world AI tasks. The MLPerf Client Working Group hopes this benchmark will drive innovation and competition, ensuring PCs can meet the challenges of an AI-driven future.

Trillium TPU is Google Cloud’s sixth-generation Tensor Processing Unit (TPU) designed specifically for AI workloads, delivering enhanced performance and cost-effectiveness. As a key component of the Google Cloud AI Hypercomputer, it supports the training, fine-tuning and inference of large-scale AI models through integrated hardware systems, open software, leading machine learning frameworks and flexible consumption models. Trillium TPU has significantly improved performance, cost efficiency and sustainability, and is an important advancement in the field of AI.

SPDL (Scalable and Performant Data Loading) is a new data loading solution developed by Meta Reality Labs, designed to improve the efficiency of AI model training. It uses thread-based parallel processing. Compared with traditional process-based solutions, SPDL achieves high throughput in the ordinary Python interpreter and consumes less computing resources. SPDL is compatible with Free-Threaded Python and, with the GIL disabled, achieves higher throughput than FT Python with the GIL enabled. The main advantages of SPDL include high throughput, easy-to-understand performance, no encapsulation of preprocessing operations, no introduction of domain-specific languages ​​(DSL), seamless integration of asynchronous tools, flexibility, simplicity and intuitiveness, and fault tolerance. Background information on SPDL shows that as the size of the model increases, the computational requirements for data also increase, and SPDL speeds up model training by maximizing GPU utilization.

OLMo-2-1124-7B-SFT is an English text generation model released by the Allen Institute for Artificial Intelligence (AI2). It is a supervised fine-tuned version of the OLMo 2 7B model and is specifically optimized for the Tülu 3 dataset. The Tülu 3 dataset is designed to provide top performance on a variety of tasks, including chatting, math problem solving, GSM8K, IFEval, and more. The main advantages of this model include powerful text generation capabilities, diverse task processing capabilities, and open source code and training details, making it a powerful tool in research and education.

Aria-Base-64K is one of the base models of the Aria series, designed for research purposes and continued training. The model is formed after the long text pre-training stage and is trained on 33B tokens (21B multimodal, 12B language, 69% long text). It is suitable for continued pre-training or fine-tuning of long video Q&A data sets or long document Q&A data sets. Even when resources are limited, the data set can be tuned with short instructions for post-training and transferred to long text Q&A scenarios. The model is able to understand up to 250 high-resolution images or up to 500 medium-resolution images and maintains strong base performance in language and multi-modal scenes.

Foundry AI is a platform focused on building, evaluating, and improving AI agents designed to deliver reliable results. The platform enables continuous improvement through real-time feedback, allows custom control of human intervention, and conducts A/B testing to optimize performance. Foundry AI is built by industry experts and provides a smarter AI management system than traditional automation, enabling higher-quality AI results, fast and effective improvements, and intelligent human-AI collaboration.

Llama-3.1-Tulu-3-8B-SFT is a member of the Tülu3 model family, a leading family of instruction-following models offering fully open source data, code, and recipes designed to provide a comprehensive guide to modern post-training techniques. The model not only performs well on chat tasks, but also shows excellent performance on diverse tasks such as MATH, GSM8K and IFEval.

Zhipu Qingliu AI open platform is an enterprise-level AI agent development platform that uses Zhipu large model technology to help enterprises quickly build professional-level agents and realize rapid application of large models to business scenarios. The platform provides model services, agent construction, data security, effect evaluation, system integration and other functions. It supports enterprises to protect data through intranet deployment and local storage to ensure data security and intellectual property rights. With its leading technology, flexible workflow orchestration, independent use of enterprise-defined data knowledge and tools, and mature AI native application implementation experience, the Zhipu AI open platform has become an important driver of enterprise digital transformation.

