Voxel51 aims to bring transparency and clarity to the world’s data.

• It is an AI-based software company located in Michigan and the founders of Voxel51 are Jason Corso, and Brian Moore.

• The term Voxel is literally a “volume element” in the space-time volume of a video.


You have likely used a variety of video editing tools or programs. And for influencers who have to create and share their videos in a rush, that is most important. When that happens, we often wonder if the procedure would be simpler if the computer could just understand what we want. And if a computer system could accomplish that, then many other fields would have similar opportunities. Have you wondered? 

Manual video content analysis requires a lot of time and effort. Observing and annotating movies frame by frame needs human operators, which is not viable for real-time or large-scale applications. Traditional computer vision methods had shortcomings when it came to automating complex video interpretation tasks. Object identification, tracking, and recognition in movies are frequently laborious and ineffective because they necessitate exclusive algorithms and substantial user involvement.

Each frame in a video data stream can have tens of thousands or even millions of pixels. Large datasets and real-time video streams were difficult to manage since processing and analyzing video data at scale required a lot of computational power. It was challenging to create reliable and accurate computer vision algorithms for video analysis. Video interpretation requires computational resources, computer vision, deep learning, and machine learning techniques, with custom code implementation and user-friendly tools for efficient data management.

Introducing, Voxel51

As the name suggests, by definition, any of the discrete elements comprising the three-dimensional space-time volume of a video.

Voxel51 is a machine learning startup that creates tools for developing machine learning systems, including in computer vision. Their tools let users create systems that can recognize things like moving cars or logos in commercials. Working with video data is difficult because each video frame contains several pixels. It takes many images or frames to analyze and comprehend video content.

Due to the computational load, system design must be pragmatic and require programming expertise. Its platform offers a simple solution that does not require special code. It offers effective methods to locate errors, distinguish unique samples, rank, and sort data, and carry out various other tasks by integrating with users' data representations.

In the field of computer vision and tool creation, a diverse set of talents and interests is necessary. Founders believe in the interest of computer language learning; thus, Voxel51 employs front-end engineers who deal with large-scale datasets and create user-friendly software applications, as well as individuals with competence in software development and a passion for the visual arts. Jason Corso and Brian Moore, the founders, too, had an intriguing path to get here.

A little about the founders

Over the past 15 years, Jason Corso has focused on locating and solving issues related to computer vision and machine learning. His goal at Voxel51 and in his capacity as a professor at the University of Michigan is to motivate others around him to think large, have a profound understanding of the significance of data in machine learning, and have an influence through our work.

Brian Moore created algorithms to solve issues in computer vision and machine learning while pursuing his Ph.D. at the University of Michigan. However, after realizing a severe shortage of machine learning (ML) tools for visual datasets, he changed course. He decided to concentrate on creating the tools he had yearned for when developing his computer vision models. 

Voxel51's weapons

The development process is made simpler by Voxel51's tools, which provide user-friendly interfaces and deal with the necessity for important specialized coding. As a result, researchers, developers, and data scientists will have a better user experience, allowing them to concentrate more on the insights and applications of their work rather than the technical details.

Voxel51 is a platform used by researchers, developers, data scientists, businesses, and startups for various applications. It helps researchers develop algorithms, develop machine learning systems, extract insights from video content, and enhance operations and services.

Businesses can analyze surveillance footage, automate video content analysis, and derive insights for decision-making. Startups can focus on innovation and differentiation by utilizing Voxel51's streamlined approach to working with video data.

  • Transforming dataset formats
  • assembling representative and diversified datasets
  • choosing video frames for annotation and image model training
  • Automatically detecting labeling errors
  • A review of model predictions
  • identifying and depicting model failure modes

The people of Voxel51 firmly believe in the benefits of open-source software. TensorFlow, PyTorch, Apache Spark, and MLflow, to name a few of the most well-known tools in the ML ecosystem, are examples of those that are open source. The greatest method to create a community around a developer tool, in their opinion, is to make the project as open and transparent as possible.

By removing entrance barriers and making a project free and open source, developers can more easily assess a tool's value, give the project their code's seal of approval (via GitHub stars), and promote the tool inside their organizations.

The media and entertainment sector can automate video content analysis using Voxel51's technology. It can help with activities like scene recognition, video tagging, and personalized content recommendations, which will enhance users' viewing experiences. Social media platforms or content producers can make use of Voxel51's video interpretation capabilities.

It can aid in automatically classifying and recognizing video content, simplifying the organization of and searching for particular kinds of films.

What else does it offer?

Voxel51's technology can help in the healthcare industry with video analysis for medical imaging, tracking patient motion or behavior, or even helping with remote diagnostics via telemedicine applications.

Additionally, They have just launched VoxelGPT, which is a tool that combines GPT-3.5 with FiftyOne's computer vision query language, allowing users to interact with datasets using natural language queries. It offers no-code solutions, advanced querying, and visualization and serves as a Python programmer-at-your-fingertip and educational resource.

VoxelGPT streamlines computer vision workflows, saves time, simplifies complex queries, and enhances user interaction with datasets.

FiftyOne, the flagship product of Voxel51, debuted in open source in August 2020. Concerning computer vision and machine learning use cases, the tool promises to assist developers in visually analyzing and improving unstructured datasets. All machine learning processes depend on data, and developing high-performance machine learning systems requires high-quality, clean data. 

Make machine learning first, which has applications in many fields, and then VoxelGPT for beginners; how much simpler can it get? Are you as eager to use this as I am? 


Edited by Shruti Thapa