Alternatives to NVIDIA DeepStream SDK
Compare NVIDIA DeepStream SDK alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to NVIDIA DeepStream SDK in 2026. Compare features, ratings, user reviews, pricing, and more from NVIDIA DeepStream SDK competitors and alternatives in order to make an informed decision for your business.
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Qloo
Qloo
Qloo is the “Cultural AI”, decoding and predicting consumer taste across the globe. A privacy-first API that predicts global consumer preferences and catalogs hundreds of millions of cultural entities. Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things. Our technology empowers you to look beyond trends and uncover the connections behind people’s tastes in the world around them. Look up entities in our vast library spanning categories like brands, music, film, fashion, travel destinations, and notable people. Results are delivered within milliseconds and can be weighted by factors such as regionalization and real-time popularity. Used by companies who want to incorporate best-in-class data in their consumer experiences. Our flagship recommendation API delivers results based on demographics, preferences, cultural entities, metadata, and geolocational factors. -
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NVIDIA Holoscan
NVIDIA
NVIDIA® Holoscan is a domain-agnostic AI computing platform that delivers the accelerated, full-stack infrastructure required for scalable, software-defined, and real-time processing of streaming data running at the edge or in the cloud. Holoscan supports a camera serial interface and front-end sensors for video capture, ultrasound research, data acquisition, and connection to legacy medical devices. Use the NVIDIA Holoscan SDK’s data transfer latency tool to measure complete, end-to-end latency for video processing applications. Access AI reference pipelines for radar, high-energy light sources, endoscopy, ultrasound, and other streaming video applications. NVIDIA Holoscan includes optimized libraries for network connectivity, data processing, and AI, as well as examples to create and run low-latency data-streaming applications using either C++, Python, or Graph Composer. -
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Bright Cluster Manager
NVIDIA
NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous high-performance computing (HPC) and AI server clusters at the edge, in the data center, and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a couple of nodes to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and enables orchestration with Kubernetes. Heterogeneous high-performance Linux clusters can be quickly built and managed with NVIDIA Bright Cluster Manager, supporting HPC, machine learning, and analytics applications that span from core to edge to cloud. NVIDIA Bright Cluster Manager is ideal for heterogeneous environments, supporting Arm® and x86-based CPU nodes, and is fully optimized for accelerated computing with NVIDIA GPUs and NVIDIA DGX™ systems. -
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RoboMinder
RoboMinder
Comprehensive monitoring, in-depth analysis, and interactive insights with our multimodal LLM-based analytics tool. Unify multi-modal data like video, logs, sensor data, and documentation for a complete operational overview. Delve beyond symptoms to uncover the deep causes of incidents, enabling preventative strategies and robust solutions. Dive into data with interactive inquiries to understand and learn from past incidents. Get early access to the next-gen of robot analytics. -
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NVIDIA DIGITS
NVIDIA DIGITS
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting the best performing model from the results browser for deployment. DIGITS is completely interactive so that data scientists can focus on designing and training networks rather than programming and debugging. Interactively train models using TensorFlow and visualize model architecture using TensorBoard. Integrate custom plug-ins for importing special data formats such as DICOM used in medical imaging. -
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NVIDIA GPU-Optimized AMI
Amazon
The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions. This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'Starting Price: $3.06 per hour -
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NVIDIA DRIVE
NVIDIA