OuteTTS-0.1-350M is a text-to-speech synthesis technology based on a pure language model. It does not require external adapters or complex architectures and achieves high-quality speech synthesis through carefully designed prompts and audio tags. This model is based on the LLaMa architecture and uses 350M parameters, demonstrating the potential of directly using language models for speech synthesis. It processes audio in three steps: audio tokenization using WavTokenizer, CTC-enforced alignment to create precise word-to-audio token mapping, and creation of structured prompts that follow a specific format. Key advantages of OuteTTS include a pure language modeling approach, sound cloning capabilities, and compatibility with llama.cpp and GGUF formats.

Tencent-Hunyuan-Large (Hunyuan Large Model) is an industry-leading open source large-scale hybrid expert (MoE) model launched by Tencent, with 389 billion total parameters and 52 billion activation parameters. The model has made significant progress in fields such as natural language processing, computer vision, and scientific tasks, especially in processing long-context input and improving long-context task processing capabilities. The open source of the Hunyuan large model aims to inspire more researchers to innovate and jointly promote the progress and application of AI technology.

Fish Agent V0.1 3B is a groundbreaking speech-to-speech model that captures and generates environmental audio information with unprecedented accuracy. The model uses a semantic markup-free architecture that eliminates the need for traditional semantic encoders/decoders. Additionally, it is a cutting-edge text-to-speech (TTS) model with training data covering 700,000 hours of multilingual audio content. As a continued pre-trained version of Qwen-2.5-3B-Instruct, it is trained on 200B speech and text tokens. The model supports 8 languages ​​including English and Chinese. The amount of training data for each language is different, including approximately 300,000 hours each for English and Chinese, and approximately 20,000 hours each for other languages.

π0 is a universal robot basic model designed to allow AI systems to acquire physical intelligence through physical training and be able to perform various tasks, just like large language models and chatbot assistants. π0 acquires physical intelligence through physical experience trained on robots, can directly output low-level motor commands, control a variety of different robots, and can be fine-tuned for specific application scenarios. The development of π0 represents an important advance in the application of artificial intelligence to the physical world, by combining large-scale multi-task and multi-robot data collection with new network architectures to provide the most capable and dexterous general-purpose robotic policy to date.

Decart is an efficient AI platform that delivers orders of magnitude improvements in training and inferencing large generative models. Leveraging these advanced capabilities, Decart is able to train fundamental generative interaction models and make them accessible to everyone in real time. Decart’s OASIS model is a real-time generated AI open world model that represents the future of real-time video generation. The platform also provides the ability to train or infer on a cluster of 1,000+ NVIDIA H100 Tensor Core GPUs, bringing a breakthrough in the field of AI video generation.

ComfyOnline provides an online environment for running ComfyUI workflows and can generate APIs to facilitate AI application development. 它无需昂贵的硬件投资，无需复杂的设置或安装，仅按运行时间收费，自动扩展以满足需求，帮助用户轻松部署AI应用。

OMat24 is a series of model checkpoints published by Meta's FAIR Chemistry team that vary in different model sizes and training strategies. These models use the EquiformerV2 architecture and are designed to promote research in the field of materials science and predict the properties of materials through machine learning models, thereby accelerating the discovery and development of new materials. These models are pre-trained on publicly available datasets and are available in different scales to suit different research needs.

Aya Expanse 32B is a multi-language large-scale language model developed by Cohere For AI, with 3.2 billion parameters, focusing on providing high-performance multi-language support. It combines advanced data arbitration, multi-language preference training, security tuning and model merging technology to support 23 languages, including Arabic, Chinese (Simplified and Traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian and Vietnamese. The release of this model aims to make community-based research more accessible by releasing high-performance, multi-language model weights for use by researchers around the world.

The Llama model is a large language model launched by Meta Company. Through quantification technology, the model is smaller and runs faster while maintaining the quality and safety of the model. These models are particularly suitable for mobile devices and edge deployments, enabling fast on-device inference on resource-constrained devices while reducing memory footprint. The development of the quantitative Llama model marks an important advancement in the field of mobile AI, enabling more developers to build and deploy high-quality AI applications without requiring large amounts of computing resources.

