Encord specializes in providing a data platform focused on advanced computer vision technology. The platform offers tools that help businesses manage their data labeling and workflow processes efficiently. It allows AI teams to create 'Ground Truth' data significantly faster, which is crucial for training AI models. Encord combines technology with human expertise to ensure high-quality data management services, enabling clients to monitor and evaluate their data and labels effectively. The platform supports various types of visual data, including images, videos, and medical imagery, and features one-click automated labeling and customizable workflows that incorporate human input. Encord's goal is to streamline the data management process for AI teams, helping them scale their projects while maintaining quality.

Harvard Management Company

Crane Venture Partners

Charles River Ventures

Y Combinator

Harpoon

Next47

Data & Analytics

AI & Machine Learning

Encord

AI data annotation platform Encord, also known as Cord Technologies Inc., has raised $30 million in a Series B round led by Next47, with participation from Y Combinator, CRV, and Crane Venture Partners. Encord's platform automates data preparation and annotation using AI, aiming to streamline AI model training. The company competes in a growing industry expected to reach $3.6 billion by 2027, facing rivals like Scale AI, Datasaur, Dataloop, and Soda Data.

Encord raises $30M for AI platform

In April 2023, Encord introduced the original SAM model to its platform a mere few days after its initial release.

Announcing the launch of SAM 2 in Encord

Today, we are excited to announce that Encord has raised $30 million in Series B funding to invest fully in the future of multimodal AI data dev

Announcing Encord’s $30 million Series B funding

A White-tailed bumblebee collects nectar on 8.8.2022, Knutsford, England. Honey bees play a vital . [+] role in the pollination of the food we eat but changing weather, increased land use, imported pests & chemicals in farming have decimated British honey bees. Getty ImagesA 2021 study published in the Royal Society Open Science journal detailed how bees send out a rallying call for collective defense against an attack of Asian Hornets. The study noted that this signal was previously undiscovered and is now known as the anti-predator pipe. According to the study, the 'pipe' shares acoustic traits with alarm shrieks, fear screams and panic calls of primates, birds and meerkats.In 2021, the New York Times reported that Asian Hornets can kill a bee every 14 seconds

See How This Ai Prototype Can Detect Asian Hornets And Protect Bees

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More. Throughout 2022, generative AI captured the public’s imagination. With the release of Stable Diffusion, Dall-E2, and ChatGPT-3, people could engage with AI first-hand, watching with awe as seemingly intelligent systems created art, composed songs, penned poetry and wrote passable college essays.Only a few months later, some investors have begun narrowing their focus. They’re only interested in companies building generative AI, relegating those working on predictive models to the realm of  “old school” AI.However, generative AI alone won’t fulfill the promise of the AI revolution. The sci-fi future that many people anticipate accompanying the widespread adoption of AI depends on the success of predictive models. Self-driving cars, robotic attendants, personalized healthcare and many other innovations hinge on perfecting “old school” AI

We Must Perfect Predictive Models For Generative Ai To Deliver On The Ai Revolution

Before Eric Landau co-founded Encord, he spent nearly a decade at DRW, where he was lead quantitative researcher on a global equity delta one desk and put thousands of models into production. He holds an S.M. in Applied Physics from Harvard University, an M.S. in Electrical Engineering and a B.S. in Physics from Stanford University.More posts by this contributorDuring the past six months, we have witnessed some incredible developments in AI. The release of Stable Diffusion forever changed the artworld, and ChatGPT-3 shook up the internet with its ability to write songs, mimic research papers, and provide thorough and seemingly intelligent answers to commonly Googled questions.These advancements in generative AI offer further evidence that we’re on the precipice of an AI revolution.However, most of these generative AI models are foundational models: high-capacity, unsupervised learning systems that train on vast amounts of data and take millions of dollars of processing power to do it

Active Learning Is The Future Of Generative Ai: Here’S How To Leverage It

Encord secures $30M in Series B funding and introduces Encord Index to automate AI data curation and management.

Encord Secures $30M in Series B Funding and Introduces Encord Index to Automate AI Data Curation and Management

Encord also launched Encord Index, an end-to-end data management tool that allows customers to visualize, search, sort, and control their internal data that will be used to train and create AI models.

Encord: AI Data Development Company Raises $30 Million (Series B)

LONDON--(BUSINESS WIRE)--Encord, the platform for data-centric computer vision, has released Encord Active, a free open source industry agnostic toolkit that enables machine learning (ML) engineers and data scientists to understand and improve their training data quality and help boost model performance.For many use cases, such as self-driving cars and diagnostic medical models, AI suffers from a “production gap” between successful proof-of-concept models and models capable of running “in the wild.” Proof-of-concept models perform well in research environments but struggle to make predictions accurately and consistently in real-world scenarios. This gap is due to issues of model robustness and reliability which have hindered the widespread adoption of AI.With Encord’s open source toolkit, ML engineers can bridge this gap using a new approach for investigating the quality of their data, labels, and model performance. Data and label errors can severely impact a model’s performance, so continuously evaluating and improving training datasets is critical for ensuring high-quality predictions. Encord's new tool empowers machine learning teams to find failure modes in their models, prioritize high-value data for labeling, and drive smart data curation to improve model performance.Active learning, a process for training models in which the model asks for data that can help improve its performance, has gained traction as a theory among researchers, start-ups, and enterprises. Smaller AI companies, however, have not yet been able to implement usable active learning techniques. Encord Active allows companies of all sizes to move from theory to implementation by providing a new methodology based on “quality metrics.” Quality metrics are computed indexes added on top of your data, labels, and models based on human-explainable concepts.Current active learning methods rely on ML engineers building their own tools and creating their own versions of quality metrics, making the process a time-consuming and expensive approach

Encord Launches Open Source Active Learning Toolkit To Speed Up Real-World Applications Of Computer Vision

A visitor takes a picture with his mobile phone of an image designed with artificial intelligence by . [+] Berlin-based digital creator Julian van Dieken (C) inspired by Johannes Vermeer's painting "Girl with a Pearl Earring" at the Mauritshuis museum in The Hague on March 9, 2023. Photo by Simon Wohlfahrt. AFP via Getty ImagesFake images and misinformation in the age of AI are growing. Even in 2019, a Pew Research Center study found that 61% of Americans said it is too much to ask of the average American to be able to recognize altered videos and images. And that was before generative AI tools became widely available to the public.Adobe ADBE shared August 2023 statistics on the number of AI-generated images created with Adobe Firefly reaching one billion, only three months after it launched in March 2023.In response to the increasing use of AI images, Google Deep Mind announced a beta version of SynthID

Google Launches Tool That Detects Ai Images In Effort To Curb Deepfakes

Data platform for computer vision workflows

Encord

Data platform for computer vision workflows

Encord

Data platform for computer vision workflows

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