Software is what turns a vehicle into an intelligent machine. The NVIDIA DRIVE™ Software stack is open, empowering developers to efficiently build and deploy a variety of state-of-the-art AV applications, including perception, localization and mapping, planning and control, driver monitoring, and natural language processing. The foundation of the DRIVE Software stack, DRIVE OS is the first safe operating system for accelerated computing. It includes NvMedia for sensor input processing, NVIDIA CUDA® libraries for efficient parallel computing implementations, NVIDIA TensorRT™ for real-time AI inference, and other developer tools and modules to access hardware engines. The NVIDIA DriveWorks® SDK provides middleware functions on top of DRIVE OS that are fundamental to autonomous vehicle development. These consist of the sensor abstraction layer (SAL) and sensor plugins, data recorder, vehicle I/O support, and a deep neural network (DNN) framework. -
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Amazon EC2 G4 Instances
Amazon
Amazon EC2 G4 instances are optimized for machine learning inference and graphics-intensive applications. It offers a choice between NVIDIA T4 GPUs (G4dn) and AMD Radeon Pro V520 GPUs (G4ad). G4dn instances combine NVIDIA T4 GPUs with custom Intel Cascade Lake CPUs, providing a balance of compute, memory, and networking resources. These instances are ideal for deploying machine learning models, video transcoding, game streaming, and graphics rendering. G4ad instances, featuring AMD Radeon Pro V520 GPUs and 2nd-generation AMD EPYC processors, deliver cost-effective solutions for graphics workloads. Both G4dn and G4ad instances support Amazon Elastic Inference, allowing users to attach low-cost GPU-powered inference acceleration to Amazon EC2 and reduce deep learning inference costs. They are available in various sizes to accommodate different performance needs and are integrated with AWS services such as Amazon SageMaker, Amazon ECS, and Amazon EKS. -
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NVIDIA NGC
NVIDIA
NVIDIA GPU Cloud (NGC) is a GPU-accelerated cloud platform optimized for deep learning and scientific computing. NGC manages a catalog of fully integrated and optimized deep learning framework containers that take full advantage of NVIDIA GPUs in both single GPU and multi-GPU configurations. NVIDIA train, adapt, and optimize (TAO) is an AI-model-adaptation platform that simplifies and accelerates the creation of enterprise AI applications and services. By fine-tuning pre-trained models with custom data through a UI-based, guided workflow, enterprises can produce highly accurate models in hours rather than months, eliminating the need for large training runs and deep AI expertise. Looking to get started with containers and models on NGC? This is the place to start. Private Registries from NGC allow you to secure, manage, and deploy your own assets to accelerate your journey to AI. -
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NVIDIA DRIVE Map
NVIDIA
NVIDIA DRIVE® Map is a multi-modal mapping platform designed to enable the highest levels of autonomy while improving safety. It combines the accuracy of ground truth mapping with the freshness and scale of AI-based fleet-sourced mapping. With four localization layers—camera, lidar, radar, and GNSS—DRIVE Map provides the redundancy and versatility required by the most advanced AI drivers. DRIVE Map is designed for the highest level of accuracy, the ground truth map engine creates DRIVE Maps using rich sensors—cameras, radars, lidars, and differential GNSS/IMU—with NVIDIA DRIVE Hyperion data collection vehicles. It achieves better than 5 cm accuracy for higher levels of autonomy (L3/L4) in selected environments, such as highways and urban environments. DRIVE Map is designed for near real-time operation and global scalability. Based on both ground truth and fleet-sourced data, it represents the collective memory of millions of vehicles. -
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NVIDIA Metropolis
NVIDIA
NVIDIA Metropolis is an application framework, set of developer tools, and partner ecosystem that brings visual data and AI together to improve operational efficiency and safety across a broad range of industries. It helps make sense of the flood of data created by trillions of sensors for frictionless retail, streamlined inventory management, traffic engineering in smart cities, optical inspection on factory floors, patient care in healthcare facilities, and more. Businesses can now take advantage of this cutting-edge technology and the extensive Metropolis developer ecosystem to create, deploy, and scale AI and IoT applications from the edge to the cloud. Maintain and improve city infrastructure, parking spaces, buildings, and public services. Improve industrial inspection, increase productivity, and reduce waste on manufacturing lines. -
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NWarch AI
Daten And Wissen
Daten & Wissen (DPIIT-recognised; NVIDIA Inception partner) builds NWarch AI, an edge-first video analytics and automation platform that converts existing CCTV and sensor streams into real-time safety, crowd and operational intelligence. We solve fragmented video data, slow manual monitoring, and costly rip-and-replace upgrades by delivering plug-and-play edge inference, natural-language AI agents for on-demand queries, and zero-code automation workflows. Nwarch AI serves construction, manufacturing, logistics, retail and security - enabling faster incident response, automated compliance reports, and measurable efficiency gains.Starting Price: 500 per use case per month -