AIxBlock is an integrated platform that uses decentralized computing resources to quickly productize AI models with flexibility and complete privacy control. It provides decentralized super computing power for AI projects through blockchain technology, reducing computing costs by up to 90%, and reducing costs through peer-to-peer transactions without transaction fees. AIxBlock also emphasizes data privacy and security, providing platform options that run on local infrastructure to ensure the privacy of data and models. Additionally, it provides a code-free AI ecosystem that supports the entire AI development journey from concept to commercialization.

Spirit LM is a basic multi-modal language model that can freely mix text and speech. The model is based on a 7B pre-trained text language model and extends to speech modes by continuously training on text and speech units. Speech and text sequences are concatenated into a single token stream and trained using a small automatically curated speech-text parallel corpus using a word-level interleaved approach. Spirit LM has two versions: the basic version uses speech phoneme units (HuBERT), while the expression version uses pitch and style units in addition to phoneme units to simulate expressivity. For both versions, the text is encoded using subword BPE tokens. This model not only demonstrates the semantic capabilities of the text model, but also demonstrates the expressive capabilities of the speech model. Furthermore, we show that Spirit LM is able to learn new tasks (e.g., ASR, TTS, speech classification) across modalities with a small number of samples.

Liquid Foundation Models (LFMs) are a new family of generative AI models that achieve state-of-the-art performance at all scales while maintaining a smaller memory footprint and more efficient inference efficiency. LFMs utilize computational units from dynamic systems theory, signal processing, and numerical linear algebra to process any type of sequence data including video, audio, text, time series, and signals. These models are general-purpose AI models designed to process large-scale sequential multi-modal data, enable advanced reasoning, and make reliable decisions.

Emu3 is a set of the latest multi-modal models, trained only by next token prediction, capable of processing images, text and video. It outperforms multiple task-specific flagship models on both generation and perception tasks, and does not require diffusion or compositional architectures. Emu3 simplifies complex multi-modal model design by unifying multi-modal sequences into a single transformer model, demonstrating great potential for scaling during training and inference.

Future AGI is an automated AI model evaluation platform that eliminates the need for manual QA evaluation by automatically scoring AI model output, allowing QA teams to focus on more strategic tasks, increasing efficiency and bandwidth by up to 10x. The platform uses natural language to define the metrics most important to the business, providing enhanced flexibility and control to evaluate model performance and ensure alignment with business goals. It also creates a cycle of continuous improvement by integrating performance data and user feedback into the development process, making the AI ​​smarter with every interaction.

The 1X World Model is a machine learning program that simulates how the world responds to a robot's behavior. It is based on technological advances in video generation and self-driving car world models, providing a virtual simulator for robots capable of predicting future scenarios and evaluating robot strategies. This model is not only able to handle complex object interactions such as rigid bodies, the impact of dropped objects, partial observability, deformable objects, and articulated objects, but is also capable of evaluation in changing environments, which is crucial for the development of robotics.

Weavel is an AI prompt engineer that helps users optimize the application of large language models (LLM) through functions such as tracking, data set management, batch testing and evaluation. Used in conjunction with the Weavel SDK, Weavel automatically records and adds LLM-generated data to your dataset, enabling seamless integration and continuous improvement for specific use cases. In addition, Weavel can automatically generate evaluation codes and use LLM as an impartial referee for complex tasks, simplifying the evaluation process and ensuring accurate and detailed performance indicators.

The ultra-long context model (LTM) developed by the Magic team can handle context information up to 100M tokens, which is a major breakthrough in the field of AI. This technology is mainly aimed at the field of software development and greatly improves the quality and efficiency of code synthesis by providing a large amount of context for codes, documents and libraries during the reasoning process. Compared with traditional recurrent neural networks and state space models, LTM models have obvious advantages in storing and retrieving large amounts of information, and can build more complex logic circuits. In addition, the Magic team is also collaborating with Google Cloud to build a next-generation AI supercomputer using NVIDIA GB200 NVL72 to further promote model inference and training efficiency.

