Alternatives to NVIDIA Picasso

YandexART, a diffusion neural net by Yandex, is designed for image and videos creation. This new neural model is a global leader in image generation quality among generative models. It is integrated into Yandex's services, such as Yandex Business or Shedevrum. It generates images and video using the cascade diffusion technique. This updated version of the neural network is already operational in the Shedevrum app, improving user experiences. YandexART, the engine behind Shedevrum, boasts a massive scale with 5 billion parameters. It was trained on a dataset of 330,000,000 images and their corresponding text descriptions. Shedevrum consistently produces high-quality content through the combination of a refined dataset with a proprietary text encoding algorithm and reinforcement learning.

Your ML model can be served in minutes in any cloud. Unified model packaging format that allows online and offline delivery on any platform. Our micro-batching technology allows for 100x more throughput than a regular flask-based server model server. High-quality prediction services that can speak the DevOps language, and seamlessly integrate with common infrastructure tools. Unified format for deployment. High-performance model serving. Best practices in DevOps are incorporated. The service uses the TensorFlow framework and the BERT model to predict the sentiment of movie reviews. DevOps-free BentoML workflow. This includes deployment automation, prediction service registry, and endpoint monitoring. All this is done automatically for your team. This is a solid foundation for serious ML workloads in production. Keep your team's models, deployments and changes visible. You can also control access via SSO and RBAC, client authentication and auditing logs.

NVIDIA GPU Cloud is a GPU-accelerated cloud platform that is optimized for scientific computing and deep learning. NGC is responsible for a catalogue of fully integrated and optimized deep-learning framework containers that take full benefit of NVIDIA GPUs in single and multi-GPU configurations.

Text can be converted into images, audio and video. Upload your own data for custom models. Upload images to train your personal custom model. Text descriptions can be used to generate videos and animations. Choose from creative, structured anime, or photorealistic designs. Most advanced pixel-art generative algorithm.

Explore the full range of AI APIs for image, audio, video and LLM applications. Novita AI offers model hosting and training to help you elevate your AI-driven company at the pace of technology. Access 100+ APIs including AI image creation & editing with 10,000+ model, and training APIs to create custom models. Pay-as you-go pricing allows you to build your own products without worrying about GPU maintenance. With a single click, you can generate images in just 2 seconds from more than 10000 models. Updated models include civitai, hugging faces and updated models. Novita API allows you to offer a variety of products. You can integrate Novita API into your own products.

The NVIDIA GPU Optimized AMI is a virtual image that accelerates your GPU-accelerated Machine Learning and Deep Learning workloads. This AMI allows you to spin up a GPU accelerated EC2 VM in minutes, with a preinstalled Ubuntu OS and GPU driver. Docker, NVIDIA container toolkit, and Docker are also included. This AMI provides access to NVIDIA’s NGC Catalog. It is a hub of GPU-optimized software for pulling and running performance-tuned docker containers that have been tested and certified by NVIDIA. The NGC Catalog provides free access to containerized AI and HPC applications. It also includes pre-trained AI models, AI SDKs, and other resources. This GPU-optimized AMI comes free, but you can purchase enterprise support through NVIDIA Enterprise. Scroll down to the 'Support information' section to find out how to get support for AMI.

There are options for every business to train deep and machine learning models efficiently. There are AI accelerators that can be used for any purpose, from low-cost inference to high performance training. It is easy to get started with a variety of services for development or deployment. Tensor Processing Units are ASICs that are custom-built to train and execute deep neural network. You can train and run more powerful, accurate models at a lower cost and with greater speed and scale. NVIDIA GPUs are available to assist with cost-effective inference and scale-up/scale-out training. Deep learning can be achieved by leveraging RAPID and Spark with GPUs. You can run GPU workloads on Google Cloud, which offers industry-leading storage, networking and data analytics technologies. Compute Engine allows you to access CPU platforms when you create a VM instance. Compute Engine provides a variety of Intel and AMD processors to support your VMs.