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NetApp AIPod
NetApp
NetApp AIPod is a comprehensive AI infrastructure solution designed to streamline the deployment and management of artificial intelligence workloads. By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and inference, while ensuring robust data management and security. With preconfigured infrastructure optimized for AI tasks, NetApp AIPod reduces complexity, accelerates time to insights, and supports seamless integration into hybrid cloud environments. -
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IBM Streams
IBM
IBM Streams evaluates a broad range of streaming data — unstructured text, video, audio, geospatial and sensor — helping organizations spot opportunities and risks and make decisions in real-time. Make sense of your data, turning fast-moving volumes and varieties into insight with IBM® Streams. Streams evaluate a broad range of streaming data — unstructured text, video, audio, geospatial and sensor — helping organizations spot opportunities and risks as they happen. Combine Streams with other IBM Cloud Pak® for Data capabilities, built on an open, extensible architecture. Help enable data scientists to collaboratively build models to apply to stream flows, plus, analyze massive amounts of data in real-time. Acting upon your data and deriving true value is easier than ever. -
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Amazon EC2 P5 Instances
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery. -
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Deepen
Deepen
Deepen AI offers advanced multi-sensor data labeling and calibration tools and services to accelerate computer vision training for autonomous vehicles, robotics, and more. Their annotation suite supports various key cases, including 2D and 3D bounding boxes, semantic and instance segmentation, polylines, and key points. The platform is AI-powered, featuring pre-labeling capabilities that can automatically label up to 80 common classes, improving productivity by seven times. It also includes machine learning-assisted segmentation, allowing users to segment objects with just a few clicks, and accurate object detection and tracking across frames to avoid duplicate efforts and save time. Deepen AI's calibration suite supports all key sensor types, such as LiDAR, camera, radar, IMU, and vehicle sensors. The tools enable seamless visualization and inspection of multi-sensor data integrity, and calculation of intrinsic and extrinsic calibration parameters in seconds. -
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Amazon EC2 P4 Instances
Amazon
Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.Starting Price: $11.57 per hour -
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Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. High computational power has been required to process neural networks due to the number of layers and the volumes of data to train the networks. Furthermore, businesses are struggling to show results from deep learning experiments implemented in silos.
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NVIDIA Run:ai
NVIDIA
NVIDIA Run:ai is an enterprise platform designed to optimize AI workloads and orchestrate GPU resources efficiently. It dynamically allocates and manages GPU compute across hybrid, multi-cloud, and on-premises environments, maximizing utilization and scaling AI training and inference. The platform offers centralized AI infrastructure management, enabling seamless resource pooling and workload distribution. Built with an API-first approach, Run:ai integrates with major AI frameworks and machine learning tools to support flexible deployment anywhere. It also features a powerful policy engine for strategic resource governance, reducing manual intervention. With proven results like 10x GPU availability and 5x utilization, NVIDIA Run:ai accelerates AI development cycles and boosts ROI. -
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Microsoft Cognitive Toolkit
Microsoft
The Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph. CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the toolkit from the source provided in GitHub. -
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Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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OGP ZONE3
OGP