Zamba2-mini is a small language model released by Zyphra Technologies Inc., designed for device-side applications. It achieves evaluation scores and performance comparable to larger models while maintaining a very small memory footprint (<700MB). This model uses 4-bit quantization technology, which has the characteristics of 7 times parameter reduction while maintaining the same performance. Zamba2-mini excels in inference efficiency, with faster first token generation time, lower memory overhead, and lower generation latency than larger models such as Phi3-3.8B. Additionally, the model's weights have been released as open source (Apache 2.0), allowing researchers, developers, and companies to leverage its capabilities and push the boundaries of efficient base models.

Cerebras Inference is an AI inference platform launched by Cerebras, which provides 20 times the speed of GPU and 1/5 the cost. It leverages Cerebras' high-performance computing technology to provide fast and efficient inference services for large-scale language models, high-performance computing, etc. The platform supports a variety of AI models, including industry applications such as medical, energy, government, and financial services. It is open source and allows users to train their own basic models or fine-tune open source models.

Datalab's AI For Document Intelligence is a series of AI models for intelligent document processing, including OCR, layout analysis, PDF to Markdown, etc. These models represent the latest developments in document processing technology, are easy to use, are open source, and can be widely applied to improve the efficiency and accuracy of document processing.

Mystic Turbo Registry is a high-performance AI model loader developed by Mystic.ai. It is written in Rust language and is specifically optimized to reduce the cold start time of AI models. By improving container loading efficiency, it significantly reduces the time required from model startup to running, providing users with faster model response speed and higher operating efficiency.

LLM Quality Beefer-Upper is a website designed to improve the quality of Large Language Model (LLM) responses through automated criticism, reflection, and improvement. It adopts the chain of thought approach, which has been proven to be the best way to improve the quality and accuracy of LLM. Users can use and refine customized and pre-built multi-agent prompt templates to obtain the most reliable and high-quality output. The website currently uses Claude Sonnet 3.5 API as it is the best LLM on the market. As soon as a better model becomes available, it will be adopted as providing the highest quality output is the only goal of the application.

UbiOps is an AI infrastructure platform that helps teams quickly run their AI and machine learning workloads as reliable and secure microservices without changing existing workflows. It provides ultra-fast pipelines with zero DevOps, optimized computing resources, support for LLMs and CV models, and other features. UbiOps supports hybrid and multi-cloud workload orchestration, allowing models to be deployed in private or public cloud environments, ensuring that data and models always remain in the user's environment. In addition, UbiOps provides built-in security features such as end-to-end encryption, secure data storage and access control to help enterprises comply with relevant regulations.

GPUDeploy is a website that provides low-cost on-demand GPU resources. It is designed for machine learning and artificial intelligence tasks. Users can instantly launch preconfigured GPU instances to support complex computing tasks. The main advantages of this product include low cost, instant availability and convenience of pre-configuration, making it suitable for enterprises and individuals who need to quickly deploy machine learning models and algorithms.

Arcee Spark is a 7B parameter language model that provides high performance in a compact package, proving that small models can compete with large models. It is the highest-scoring model in the 7B-15B range and outperforms larger models like GPT 3.5 and Claude 2.1 on the MT-Bench benchmark. It is suitable for real-time applications, edge computing scenarios, cost-effective AI implementation, rapid prototyping and on-premises deployment with enhanced data privacy.

Source.Plus is a professional AI training data search platform that allows users to precisely search, filter and organize the required data sets through advanced search operators. It supports multiple data sources, including Wikimedia Commons, NMNH - Botany Dept., etc., providing a wide range of image and document resources. The platform also features file upload capabilities, allowing users to further customize and enrich their datasets. The main advantages of Source.Plus include its powerful search capabilities, diversity of data sources, and special optimization of AI training data.