Generative AI has a profound impact on virtually every industry. It opens up new opportunities for creative workers and knowledge to solve the world's most pressing problems. NVIDIA is empowering generative AI with a powerful suite of cloud services, pretrained foundation models, cutting-edge frameworks and optimized inference engines. NVIDIA AI Foundations is an array of cloud services that enable customization across use cases in areas like text (NVIDIA NeMo™, NVIDIA Picasso), or biology (NVIDIA BIONeMo™. Enjoy the full potential of NeMo, Picasso and BioNeMo cloud-based services powered by NVIDIA DGX™ Cloud, an AI supercomputer. Marketing copy, storyline creation and global translation in many different languages. News, email, meeting minutes and information synthesis.

Generate AI images. AI can be used to improve your workday by creating custom workflows and training AI on your images. Finally, a great API for training & running custom AI models on a large scale! Add any repetitive task to a workflow and run it in just 2 clicks. Our simple interface allows you to train, experiment, and manage integrations. Upload your creative assets to generate more content or to explore the AI capabilities. Create templates that your team can use.

Nebula enables you to scale and deploy your AI projects quickly and easily2 on a highly robust GPU infrastructure. Nebula Cloud powered by Nvidia GPUs on demand allows you to train and infer models easily and securely. You can also create and manage containerized workloads using Nebula's easy-to-use orchestration layer. Access Nebula’s MLOps, low-code/no code engines and AI-powered applications to quickly and seamlessly deploy AI-powered apps for business teams. Choose from the Nebula containerized AI Cloud, your on-prem or any cloud. The Nebula Unify platform allows you to build and scale AI-enabled use cases for business in a matter weeks, not months.

NVIDIA AI Enterprise is the software layer of NVIDIA AI Platform. It accelerates the data science pipeline, streamlines development and deployments of production AI including generative AI, machine vision, speech AI, and more. NVIDIA AI Enterprise has over 50 frameworks, pre-trained models, and development tools. It is designed to help enterprises get to the forefront of AI while simplifying AI to make it more accessible to all. Artificial intelligence and machine learning are now mainstream and a key part of every company's competitive strategy. Enterprises face the greatest challenges when it comes to managing siloed infrastructure in the cloud and on-premises. AI requires that their environments be managed as a single platform and not as isolated clusters of compute.

Platform with NVIDIA H100 Tensor core GPUs. Competitive pricing. Support from a dedicated team. Built for large-scale ML workloads. Get the most from multihost training with thousands of H100 GPUs in full mesh connections using the latest InfiniBand networks up to 3.2Tb/s. Best value: Save up to 50% on GPU compute when compared with major public cloud providers*. You can save even more by purchasing GPUs in large quantities and reserving GPUs. Onboarding assistance: We provide a dedicated engineer to ensure smooth platform adoption. Get your infrastructure optimized, and k8s installed. Fully managed Kubernetes - Simplify the deployment and scaling of ML frameworks using Kubernetes. Use Managed Kubernetes to train GPUs on multiple nodes. Marketplace with ML Frameworks: Browse our Marketplace to find ML-focused libraries and applications, frameworks, and tools that will streamline your model training. Easy to use. All new users are entitled to a one-month free trial.

NVIDIA Triton™, an inference server, delivers fast and scalable AI production-ready. Open-source inference server software, Triton inference servers streamlines AI inference. It allows teams to deploy trained AI models from any framework (TensorFlow or NVIDIA TensorRT®, PyTorch or ONNX, XGBoost or Python, custom, and more on any GPU or CPU-based infrastructure (cloud or data center, edge, or edge). Triton supports concurrent models on GPUs to maximize throughput. It also supports x86 CPU-based inferencing and ARM CPUs. Triton is a tool that developers can use to deliver high-performance inference. It integrates with Kubernetes to orchestrate and scale, exports Prometheus metrics and supports live model updates. Triton helps standardize model deployment in production.

You can quickly provision a VM with everything you need for your deep learning project on Google Cloud. Deep Learning VM Image makes it simple and quick to create a VM image containing all the most popular AI frameworks for a Google Compute Engine instance. Compute Engine instances can be launched pre-installed in TensorFlow and PyTorch. Cloud GPU and Cloud TPU support can be easily added. Deep Learning VM Image supports all the most popular and current machine learning frameworks like TensorFlow, PyTorch, and more. Deep Learning VM Images can be used to accelerate model training and deployment. They are optimized with the most recent NVIDIA®, CUDA-X AI drivers and libraries, and the Intel®, Math Kernel Library. All the necessary frameworks, libraries and drivers are pre-installed, tested and approved for compatibility. Deep Learning VM Image provides seamless notebook experience with integrated JupyterLab support.