ZONE3® Metrology Software represents a totally new way of working with multisensor measurement systems and provides faster, easier, and more productive measurements than ever before. Its interface clearly displays relationships between parts, sensors, datum alignments, and machine accessories. Truly sensor independent with full multisensor capability, including OGP’s most advanced sensor options, without the need to specify a primary sensor. Intelligent routine optimization makes sure steps are run as efficiently as possible by reducing machine movements and measuring features that can be seen at the same time simultaneously. Auto path generation uses CAD or user-entered nominals. -
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Parole
XFCE
Parole is a modern simple media player based on the GStreamer framework and written to fit well in the Xfce desktop. Parole features playback of local media files, DVD/CD, and live streams. Parole is extensible via plugins, for a complete how to write a plugin for Parole see the Plugins API documentation and the plugins directory which contains some useful examples. Parole is a modern simple media player based on the GStreamer framework and written to fit well in the Xfce desktop. It is designed with simplicity, speed, and resource usage in mind. Parole features playback of local media files, including a video with subtitles support, audio CDs, DVDs, and live streams. Parole is completely free, meaning anyone can use it, redistribute and/or modify it under the GNU general public license. GStreamer Base plugins comprises the base functionality of GStreamer and are required for normal operation. GStreamer Good plugins comprises a set of high quality plug-ins under the LGPL license.Starting Price: Free -
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Cerence
Cerence
The most powerful, most intelligent AI assistant solution for global mobility, Cerence offers a robust portfolio of products, services, toolkits, and innovations that brings tomorrow’s user experience to today’s mobility ecosystem. As the car of the future takes hold, Cerence leads the way with a new era of in-car assistants, a multi-modal, deeply integrated, proactive companion that accompanies drivers throughout their daily journeys, delivering effortless interaction that keeps drivers safe, comfortable, productive, and informed. Cerence Co-Pilot is a first-of-its-kind, multi-modal driving experience that transforms the automotive voice assistant into a proactive, intuitive, AI-powered companion that can support drivers like never before. Cerence Co-Pilot runs directly on a vehicle’s head unit, with advanced AI deeply integrated with car sensors and data to understand complex situations both inside the vehicle and around it. -
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SKY ENGINE AI
SKY ENGINE AI
SKY ENGINE AI is a fully managed 3D Generative AI platform that transforms how enterprises build Vision AI by producing high-quality synthetic data at scale. It replaces difficult, expensive real-world data collection with physics-accurate simulation, multispectrum rendering, and automated ground-truth generation. The platform integrates a synthetic data engine, domain adaptation tools, sensor simulators, and deep learning pipelines into a single environment. Teams can test hypotheses, capture rare edge cases, and iterate datasets rapidly using advanced randomization, GAN post-processing, and 3D generative blueprints. With GPU-integrated development tools, distributed rendering, and full cloud resource management, SKY ENGINE AI eliminates workflow complexity and accelerates AI development. The result is faster model training, significantly lower costs, and highly reliable Vision AI across industries. -
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FonePaw Video Converter Ultimate
FonePaw
Multifunctional software makes it possible for you to convert, edit and play videos, DVD and audios. In addition, you can also create you own videos or GIF image freely with it. You can convert one video at a time or add several video files for converting simultaneously. It can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. Your video will not be quality loss. Equipped with NVIDIA's CUDA and AMD APP acceleration technology, you're able to experience 6X faster conversion speed and supports multi-core processor completely. Supported with NVIDIA® CUDA™, AMD®, etc. technologies, FonePaw Video Converter Ultimate can decode and encode videos on a CUDA-enabled graphics card, leading to your fast and high quality HD and SD video conversion. This all-in-one video converter is capable of converting video, audio and DVD files efficiently and even editing them with better effect.Starting Price: $39 one-time payment -
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TFLearn
TFLearn
TFlearn is a modular and transparent deep learning library built on top of Tensorflow. It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorial and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations and more. The high-level API currently supports most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, PReLU, Residual networks, Generative networks. -