Samba-1 Turbo is a platform that provides AI model selection and application. It allows developers to try, compare and evaluate various expert models in Samba-1 through free developer inference services. In addition, the platform offers a number of demo business applications built on Samba-1, as well as open source language expert SambaLingo. Samba-1 Turbo is designed to provide developers with powerful tools to simplify the integration and application process of AI models.

Refuel LLM-2 is an advanced language model designed for data annotation, cleaning and enrichment. It surpasses all existing state-of-the-art language models, including GPT-4-Turbo, Claude-3-Opus, and Gemini-1.5-Pro, on benchmarks on approximately 30 data annotation tasks. Refuel LLM-2 is designed to improve the work efficiency of data teams and reduce manual labor in preliminary work such as data cleaning, normalization, annotation, etc., thereby realizing the business value of data faster.

Mazaal is a no-code AI platform that turns your data into powerful AI models without writing any code. It provides a variety of pre-trained models that can be used to optimize production, manage inventory, forecast demand, etc. Mazaal automates workflows, improves efficiency, and helps you solve various problems in your business.

TensorDock is a professional cloud service provider built for workloads that require uncompromising reliability. It offers multiple GPU server options, including NVIDIA H100 SXMs, and the most cost-effective virtual machine infrastructure for deep learning, AI, and rendering. TensorDock also provides fully managed container hosting with operating system-level monitoring, autoscaling, and load balancing. Additionally, TensorDock offers world-class enterprise support, staffed by professionals.

AI Express is a service platform designed for AI developers. It provides free accelerated downloading of HuggingFace models, solving the problem of slow and disconnected downloads of large models. It supports download speeds up to 4M/s, greatly reducing waiting time and improving development efficiency.

Portkey is an LLMOps platform that helps enterprises develop, release, maintain and iterate generative AI applications and features faster. With Portkey’s Observability Suite and AI Gateway, hundreds of teams can release applications that are reliable, efficient, and fast. Prices are customized based on demand.

ragobble is a platform that uses artificial intelligence to convert audio files into documents. By converting online video and audio information into vectorizable RAG documents, users can apply the generated documents to their LLM instances or servers to provide their models with the latest knowledge. Ragobble provides a fast and easy way to convert video audio into documents, allowing users to feed models with up-to-date information that can infer data recorded only seconds ago.

KPU (Knowledge Processing Unit) is a proprietary rich framework that leverages the power of large language models and separates inference and data processing in an open system capable of solving complex tasks. It consists of three main components: inference engine, execution engine and virtual context window. The inference engine is responsible for designing step-by-step plans to solve user tasks, leveraging large pluggable language models (currently extensively tested with GPT-4 Turbo). The execution engine receives commands from the inference engine and executes them, and the results are sent back to the inference engine as feedback for re-planning. The virtual context window manages data and information input and output between the inference engine and the execution engine. This architecture that separates reasoning and execution allows large language models to focus on reasoning, avoiding pitfalls such as lying, data processing, or retrieving the latest information. KPU aims to improve task quality and performance and solve challenges such as large data volume, multi-modal content, open problem solving and interactivity.

Aipify is the best choice for your AI powered API needs. With Aipify, you get structured responses, powerful performance, and secure, fast, affordable, scalable access to the latest AI models, including GPT-4, to enhance your application capabilities.

This project focuses on realizing real-time full-body human-to-humanoid teleoperation, aiming to control the robot by learning human movements and behaviors.

Answer.AI is committed to developing practical end-user products through breakthroughs in basic research. The lab released an open source system based on FSDP and QLoRA that allows users to train a 7 billion parameter language model at home using two 24GB GPUs. In addition, Answer.AI also publishes historical analysis articles about the greatest R&D laboratories in history, as well as an introduction to the laboratory’s research agenda and background.