LensGo is an AI-powered image and video creation tool. LensGo is the best tool for creating personalized videos.

NVIDIA Base Command™, Platform is a software platform for enterprise-class AI training. It enables businesses and data scientists to accelerate AI developments. Base Command Platform is part of NVIDIA DGX™. It provides centralized, hybrid management of AI training projects. It can be used with NVIDIA DGX Cloud or NVIDIA DGX SUPERPOD. The Base Command Platform is combined with NVIDIA-accelerated AI infrastructure to provide a cloud-hosted solution that allows users to avoid the overheads and pitfalls of setting up and maintaining a do it yourself platform. Base Command Platform efficiently configures, manages, and executes AI workloads. It also provides integrated data management and executions on the right-sized resources, whether they are on-premises or cloud. The platform is continuously updated by NVIDIA's engineers and researchers.

Hyperstack, the ultimate self-service GPUaaS Platform, offers the H100 and A100 as well as the L40, and delivers its services to the most promising AI start ups in the world. Hyperstack was built for enterprise-grade GPU acceleration and optimised for AI workloads. NexGen Cloud offers enterprise-grade infrastructure for a wide range of users from SMEs, Blue-Chip corporations to Managed Service Providers and tech enthusiasts. Hyperstack, powered by NVIDIA architecture and running on 100% renewable energy, offers its services up to 75% cheaper than Legacy Cloud Providers. The platform supports diverse high-intensity workloads such as Generative AI and Large Language Modeling, machine learning and rendering.

VideoPoet, a simple modeling technique, can convert any large language model or autoregressive model into a high quality video generator. It is composed of a few components. The autoregressive model learns from video, image, text, and audio modalities in order to predict the next audio or video token in the sequence. The LLM training framework introduces a mixture of multimodal generative objectives, including text to video, text to image, image-to video, video frame continuation and inpainting/outpainting, styled video, and video-to audio. Moreover, these tasks can be combined to provide additional zero-shot capabilities. This simple recipe shows how language models can edit and synthesize videos with a high level of temporal consistency.

Arting.ai's AI creation tool is easy to use and will help you get your creative juices flowing. • Get started quickly using a simple, intuitive interface. • Supports the generation of visual effects using text descriptions, voice and other forms. • Create your own artistic masterpieces in just seconds. • Low cost and free. • Unlimited creations without restrictions on images or videos. You can get the photos, videos, and audios you want quickly, at a low cost, with high efficiency. -AI Image Generator: Turn your ideas into any image. -AI video creator: convert speech into videos. -AI celebrity Voice Generator: Create fun and high quality audio clips.

Amazon SageMaker lets you identify raw data, such as images, text files and videos. You can also add descriptive labels to generate synthetic data and create high-quality training data sets to support your machine learning (ML). SageMaker has two options: Amazon SageMaker Ground Truth Plus or Amazon SageMaker Ground Truth. These options allow you to either use an expert workforce or create and manage your data labeling workflows. data labeling. SageMaker GroundTruth allows you to manage and create your data labeling workflows. SageMaker Ground Truth, a data labeling tool, makes data labeling simple. It also allows you to use human annotators via Amazon Mechanical Turk or third-party providers.

Upload your photo and type in a vision. Watch as our AI transforms it into artwork. Retouch your photos with our magic editing feature. Select any part of your image and customize it to perfection. Gencraft will create a unique video for you within seconds by simply providing a prompt. Gencraft will create high-resolution images for you by simply providing a prompt and choosing from our beautiful styles. Visualize new ideas with keywords that inspire you. Then, watch your words come alive. Find your voice and create a content that represents you. Share your creations with the world.

Our AI is trained on top-performing copy from top brands. It can convert and generate content that resonates well with your audience. You can generate endless social media content free of cost: ideas, posts and tweets, captions as well as scripts, scripts and outlines, hashtags. Talking photos, shorts and reels are all just a click away. You can track performance and make data-driven decisions. Never miss a bear. Maximize your reach and engagement. AI can generate an image for you and make it speak or you can use one of our 100+ AI human avatars. You can add background music and subtitles.