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Kallipr Kloud
Kallipr
Kallipr Kloud is an industrial IoT software platform that manages large-scale monitoring networks for water, wastewater, stormwater, environmental and industrial operations. It handles the full device lifecycle, from fast deployment with configuration templates to secure registration, remote updates and real-time diagnostics. The platform gives operators a complete view of their network with live insights, trend analysis and clear alarm management for issues like blockages, leaks and pressure changes. Kallipr Kloud integrates directly with Azure and can send data into existing SCADA, GIS or analytics tools without middleware. It is designed for scale, secure communications, long device life and high uptime. Used with Kallipr’s data loggers, radar sensors and multi-sensor gateways, it provides a fully integrated hardware and software stack for more than 300 organisations across Australia, New Zealand and the United States.Starting Price: $15 -
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Arena Autonomy OS
Arena
Arena empowers businesses across industries to make high-frequency, critical path decisions fully autonomous. Autopilot for high-frequency business decisions. Similar to a physical robot, Autonomy OS is composed of three components, the sensor, the brain, and the arm. The sensor measures, the brain makes decisions, and the arm takes action. The whole system operates automatically and in real time. Autonomy OS ingests and encodes heterogeneous data with different latency profiles, from streaming real-time and structured time series, to unstructured data like images and text, into features that train machine learning models. Autonomy OS also augments data with contextual data from Arena’s Demand Graph, a daily updating index of factors that affect consumer demand and supply, from product prices and availability by location, to demand proxies from social media platforms. Customer preferences and behaviors change, supply routes are unexpectedly disrupted, and competitors alter strategy. -
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SAS Event Stream Processing
SAS Institute
Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise. -
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Lambda
Lambda
Lambda provides high-performance supercomputing infrastructure built specifically for training and deploying advanced AI systems at massive scale. Its Superintelligence Cloud integrates high-density power, liquid cooling, and state-of-the-art NVIDIA GPUs to deliver peak performance for demanding AI workloads. Teams can spin up individual GPU instances, deploy production-ready clusters, or operate full superclusters designed for secure, single-tenant use. Lambda’s architecture emphasizes security and reliability with shared-nothing designs, hardware-level isolation, and SOC 2 Type II compliance. Developers gain access to the world’s most advanced GPUs, including NVIDIA GB300 NVL72, HGX B300, HGX B200, and H200 systems. Whether testing prototypes or training frontier-scale models, Lambda offers the compute foundation required for superintelligence-level performance. -
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Embiot
Telchemy
Embiot® is a compact, high performance IoT analytics software agent for IoT gateway and smart sensor applications. This edge computing application is small enough to integrate directly into devices, smart sensors and gateways, but powerful enough to calculate complex analytics from large amounts of raw data at high speed. Internally, Embiot uses a stream processing model to enable it to handle sensor data that arrives at different rates and out of order. It has a simple intuitive configuration language and a rich set of math, stats and AI functions making it fast and easy to solve your analytics problems. Embiot supports a range of input methods including MODBUS, MQTT, REST/XML, REST/JSON, Name/Value and CSV. Embiot is able to send output reports to multiple destinations concurrently in REST, MQTT and custom text formats. For security, Embiot supports TLS selectively on any input or output stream, HTTP and MQTT authentication. -
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Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. The FfDL platform uses a microservices architecture to reduce coupling between components, keep each component simple and as stateless as possible, isolate component failures, and allow each component to be developed, tested, deployed, scaled, and upgraded independently. Leveraging the power of Kubernetes, FfDL provides a scalable, resilient, and fault-tolerant deep-learning framework. The platform uses a distribution and orchestration layer that facilitates learning from a large amount of data in a reasonable amount of time across compute nodes.