Qualcomm AI Hub provides AI models optimized and verified by Qualcomm, supporting multiple devices and platforms. All models are optimized for hardware acceleration of Qualcomm AI Engine, utilizing all computing cores of CPU, GPU and NPU.

iGOT.ai is a zero-coding GPT development platform that helps users build, define, explore and execute GPT models without programming, simplifying the creation of AI engines. It provides an intuitive interface where users can describe problems and solutions through natural language, and the platform will automatically convert them into reasoning objects that GPT can understand, then execute the task and review the results to ensure optimal output. The main functions include statement exploration, reasoning object creation, user testing, LLM task execution, etc. It is suitable for enterprise users in various industries who automate professional knowledge.

Athina AI is a tool for monitoring and debugging LLM (Large Language Model) models. It can help you discover and fix hallucinations and errors of LLM models in production environments, and provide detailed analysis and improvement suggestions. Athina AI supports multiple LLM models and can configure customized evaluations to meet different usage scenarios. You can use Athina AI to detect incorrect output, analyze cost and accuracy, debug model output, explore conversation content, and compare the performance of different models.

Ramen AI is a modern toolset for building, testing, and deploying LLM-based content classification applications. It provides a complete AI toolset that allows you to easily build, evaluate, deploy and monitor content classification. Ramen AI supports flexible classification management for instant testing for fast and accurate results. It also provides multiple classification methods to choose the best classification method for you. You can also use Ramen AI’s API to integrate classification applications into your code, and even use Ramen AI’s formulas in Google Sheets. Ramen AI also provides AI-generated test data sets, saving time on manually generating verification data sets. It can also monitor and report on category application usage to help you understand changing trends. Ramen AI is suitable for various classification application scenarios, including medical, financial, retail, legal, customer service, education and research, etc.

Lumino is a machine learning model training platform that can reduce costs by 50-70%. Users can train machine learning models on its extensive network of computing resources, which can also be provisioned. The platform significantly reduces costs by cutting out middlemen (such as AWS, GCP, and Azure) and connecting directly to computing resource providers. All models and training sets are traceable to cryptographically verified evidence, enabling complete accountability. In addition, Lumino adopts a decentralized and permissionless network structure to prevent centralized cloud platforms and authoritarian states from abusing their power.

Together AI provides the fastest and most efficient tools and infrastructure to help users build general-purpose AI models. Work with our dedicated AI team dedicated to your success.

BafCloud is an integrated cloud platform that simplifies the AI ​​development process. We provide single API access to a wide range of AI models and agents. You can easily manage, tune, and deploy large-scale language models using a user-friendly interface. You can quickly build custom AI agents for any use case, ensuring seamless integration and collaboration. Join BafCloud to accelerate brainstorming, building, integrating and deploying AI projects.

Appen is a company that provides professional tools and expertise to build a better future. Our products help customers build innovative artificial intelligence applications and provide high-quality data annotation, data collection and data processing services. Our strengths are extensive experience, flexible solutions and reliable partnerships. Our pricing is based on the complexity and size of the project. Appen is positioned to be the preferred partner for innovative world-class AI applications.

XSpecs is an AI-driven, single-source software platform that generates clear specifications from high-level requirements and deploys them directly as GraphQL native backend code, enabling weeks of software development to be completed in hours. It helps development teams deliver high-quality software faster.

Algomax simplifies the evaluation of LLM and RAG models, optimizes tip development, and provides unique insights into qualitative metrics through intuitive dashboards. Our evaluation engine accurately evaluates LLMs and ensures reliability through extensive testing. The platform provides comprehensive qualitative and quantitative metrics to help you better understand the behavior of your model and provide specific suggestions for improvement. Algomax has a wide range of uses and is suitable for various industries and fields.

Llog is an end-to-end platform for collaborative monitoring of LLM applications, providing teams with insights into how their LLM applications are performing post-production. Team members can review logs, mark important items, and assign tasks in one collaborative space. No matter the size of your team, enjoy unlimited seat support at any price tier. Gain a complete understanding of end-user behavior by directly observing user interactions and never worry about what the LLM is actually saying. Use our simple format, make a few API requests and see results instantly on our platform.

