Edge Impulse, a cloud platform for edge machine learning (ML), announced it has raised $14 million in Series B funding to bring its solutions to developers and enterprises everywhere. This new round of funding is led by Boldstart Ventures and further strengthens Edge Impulse’s mission to make edge ML accessible to everyone.
This announcement marks a new era in ML. It highlights the potential of Edge Impulse to provide powerful, cloud-hosted solutions that allow developers to build and deploy ML models from the edge.
Let’s dive into the benefits Edge Impulse can offer developers.
Edge Impulse Announces Series B Funding, Scaling Edge ML for Developers and Enterprises Everywhere
Edge Impulse is a platform dedicated to helping developers and enterprises quickly and easily deploy machine learning models at the edge. Founded in 2018, the San Francisco-based startup has made it their mission to provide an open platform that improved embedded system ML development. With its latest series B funding, Edge Impulse can expand their cloud offering, grow their customer base and bring seamless ML projects to a wider audience.
The platform offers four core components designed to make machine learning simpler for businesses and developers alike:
-Data ingestion: Edge Impulse allows users to capture data from any source – from pre-recorded audio signals input by humans, real-time environmental sound recordings, accelerometer readings and more.
-Data labeling: Once data is collected it needs to be labeled appropriately for the model to recognize patterns. Edge Impulse utilizes automated tools and hand labeling support for unique annotation tasks.
-Model training & evaluation: Users can use pre-trained models or create custom AI/ML models with no coding required using the cloud service hosted on Amazon Web Services or Azure Machine Learning Services—enabling trained models without leaving the tool.
-Deployment for inference application: Each project contains an Interactive Device Terminal which enables users to quickly deliver inference applications generated with popular model formats such as TensorFlow Lite, ONNX Runtime or CoreML ready for consumption on either Android or IOS mobiles devices all within one click of a button!
Overview of Series B Funding
Series B funding occurs after a company has gone through its initial seed funding, developed a prototype and gone through other developmental stages. In this stage, the company has in most cases demonstrated some signs of success, and looks to attract investors who are ready to take their business to the next level.
Series B funding typically occurs when an established startup is looking for capital to expand. This round of payment is necessary for them to increase their user base, manufacture new products, or any form of improvement that helps the success of that startup.
This form of venture capital is meant to help a growing business attain the resources they need to quickly grow and become competitive in their respective area. It is important for companies opting out of Series B funding to have potential growth plans set out so they can seek out investors that are interested in seeing those plans come into action.
At this stage investors are usually very interested in receiving returns on their Series B capital investments quickly. Investors usually want proofs-of-concept from startups’ projects before investing more capital into the latter projects thus startups have to show concrete use cases for continued investments from Series B Venture Capitalists after receiving Series A funds previously.
Benefits of Edge Impulse for Developers
Edge Impulse is a platform that enables developers to easily apply machine learning at the edge. With Edge Impulse, developers can quickly build sophisticated AI applications with minimal effort.
In this article, we’ll cover the benefits of Edge Impulse for developers, from speeding up development to enabling easy deployment on a wide range of hardware.
Low-code development platform
Edge Impulse is a low-code development platform for efficiently developing machine learning inference solutions for the edge. This platform enables developers to quickly and easily prototype, develop, train and deploy machine learning models to the edge using sensor signals and other ioT devices.
Edge Impulse provides developers with intuitive, easy-to-learn tools to help them create models quickly. With Edge Impulse, developers have access to an intuitive drag-and-drop interface that automatically generates efficient machine learning inference code for embedded devices; this code can then be deployed directly onto the device in question. Developers also have access to an active community of support and best practices, numerous tutorials and examples of successful projects, and accuracy visualizations to help them improve the accuracy of their models.
With Edge Impulse developers can benefit from no limit on data size or compute resources required, allowing them to create powerful models – all while reducing their time spent in programing embedded devices. Additionally, no specialized hardware or testbeds are needed when working with Edge impulse allowing its users to make great applications faster with much less headache involved.
Real-time insights and analytics
Edge Impulse helps developers make well-informed decisions quickly, enabling them to use data to drive their development process. With Edge Impulse’s real-time insights and analytics, developers can make better decisions in less time and with far less effort than before. By gathering data from hundreds of different devices and sources – Edge Impulse makes it easier for developers to quickly access and analyze the data they need for their projects.
Edge Impulse’s platform offers essential analytics tools to help developers unlock their predictive models from the edge. From anomaly detection and resource optimization to managing deployment cycles, Edge Impulse gives developers the necessary tools for a more efficient development process. On top of this, Edge Impulse provides unprecedented scalability for companies of all sizes – from single developer applications to massive enterprise networks hosting thousands of nodes.
In addition to helping companies develop reliable solutions faster, Edge Impulse offers powerful machine learning capabilities that can be used with or without a managed solution. This means that companies can send their ML models straight into production to get real-time feedback on performance and optimize the model’s accuracy on an ongoing basis. The platform also allows companies to build databases full of information about sensors, connected devices, and system configurations accessible directly via an API or using built-in functions.
By providing immediate access to analytics while making it easy for developers to create machine learning models, Edge Impulse has revolutionized how sensor data is used today – enabling businesses everywhere to take advantage of its powerful capabilities.
Easy deployment and scalability
Edge Impulse provides developers with easy to use tools that make it easy to build, deploy, and scale machine learning (ML) models at the edge. The platform is ideal for developers looking to optimize their ML performance and reduce latency by running their applications locally. Edge Impulse allows developers to quickly develop, train and deploy models without having to write extensive code or acquire extensive ML knowledge. This saves time and removes a major barrier for entry for developers of all experience levels.