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SAS Analytics for IoT
SAS Institute
Access, organize, select and transform IoT data with this complete, AI-embedded solution. SAS Analytics for IoT covers the entire Internet of Things analytics life cycle, providing streamlined, extensible ETL, a sensor-focused data model, advanced analytics, and an industry-leading streaming execution engine to perform multi-phase analytics. SAS Analytics for IoT is built on SAS® Viya® and runs in a fast, in-memory distributed environment. Learn how to build SAS Event Stream Processing applications that ingest high-volume and high-velocity data streams, respond in real time, and store only relevant data elements. This course covers basic concepts of event stream processing, including what component objects are available to build event stream processing applications. Curiosity is our code. SAS analytics solutions transform data into intelligence, inspiring customers around the world to make bold new discoveries that drive progress. -
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Zebra by Mipsology
Mipsology
Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application. Zebra computes neural networks at world-class speed, setting a new standard for performance. Zebra runs on highest-throughput boards all the way to the smallest boards. The scaling provides the required throughput, in data centers, at the edge, or in the cloud. Zebra accelerates any neural network, including user-defined neural networks. Zebra processes the same CPU/GPU-based trained neural network with the same accuracy without any change. -
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understand.ai
understand.ai
Understand.ai provides cutting-edge ground truth annotation technology to handle complexity at scale. Their state-of-the-art annotation platform is designed to manage complex ground truth annotation projects, featuring scalable infrastructure that effortlessly handles high data volumes and projects of any size. It excels in customized data elevation and workflows, tailored to meet specific project needs while prioritizing compliance with stringent data privacy and security standards. User-friendly tools enable streamlined collaboration between customers and labeling partners, and automation capabilities significantly reduce manual annotation efforts, making large-scale ADAS/AD programs commercially feasible. Key features include multi-sensor integration, allowing seamless incorporation and processing of data from multiple LiDAR sensors for a comprehensive view of complex 3D environments and precise annotation. -
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Caffe
BAIR
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU. -
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Tive
Tive
Cellular trackers and a cloud-based software platform enable real-time visibility into your shipment’s location and condition, from end to end. Our proprietary low-power multi-sensor tracker uses global cellular connectivity and on-board sensors to provide real-time monitoring of shipments so you are always aware of location, shipment integrity and climate. Create shipment profiles, set custom alerts, configure geofences, and use the Tive API to pull data into your SCM or ERP systems – Tive makes it easy to get the information you need, when you need it. -
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Build your deep learning project quickly on Google Cloud: Quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications with Deep Learning Containers. These Docker images use popular frameworks and are performance optimized, compatibility tested, and ready to deploy. Deep Learning Containers provide a consistent environment across Google Cloud services, making it easy to scale in the cloud or shift from on-premises. You have the flexibility to deploy on Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.
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AWS Deep Learning AMIs
Amazon
AWS Deep Learning AMIs (DLAMI) provides ML practitioners and researchers with a curated and secure set of frameworks, dependencies, and tools to accelerate deep learning in the cloud. Built for Amazon Linux and Ubuntu, Amazon Machine Images (AMIs) come preconfigured with TensorFlow, PyTorch, Apache MXNet, Chainer, Microsoft Cognitive Toolkit (CNTK), Gluon, Horovod, and Keras, allowing you to quickly deploy and run these frameworks and tools at scale. Develop advanced ML models at scale to develop autonomous vehicle (AV) technology safely by validating models with millions of supported virtual tests. Accelerate the installation and configuration of AWS instances, and speed up experimentation and evaluation with up-to-date frameworks and libraries, including Hugging Face Transformers. Use advanced analytics, ML, and deep learning capabilities to identify trends and make predictions from raw, disparate health data. -
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Segments.ai
Segments.ai
Segments.ai is an advanced data labeling platform that allows users to label data from multiple sensors simultaneously, improving the speed and accuracy of labeling for robotics and autonomous vehicle (AV) applications. It supports 2D and 3D labeling, including point cloud annotation, and enables users to label moving and stationary objects with ease. The platform leverages smart automation tools like batch mode and ML-powered object tracking, streamlining workflows and reducing manual labor. By fusing 2D image data with 3D point cloud data, Segments.ai offers a more efficient and consistent labeling process, ideal for high-volume, multi-sensor projects. -
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Deep Lake
activeloop
Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.Starting Price: $995 per month -
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Resi
Resi Media