Designed to create brilliant visuals for marketing in minutes. With a single click, you can create hundreds of videos and images. Simplify your content creation workflow. Bestever streamlines the creative process and allows you to focus on your ideas. We know that there is no one-size-fits-all solution. Easily tailor content for all your social media platforms. Create content for multiple aspect ratios simultaneously. You can refine and iterate your content until it perfectly reflects your vision.

Krater.ai is a user-friendly and comprehensive platform that provides a range of AI-powered tools and services, making it a powerful alternative to all the major AI services, tools, and apps. With Krater.ai, you can access all these tools and services in one convenient location, eliminating the need to switch between multiple apps and accounts that require different logins and pricing plans. Our AI-powered tool and templates enable you to generate 100% plagiarism-free content in seconds. You can be sure that your content is always original, allowing you to focus on creating high-quality content that resonates with your audience. Krater.ai offers competitive pricing plans that are tailored to meet your specific requirements. Whether you're a marketer, content creator, or small business owner, we have a pricing plan that suits your needs. Additionally, we have a free plan that you can try out without the need for a credit card.

D-I-Y can be used in certain situations, such as weed control. It's a different story to build your AI infrastructure. ONTAP AI consolidates the data center's worth in analytics, training, inference computation, and training into one, 5-petaflop AI system. NetApp ONTAP AI is powered by NVIDIA's DGX™, and NetApp's cloud-connected all flash storage. This allows you to fully realize the promise and potential of deep learning (DL). With the proven ONTAP AI architecture, you can simplify, accelerate and integrate your data pipeline. Your data fabric, which spans from the edge to the core to the cloud, will streamline data flow and improve analytics, training, inference, and performance. NetApp ONTAPAI is the first converged infrastructure platform to include NVIDIA DGX A100 (the world's first 5-petaflop AIO system) and NVIDIA Mellanox®, high-performance Ethernet switches. You get unified AI workloads and simplified deployment.

The world's first AI supercomputer in the cloud, NVIDIA DGX™ Cloud is an AI-training-as-a-service solution with integrated DGX infrastructure designed for the unique demands of enterprise AI. NVIDIA DGX Cloud allows businesses to access a combination software-infrastructure solution for AI training. It includes a full-stack AI development suite, a leadership-class infrastructure and concierge support. Businesses can get started immediately with predictable, all in-one pricing.

It supports high-performance learning on AWS Trainium based Amazon Elastic Compute Cloud Trn1 instances. It supports low-latency and high-performance inference for model deployment on AWS Inferentia based Amazon EC2 Inf1 and AWS Inferentia2-based Amazon EC2 Inf2 instance. Neuron allows you to use popular frameworks such as TensorFlow or PyTorch and train and deploy machine-learning (ML) models using Amazon EC2 Trn1, inf1, and inf2 instances without requiring vendor-specific solutions. AWS Neuron SDK is natively integrated into PyTorch and TensorFlow, and supports Inferentia, Trainium, and other accelerators. This integration allows you to continue using your existing workflows within these popular frameworks, and get started by changing only a few lines. The Neuron SDK provides libraries for distributed model training such as Megatron LM and PyTorch Fully Sharded Data Parallel (FSDP).

Launch GPU-accelerated instances that are highly configurable for your AI workload and budget. Reserve thousands of GPUs for training and inference in a next generation AI data center. The AI world is moving to GPU clouds in order to build and launch groundbreaking models without having the hassle of managing infrastructure or scarcity of resources. AI-centric cloud providers are outperforming traditional hyperscalers in terms of availability, compute costs, and scaling GPU utilization for complex AI workloads. Ori has a large pool with different GPU types that are tailored to meet different processing needs. This ensures that a greater concentration of powerful GPUs are readily available to be allocated compared to general purpose clouds. Ori offers more competitive pricing, whether it's for dedicated servers or on-demand instances. Our GPU compute costs are significantly lower than the per-hour and per-use pricing of legacy cloud services.