The Edge Impulse platform is designed with scalability in mind, providing enterprise-level users the ability to extend from dozens of devices up into millions or even billions at a moment’s notice. It also accommodates the needs of its user base, allowing different types of feedback loops from various sources like IoT devices, edge gateways, web APIs or cloud services creating an end-to-end distributed computing infrastructure. These capabilities enable teams in any industry to quickly capture data for timely analysis and insights and bring more intelligence closer to where it’s needed most – on the edge.
By integrating with existing applications and systems as well as providing helpful metrics along the way makes it easier than ever before for enterprises of all sizes realize meaningful results faster than ever before while reducing cost. With Edge Impulse companies can create more resilient products, more responsive real-time analytics capabilities based on historical data points available in real-time without wasting valuable development hours on a day-long deployment cycle.
Edge Impulse for Enterprises
Edge Impulse, the leading edge machine learning platform, recently announced that it has closed its Series B round of funding. The funding will be used to continue scaling the platform, allowing developers and enterprises to benefit from Edge Impulse’s tools and services.
In this article, we’ll be discussing the benefits of Edge Impulse for developers and enterprises alike.
AI-powered edge solutions
Edge Impulse for Enterprises provides enterprise organizations with an AI-powered edge solution designed to process data collected from the sensor network and generate insights to assess the performance of their infrastructure. Organizations can use Edge Impulse to turn the data collected from their edge networks into automated alerts and real-time insights. With low latency and high accuracy, Edge Impulse delivers cost savings and performance improvements with ease.
Edge Impulse can be used for both basic testing applications as well as predictive analytics on sensor data, allowing organizations to understand how different components within their infrastructure interact with each other. This helps them identify problems in advance, so they can take action quickly and effectively. To ensure that all processes are running properly, Edge Impulse offers streaming analytics support for evaluating raw data before it’s stored in a massive database.
Additionally, Edge Impulse makes it easy to manage large-scale deployments of edge networks by setting up over-the-air (OTA) updates on connected devices in order to ensure that the software remains up to date and secure. Organizations can also use Edge Impulse to deploy applications at scale without complexity while benefiting from a single point of contact for customer service queries around their edge solutions.
Automated machine learning
Edge Impulse announced today that it has raised $14 million in its Series B funding, led by Intel Capital and venture capitalists Norwest Venture Partners, to expand its platform for automatic machine learning (AutoML) capability which enables enterprises to build predictive analytics and intelligent systems into their Internet of Things devices.
Edge Impulse’s technology allows developers and data scientists to quickly do complex AI tasks for embedded devices with limited memory, such as processing time-series sensor data into actionable insights with as little infrastructure as possible. With the company’s new cloud-native approach to AutoML, they allow enterprises to easily scale their machine learning projects on a larger scale.
Edge Impulse’s automated machine learning (AutoML) solutions provide a range of advantages over traditional model creation solutions by enabling enterprises to quickly build sophisticated ML models with minimal effort and reduced cost. This reduces the amount of manual effort required for data preprocessing while providing an easy way for companies to generate greater ROI from their ML models. Edge Impulse’s platform makes it easier than ever for customers to build predictive analytics solutions by automating certain steps of the model development process such as building features from raw time series sensor data; classifying time series into events or labels; training algorithms with popular architectures like convolutional neural networks (CNN); monitoring ML performance over time; tuning hyperparameters until desired results are achieved; productionizing trained models on microcontrollers running low memory/power settings and more – ultimately allowing customers get more value out of their existing IoT hardware investments thanks to Edge Impulse’s powerful cloud-native platform offerings.
Security and privacy
When deploying Edge Impulse on edge devices, customer data must remain secure and private. That’s why we build all our software with the latest security standards and follow industry best-practices for encryption, authentication, and authorization. All communication between the server and devices happens over a secure encrypted channel, with customer data never leaving their own premises.
Edge Impulse also integrates with major cloud providers so that customers can securely transfer data from their devices to their accounts. We also offer private clouds for customers who need extra control over where their data is stored and managed. Customers have the ability to configure exactly which services they want running on their account – meaning only those services are running on actual millisecond-level responses are necessary. This ensures an enterprise-grade level of security and scalability that meets even the most stringent corporate requirements while preserving ultra low latency operation at the edge.
Impact of Series B Funding
Edge Impulse, an edge machine learning platform, recently announced their Series B funding of $2.2M. This funding is a testament to the growth and scalability of their platform, with the funds helping the company grow their platform and reach more developers and enterprises worldwide. The Series B funding is sure to have an impact on the world of edge machine learning and developers alike.
In this article, we’ll discuss the potential benefits of Edge Impulse for developers and enterprises.
Expansion of platform capabilities
Edge Impulse’s Series B funding allows the company to expand their platform capabilities and support the world’s leading innovators in embedded systems, edge development, and machine learning (ML). To accomplish this, Edge Impulse is developing advanced ML models that can be easily deployed at scale for applications such as anomaly detection and predictive maintenance.
The new funding also enables Edge Impulse to provide new infrastructure including an AI-first project management platform for deployment of sensor-based AI. This hub will enable data scientists to quickly design and deploy AI applications in near-realtime on popular architectures like Raspberry Pi or Android devices.
Edge Impulse aims to become a one-stop shop for edge development, empowering developers with a unified platform that includes data collection, feature engineering, developer tooling, model building as well as on-device runtime solutions. With their expanded offerings they are looking to provide end-to-end solutions catering to end users leveraging Machine Learning at the Edge.
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