Experience the most resilient all-in-one streaming solution with Resi. Automated live and on-demand streaming platform to your website, social media, mobile app and multiple simultaneous locations. Resi's technology is the first to be able to handle the problems of the public internet and results in exponentially more people being able to watch your stream without buffering wheels. The platform can overcome internet bottlenecks with zero video loss for uninterrupted playback. The Multisite Platform is a turnkey streaming solution designed from the ground up to deliver video to remote locations with unprecedented reliability and quality. The complete offering includes Multisite Encoders for realtime video capture, LAN and Cloud distribution for scalable delivery, Multisite Decoders for live/DVR playback, analytics and full weekend support. Stream at up to 4k UHD resolution through HDMI and SDI inputs. -
44
Unicorn Render
Unicorn Render
Unicorn Render is a professional rendering software that enables users to produce stunning realistic pictures and achieve high-end rendering levels without any prior skills. It offers a user-friendly interface designed to provide everything needed to obtain amazing results with minimal controls. Available as a standalone application or as a plugin, Unicorn Render integrates advanced AI technology and professional visualization tools. The software supports GPU+CPU acceleration through deep learning photorealistic rendering technology and NVIDIA CUDA technology, allowing joint support for CUDA GPUs and multicore CPUs. It features real-time progressive physics illumination, a Metropolis Light Transport sampler (MLT), a caustic sampler, and native NVIDIA MDL material support. Unicorn Render's WYSIWYG editing mode ensures that 100% of editing can be done in final image quality, eliminating surprises in the production of the final image. -
45
Agri-SCM
Agri-SCM
Agri-SCM can be used easily without any training required. Anyone can immediately use this solution with our user-friendly interface. Agri-SCM provides a way to collect data: voice recording, photo &video capture, sensor real-time data collecting, friendly select box, etc. An IoT system was integrated to create a real-time stream of input data by sensors. All farming conditions data will be sent automatically to analyze and predict models. Applying the techniques of Data Science, artificial intelligence, and machine learning, we are offering a system with smart insight to give users valuable reports of the farm and the compliance status.Starting Price: Free -
46
Neural Designer
Artelnics
Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.Starting Price: $2495/year (per user) -
47
VisionPro Deep Learning
Cognex
VisionPro Deep Learning is the best-in-class deep learning-based image analysis software designed for factory automation. Its field-tested algorithms are optimized specifically for machine vision, with a graphical user interface that simplifies neural network training without compromising performance. VisionPro Deep Learning solves complex applications that are too challenging for traditional machine vision alone, while providing a consistency and speed that aren’t possible with human inspection. When combined with VisionPro’s rule-based vision libraries, automation engineers can easily choose the best the tool for the task at hand. VisionPro Deep Learning combines a comprehensive machine vision tool library with advanced deep learning tools inside a common development and deployment framework. It simplifies the development of highly variable vision applications. -
48
Enlighted IoT
Enlighted
Applications from Enlighted and our partners improve operating efficiencies and occupant experiences, enhance productivity, and optimize resource and asset use. Sensors detect motion, temperature, and ambient light. Asset tags and badges communicate using Bluetooth with the sensors for calculating the location of assets and people. Room controls allow hands-on or automatic lighting adjustments. The most sophisticated software-defined sensor in the industry, capturing and combining multiple streams of data. The gateway relays data captured by the sensors to the energy manager for analysis and reporting. Occupants can override preset illumination levels and lighting configurations at the push of a button. -
49
Abacus.AI
Abacus.AI
Abacus.AI is the world's first end-to-end autonomous AI platform that enables real-time deep learning at scale for common enterprise use-cases. Apply our innovative neural architecture search techniques to train custom deep learning models and deploy them on our end to end DLOps platform. Our AI engine will increase your user engagement by at least 30% with personalized recommendations. We generate recommendations that are truly personalized to individual preferences which means more user interaction and conversion. Don't waste time in dealing with data hassles. We will automatically create your data pipelines and retrain your models. We use generative modeling to produce recommendations that means even with very little data about a particular user/item you won't have a cold start. -
50
Neuralhub
Neuralhub
Neuralhub is a system that makes working with neural networks easier, helping AI enthusiasts, researchers, and engineers to create, experiment, and innovate in the AI space. Our mission extends beyond providing tools; we're also creating a community, a place to share and work together. We aim to simplify the way we do deep learning today by bringing all the tools, research, and models into a single collaborative space, making AI research, learning, and development more accessible. Build a neural network from scratch or use our library of common network components, layers, architectures, novel research, and pre-trained models to experiment and build something of your own. Construct your neural network with one click. Visually see and interact with every component in the network. Easily tune hyperparameters such as epochs, features, labels and much more.