The RAPIDS software library, which is built on CUDAX AI, allows you to run end-to-end data science pipelines and analytics entirely on GPUs. It uses NVIDIA®, CUDA®, primitives for low level compute optimization. However, it exposes GPU parallelism through Python interfaces and high-bandwidth memories speed through user-friendly Python interfaces. RAPIDS also focuses its attention on data preparation tasks that are common for data science and analytics. This includes a familiar DataFrame API, which integrates with a variety machine learning algorithms for pipeline accelerations without having to pay serialization fees. RAPIDS supports multi-node, multiple-GPU deployments. This allows for greatly accelerated processing and training with larger datasets. You can accelerate your Python data science toolchain by making minimal code changes and learning no new tools. Machine learning models can be improved by being more accurate and deploying them faster.

Barbara is the Edge AI Platform in the industry space. Barbara helps Machine Learning Teams, manage the lifecycle of models in the Edge, at scale. Now companies can deploy, run, and manage their models remotely, in distributed locations, as easily as in the cloud. Barbara is composed by: .- Industrial Connectors for legacy or next-generation equipment. .- Edge Orchestrator to deploy and control container-based and native edge apps across thousands of distributed locations .- MLOps to optimize, deploy, and monitor your trained model in minutes. .- Marketplace of certified Edge Apps, ready to be deployed. .- Remote Device Management for provisioning, configuration, and updates. More --> www. barbara.tech

Amazon SageMaker JumpStart can help you speed up your machine learning (ML). SageMaker JumpStart gives you access to pre-trained foundation models, pre-trained algorithms, and built-in algorithms to help you with tasks like article summarization or image generation. You can also access prebuilt solutions to common problems. You can also share ML artifacts within your organization, including notebooks and ML models, to speed up ML model building. SageMaker JumpStart offers hundreds of pre-trained models from model hubs such as TensorFlow Hub and PyTorch Hub. SageMaker Python SDK allows you to access the built-in algorithms. The built-in algorithms can be used to perform common ML tasks such as data classifications (images, text, tabular), and sentiment analysis.

Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).

Amazing AI tools, real-time collaboration, precision editing, & more. Your next-generation video creation tool. Video editing can be simplified by eliminating the repetitive, tedious, and time-consuming tasks. Pixel-perfect multitrack audio and video editing. Full controls, powerful editing tools, keyframe animations, and full control. Secure collaboration from anywhere in this world It's as simple as sharing a link to share your projects. This tool is mind-bending and allows you to remove any object from any video using just a few brush strokes. You can do more with your videos. You can speed up your workflows by using an ever-growing, robust set of video editing tools. Automate background noise removal from your audios. You can rest assured with built-in secure collaboration. It's easy to create teams and share your projects, assets, and compositions.

Kapwing is an online video and image editor that's suitable for both casual creators and professionals. Your entire team can create multimedia using this easy-to-use, collaborative and fast software. You can save time on tasks such as subtitling, creating collages, editing screencast videos and bug reports, annotation of images, and other tasks. This modern content creation suite will make your employees more productive.

Synthesys is at the forefront of developing algorithms for text-to-voice and commercial video. Imagine being able enhance your website explainer videos and product tutorials in minutes using a natural human voice. Synthesys Text to-Speech (TTS), and Synthesys Text to-Video (TTV), technology transform your script into dynamic and engaging media presentations. Clear, natural voiceovers add credibility and authority to your digital messages, creating a human connection between your brand and your customers. Synthesys AI voice generation can transform plain text into dynamic, engaging digital content.

We are ready to meet all your business needs, whether it is quick engineering, fine-tuning or training. The Together Inference API makes it easy to integrate your new model in your production application. Together AI's elastic scaling and fastest performance allows it to grow with you. To increase accuracy and reduce risks, you can examine how models are created and what data was used. You are the owner of the model that you fine-tune and not your cloud provider. Change providers for any reason, even if the price changes. Store data locally or on our secure cloud to maintain complete data privacy.

Karlo is a model that generates images from text prompts. It builds on OpenAI's unCLIP architecture, but goes a step beyond by enhancing the super-resolution standard model, allowing for intricate details to be recovered at a remarkable 256px resolution, all while minimising noise through a small number of denoising stages. We embarked on a lengthy training process to create Karlo. We started from the beginning, using a large dataset of 115 millions image-text pairs. This included COYO100M, CC3M and CC12M. For the Prior and Decoder components we used the power of ViT/L/14, an OpenAI CLIP text encoder. We made a significant change to the unCLIP implementation in order to optimize efficiency. We integrated the text encoder of ViT-L/14 into the decoder instead of using a trainable transform.

