Deci Description
Effortlessly create, refine, and deploy high-performing, precise models using Deci’s deep learning development platform, which utilizes Neural Architecture Search. Achieve superior accuracy and runtime performance that surpass state-of-the-art models for any application and inference hardware in no time. Accelerate your path to production with automated tools, eliminating the need for endless iterations and a multitude of libraries. This platform empowers new applications on devices with limited resources or helps reduce cloud computing expenses by up to 80%. With Deci’s NAS-driven AutoNAC engine, you can automatically discover architectures that are both accurate and efficient, specifically tailored to your application, hardware, and performance goals. Additionally, streamline the process of compiling and quantizing your models with cutting-edge compilers while quickly assessing various production configurations. This innovative approach not only enhances productivity but also ensures that your models are optimized for any deployment scenario.
Deci Alternatives
Vertex AI
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Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection.
Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.
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Titan
Partnering with Salesforce, Titan Forms and Apps are a game-changer in the industry, making the world’s number #1 CRM accessible, and effortless for anyone to use. At the touch of a button, and with zero code, experience strength, speed, and agility for Salesforce Forms and your business processes.
Slash time to market, nuke code, and tackle any use case on a single platform. Our best-of-breed forms and applications for Salesforce cater to any industry and it’s our mission to provide custom solutions for difficult problems.
Build beautiful web portals, sign documents, generate docs, send surveys, automate contracts, fill out Salesforce forms, and so much more in just a few simple clicks. No code required and with our new AI assistant you can build even faster and with fewer errors.
We are the only product on the market that empowers you to send data to Salesforce and pull it back in real-time without any development or added expense.
Our customers and partners are the heartbeat of Titan. If you need a feature, simply request it via our Titan X Lab and we will consider it for our roadmap!
So what’s stopping you? Schedule a demo today.
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Microsoft Cognitive Toolkit
The Microsoft Cognitive Toolkit (CNTK) is an open-source framework designed for high-performance distributed deep learning applications. It represents neural networks through a sequence of computational operations organized in a directed graph structure. Users can effortlessly implement and integrate various popular model architectures, including feed-forward deep neural networks (DNNs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs/LSTMs). CNTK employs stochastic gradient descent (SGD) along with error backpropagation learning, enabling automatic differentiation and parallel processing across multiple GPUs and servers. It can be utilized as a library within Python, C#, or C++ applications, or operated as an independent machine-learning tool utilizing its own model description language, BrainScript. Additionally, CNTK's model evaluation capabilities can be accessed from Java applications, broadening its usability. The toolkit is compatible with 64-bit Linux as well as 64-bit Windows operating systems. For installation, users have the option of downloading pre-compiled binary packages or building the toolkit from source code available on GitHub, which provides flexibility depending on user preferences and technical expertise. This versatility makes CNTK a powerful tool for developers looking to harness deep learning in their projects.
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DeePhi Quantization Tool
This innovative tool is designed for quantizing convolutional neural networks (CNNs). It allows for the transformation of both weights/biases and activations from 32-bit floating-point (FP32) to 8-bit integer (INT8) format, or even other bit depths. Utilizing this tool can greatly enhance inference performance and efficiency, all while preserving accuracy levels. It is compatible with various common layer types found in neural networks, such as convolution, pooling, fully-connected layers, and batch normalization, among others. Remarkably, the quantization process does not require the network to be retrained or the use of labeled datasets; only a single batch of images is sufficient. Depending on the neural network's size, the quantization can be completed in a matter of seconds to several minutes, facilitating quick updates to the model. Furthermore, this tool is specifically optimized for collaboration with DeePhi DPU and can generate the INT8 format model files necessary for DNNC integration. By streamlining the quantization process, developers can ensure their models remain efficient and robust in various applications.
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Integrations
API:
Yes, Deci has an API
No Integrations at this time
Company Details
Company:
Deci AI
Year Founded:
2019
Headquarters:
Israel
Website:
deci.ai/platform/
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Live Training (Online)
Training Videos
Customer Support
Business Hours
Online Support
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