Openlayer is an evaluation tool for your development and production pipeline, helping you publish high-quality models with confidence. It provides powerful testing, evaluation, and observability, taking the guesswork out of whether your prompts are good enough. Supports LLMs, text classification, table classification, table regression and other functions. Get notified when your AI model fails with real-time notifications, allowing you to release with confidence.

Klu is an all-in-one LLM application platform that can quickly build, evaluate and optimize applications based on LLM technology on Klu. It provides a wide selection of state-of-the-art LLM models, allowing users to select and adjust according to their needs. Klu also supports team collaboration, version management, data evaluation and other functions, providing a comprehensive and convenient development platform for AI teams.

Pulze.ai is a one-stop LLM development automation platform that provides a single API to plug all the best LLM into your products and streamline your LLM feature development in minutes. Pulze.ai's API follows LLMOps best practices and makes it easy for your team to use. Pulze.ai allows you to test all your best models at once to speed up development. You can dynamically control budget and cost targets within Pulze.ai and protect your profits as you scale. Pulze.ai also provides enterprise-grade security to manage data privacy and security of all user data. Pulze.ai provides multiple function points, such as uploading data sources, optimizing results, one-click deployment, real-time tracking and version control, etc.

GPTs Hunt is a platform for users to find GPTs (Generative Adversarial Networks) suitable for various needs. It provides a variety of GPT models for users to choose from, including OpenAI's ChatGPT4 and DALLE3, etc. Users can browse different GPT models according to their needs, learn about their functions, advantages, pricing, positioning and other information, and choose the GPT model that best suits them.

Replicate is a tool for running and deploying machine learning models. There is no need to configure the environment yourself, and you can quickly run and deploy machine learning models. Replicate provides a Python library and API interface to support running and querying models. The community has shared thousands of available machine learning models, covering multiple fields such as text understanding, video editing, and image processing. Using Replicate and related tools, you can quickly build your own projects and deploy them.

Qlik AutoML is a tool that provides code-free, automated machine learning for analytics teams. It can quickly generate models, make predictions and decision planning. Users can easily create machine learning experiments, identify key factors in data and train models. At the same time, it also supports fully explainable AI that can demonstrate the cause and impact of predictions. Users can publish or integrate data directly into Qlik Sense applications for fully interactive analysis and simulations.

Aporia is an ML model management observability platform that monitors your ML models through a comprehensive dashboard to ensure optimal machine learning model performance. It provides features such as explainability, monitoring, root cause analysis, LLM observability, Gen AI, and Guardrails. Aporia's platform is powerful and supports features such as data integration, customization, big data support, and security and privacy.

CentML is an efficient and cost-effective AI model training and deployment platform. By using CentML, you can improve GPU efficiency, reduce latency, increase throughput, and achieve cost-effective and powerful computing performance.

Data Sherlocks is a powerful data analysis and generative AI tool that helps users discover the potential of data and provide their own generative AI models. It offers a variety of features and benefits, including data visualization, model training, generating AI applications, and more. Pricing is flexible and suitable for individual and business users.

Contentable.ai is a comprehensive AI model testing platform that helps users quickly test, prototype and share AI models. It provides a complete set of tools and features that enable users to easily build and deploy AI models, thereby increasing work efficiency.

promptfoo is a library for evaluating LLM prompt quality and testing. It helps you create test cases, set evaluation metrics, and integrate with existing testing and CI processes. promptfoo also provides a web viewer that allows you to easily compare different prompts and model outputs. It is used in LLM applications serving over 10 million users.

Parea AI is an LLM platform that helps developers improve the performance of LLM applications through rigorous testing and version control. It provides functions such as experimenting with different prompt versions, evaluating and comparing prompts for different test cases, one-click optimization prompts, and sharing. With Parea, you can optimize your AI development workflow and increase productivity.