Akool allows marketing innovators and creators to create custom, engaging experiences. These experiences will engage people in the brand, converting them into loyal customers. Marketers and advertisers bombard consumers with messages. Instead of allowing them to immerse themselves in the brand, where they can feel invested and engaged, the product message will be pushed onto them, making advertising and shopping completely boring. Create videos in minutes using AI-generated voices and avatars. Watch your photos come to life with real human voices. Akool is only limited by your imagination. Customize the background of your product photos in seconds.

Kling is an advanced video-generation model with powerful video-generation capabilities. It allows users to create art videos quickly and easily. It can model complex time-space games and generate video content for a larger movement with a 3D joint attention mechanism. The model can produce video with 30 FPS in 2 minutes thanks to its efficient training infrastructure, extreme reason optimization, and scalable architecture. Kling's powerful modeling capabilities and self-research model can simulate physical characteristics in the real world, and generate videos that are in accordance with the laws of physics. Based on a deep knowledge of text-video meaning, it can translate a user's rich fantasy into a concrete image, fictional scenes which will not appear in real life.

Pixray is an image-generation system. It combines existing ideas, such as Perception Engines, which uses image augmentation and iteratively optimizes the images against a group of classifiers. CLIP-guided GAN imagery by Ryan Murdoch and Katherine Crowson, as well as modifications like CLIPDraw by Kevin Frans. Sampling Generative Networks offers useful ways to navigate latent space. Pixray can be used to create an image from a text prompt. Predictions are run on Nvidia T4 GPU hardware. Predictions are usually completed in 7 minutes. Based on the inputs, the predicted time for this model can vary greatly. pixray is a command-line utility and python library. Replicate is free to use, but you will be asked for your credit card information after a while. The prediction you run is charged by the second. The hardware on which the model is run will affect the price per second. Different models require different hardware.

One development environment for all data science workflows. Natively analyze your data without the need to switch between services. Data to training at scale Models can be built and trained 5X faster than traditional notebooks. Scale up model development using simple connectivity to Vertex AI Services. Access to data is simplified and machine learning is made easier with BigQuery Dataproc, Spark and Vertex AI integration. Vertex AI training allows you to experiment and prototype at scale. Vertex AI Workbench allows you to manage your training and deployment workflows for Vertex AI all from one location. Fully managed, scalable and enterprise-ready, Jupyter-based, fully managed, scalable, and managed compute infrastructure with security controls. Easy connections to Google Cloud's Big Data Solutions allow you to explore data and train ML models.

Fal is a serverless Python Runtime that allows you to scale your code on the cloud without any infrastructure management. Build real-time AI apps with lightning-fast inferences (under 120ms). You can start building AI applications with some of the models that are ready to use. They have simple API endpoints. Ship custom model endpoints that allow for fine-grained control of idle timeout, maximum concurrency and autoscaling. APIs are available for models like Stable Diffusion Background Removal ControlNet and more. These models will be kept warm for free. Join the discussion and help shape the future AI. Scale up to hundreds GPUs and down to zero GPUs when idle. Pay only for the seconds your code runs. You can use fal in any Python project simply by importing fal and wrapping functions with the decorator.

Optimize ML models with real-time training metrics capture and alerting when anomalies are detected. To reduce the time and costs of training ML models, stop training when the desired accuracy has been achieved. To continuously improve resource utilization, automatically profile and monitor the system's resource utilization. Amazon SageMaker Debugger reduces troubleshooting time from days to minutes. It automatically detects and alerts you when there are common errors in training, such as too large or too small gradient values. You can view alerts in Amazon SageMaker Studio, or configure them through Amazon CloudWatch. The SageMaker Debugger SDK allows you to automatically detect new types of model-specific errors like data sampling, hyperparameter value, and out-of bound values.

AWS Trainium, the second-generation machine-learning (ML) accelerator, is specifically designed by AWS for deep learning training with 100B+ parameter model. Each Amazon Elastic Comput Cloud (EC2) Trn1 example deploys up to sixteen AWS Trainium accelerations to deliver a low-cost, high-performance solution for deep-learning (DL) in the cloud. The use of deep-learning is increasing, but many development teams have fixed budgets that limit the scope and frequency at which they can train to improve their models and apps. Trainium based EC2 Trn1 instance solves this challenge by delivering a faster time to train and offering up to 50% savings on cost-to-train compared to comparable Amazon EC2 instances.

Dream Machine is a model AI that creates high quality, realistic video fast from text and image. It is a highly efficient and scalable transformer model that can be trained directly on videos to generate physically accurate, consistent, and eventful shots. Dream Machine is the first step in building a universal engine of imagination and is now available to everyone! Dream Machine is a video generator that produces videos at an incredible speed! 120 frames in 120s. Iterate faster and explore more ideas! Dream Machine creates 5s shots that have a smooth, realistic motion, cinematography and drama. Transform lifeless images into vibrant ones. Turn your snapshots into stories. Dream Machine is able to understand how people, animals and other objects interact with the physical universe. This allows you create videos with a great character consistency, and accurate physics.

SynapseAI, like our accelerator hardware, is designed to optimize deep learning performance and efficiency, but most importantly, for developers, it is also easy to use. SynapseAI's goal is to make it easier and faster for developers by supporting popular frameworks and model. SynapseAI, with its tools and support, is designed to meet deep-learning developers where they are -- allowing them to develop what and in the way they want. Habana-based processors for deep learning preserve software investments and make it simple to build new models. This is true both for training and deployment.

Unlock prices that are 3-5x higher than those of traditional clouds. FluidStack aggregates GPUs from data centres around the world that are underutilized to deliver the best economics in the industry. Deploy up to 50,000 high-performance servers within seconds using a single platform. In just a few days, you can access large-scale A100 or H100 clusters using InfiniBand. FluidStack allows you to train, fine-tune and deploy LLMs for thousands of GPUs at affordable prices in minutes. FluidStack unifies individual data centers in order to overcome monopolistic GPU pricing. Cloud computing can be made more efficient while allowing for 5x faster computation. Instantly access over 47,000 servers with tier four uptime and security through a simple interface. Train larger models, deploy Kubernetes Clusters, render faster, and stream without latency. Setup with custom images and APIs in seconds. Our engineers provide 24/7 direct support through Slack, email, or phone calls.

Machine learning has led to business and research breakthroughs in everything from network security to medical diagnosis. To make similar breakthroughs possible, we created the Tensor Processing unit (TPU). Cloud TPU is a custom-designed machine learning ASIC which powers Google products such as Translate, Photos and Search, Assistant, Assistant, and Gmail. Here are some ways you can use the TPU and machine-learning to accelerate your company's success, especially when it comes to scale. Cloud TPU is designed for cutting-edge machine learning models and AI services on Google Cloud. Its custom high-speed network provides over 100 petaflops performance in a single pod. This is enough computational power to transform any business or create the next breakthrough in research. It is similar to compiling code to train machine learning models. You need to update frequently and you want to do it as efficiently as possible. As apps are built, deployed, and improved, ML models must be trained repeatedly.

This model is based upon a multi-stage text to video generation diffusion model. It takes a text description and returns a video which matches the text description. Only English input is supported. This model is based upon a multi-stage text to video generation diffusion model. It takes a text description and returns a video which matches the text description. Only English input is supported. The text-to video generation diffusion model is composed of three sub-networks, namely: text feature extraction; text feature-to video latent-space diffusion model; and video latent-space to video visual-space. The model parameters are approximately 1.7 billion. Support English input. The model uses the Unet3D structure and achieves video generation by iteratively denoising the pure Gaussian video.

Google Cloud allows you to quickly build your deep learning project. You can quickly prototype your AI applications using Deep Learning Containers. These Docker images are compatible with popular frameworks, optimized for performance, and ready to be deployed. Deep Learning Containers create a consistent environment across Google Cloud Services, making it easy for you to scale in the cloud and shift from on-premises. You can deploy on Google Kubernetes Engine, AI Platform, Cloud Run and Compute Engine as well as Docker Swarm and Kubernetes Engine.