Lepton AI is a developer-centered AI platform that provides efficient, scalable, and minute-level AI applications. It helps users build and run AI applications in less than minutes without worrying about infrastructure and scale issues. The strength of Lepton AI is its ease of use, scalability, and flexibility, making it the AI ​​platform of choice for developers and enterprises. Pricing plans are flexible and suitable for users of different sizes and needs.

Domino Data Lab is a unified, collaborative, and controlled end-to-end enterprise-level AI platform. The platform can build, deploy and manage AI models in any environment, and access data, tools, calculations and projects in any environment. Domino Data Lab helps enterprises accelerate AI applications and expand AI scale while ensuring governance and reducing costs by establishing best practices, tracking models in production, and strengthening governance.

DataRobot is an open AI platform for enterprises that supports comprehensive AI lifecycle management, including automatic machine learning, model monitoring, and AI control. The platform supports scalable and reproducible AI in cloud and hybrid environments, and can be applied to predictive modeling and generative AI in various industries, helping enterprises quickly implement AI and generate value.

AutoDL provides you with professional GPU rental services, second-level billing, stable and easy to use, high-standard computer rooms, and 7×24 hours service. You can flexibly deploy AI models to achieve shocking launches, and also provide an algorithm reproduction community to reproduce classic algorithms with one click.

The 4D Era artificial intelligence technology open platform provides digital services such as small object modeling, large scene modeling, SLAM visual tracking, and artificial intelligence visual recognition through deep learning algorithms to achieve efficient connection between the digital world and the physical world.

Pezzo is a developer-first LLMOps platform that delivers impactful AI-based software in minutes without compromising on quality. Deliver, monitor, test and iterate seamlessly without distractions. Pezzo is packed with powerful features to speed up your AI operations and let you focus on what matters.

Query Vary provides developers with the tools to design, test, and optimize queries to ensure reliability, reduce latency, and optimize costs. It has powerful features, including comparing different LLM models, tracking cost, latency and quality, version control tips, embedding tuned LLM directly into JavaScript, and more. Query Vary is suitable for individual developers, startups, and large enterprises, and offers flexible pricing plans.

Abacus.AI is the world's first end-to-end AI platform, enabling real-time large-scale deep learning for common enterprise application scenarios. Through our advanced MLOps platform, you can use your own models or use our neural network technology to create highly accurate models and operate them in a variety of application scenarios, including prediction, personalization, vision, anomaly detection, NLP and more.

ModularMind is a no-code AI builder that provides powerful artificial intelligence capabilities, including natural language processing, image recognition, machine learning, and more. It can help users quickly build AI models without coding. ModularMind also offers flexible pricing plans for individual and enterprise users. It is positioned to help users solve AI development problems and improve work efficiency.

Gretel.ai is a synthetic data platform built for developers. By using Gretel's API, you can generate anonymous and secure synthetic data to innovate faster while protecting privacy. Gretel.ai makes generating synthetic data simple and easy by training generative AI models, validating quality and privacy scores for models and use cases, and generating the amount of data you need on demand. Gretel's Python library allows you to generate synthetic data within a few lines of code. You can also use the Gretel console to start generating synthetic data without writing code.

AI Studio provides enterprise-level AI and machine learning tools to help enterprises carry out digital transformation, apply insights in real time, and assist important business decisions.

Data Scientist Assistant is your complete MLOps, monitoring and AI quality and governance solution. It automatically detects changes and trends in accuracy, data size, model drift, runtime, scheduling, and more. By providing a unified view and key metrics, you can gain complete visibility into your machine learning environment. It also tracks and monitors model performance and data drift to quickly identify accuracy degradation and data quality changes. No need to set up or wait for infrastructure configuration, with simple code integration you have complete control over what you send. You can configure custom alerts and notifications, as well as visualize trends and correlations between projects. Become an alpha user and get free access.