Join us as we take a look back at Ultralytics' highlights from 2024, featuring computer vision innovations, impactful global events, and a thriving community.
2024 has been an exciting year for artificial intelligence (AI), with Vision AI making huge strides in how we interact with technology. Vision AI, or computer vision (CV), is a field of AI that teaches machines to understand and interpret images and videos - just like humans do. It can be used in a range of applications, from helping doctors detect diseases earlier to making manufacturing smarter and more efficient.
At Ultralytics, 2024 has been focused on making Vision AI even more accessible, accurate, and versatile. With the launch of the new Ultralytics YOLO11 model and updates to the Ultralytics Python package, our team at Ultralytics has been setting new benchmarks for speed and precision. In fact, 500 million images are analyzed with the Ultralytics package every single day.
Beyond working on cutting-edge technology, Ultralytics has also been concentrated on connecting with the AI community and seeing how computer vision is being used to solve real-world problems. Through collaborations, events, and a growing community, Ultralytics has been opening the door to exciting possibilities all year long.
So let’s take a look back at Ultralytics’ highlights from 2024!
2024 started with celebrating the first anniversary of the computer vision model, Ultralytics YOLOv8. Building on its success, the YOLOv8.1 release introduced updates that made it faster, more accurate, and compatible with new hardware and datasets. These improvements made it easier for developers to use the model in real-world applications, from detecting objects in real time to classifying them more precisely.
One of the standout features of the release was the support added for Oriented Object Detection (OBB), which allows the model to identify objects at different angles - a game-changer for tasks like aerial imaging, text recognition, and satellite imagery analysis.
Later in the year, the release of YOLO11 raised the bar even higher. This new model was more efficient and precise and supported all the computer vision tasks for which YOLOv8 was known. The launch of YOLO11 also brought to the table YOLO11 Enterprise models, trained on a proprietary dataset to deliver unparalleled performance for businesses.
Alongside these innovations, Ultralytics released some new updates to its Python package all year round, making it easier for developers to integrate Ultralytics YOLO models into their workflows.
Here’s a quick glance at some of the key releases from 2024:
In February, Ultralytics was awarded $150,000 in Microsoft Azure Cloud credits through the Microsoft for Startups Founders Hub. This generous support has been a driving force behind ongoing research and development efforts, particularly for YOLOv8 and YOLO11. The credits have enabled the team to scale their work, optimize models for object detection, and explore new innovations in Vision AI.
Ultralytics was also honored with two special awards during the Intel Ignite Europe program. The team received recognition for successfully completing the Intel Ignite Europe Batch #7 program, a highly selective initiative by Intel that supports promising startups through mentorship, workshops, and networking opportunities. Ultralytics was also named "Startup with the Most Buzz," celebrating the team's innovative achievements and significant impact throughout the program.
Throughout the year, Ultralytics got a chance to showcase its vision AI innovations at major global events, connecting with industry leaders and inspiring their growing community. Barcelona Mobile World Congress (4YFN) (Feb 26–29), saw Founder and CEO Glenn Jocher, along with Director of Growth Paula Derrenger, present YOLOv8 and the Ultralytics HUB app - a no-code platform designed to create and train Ultralytics YOLO models.
The following month, during NVIDIA GTC 2024 (Mar 18–21), the Ultralytics team engaged with AI professionals worldwide, receiving some positive feedback on YOLOv8’s impact.
Later in Berlin, Ultralytics took part in the WeAreDevelopers World Congress 2024 (July 17–19), connecting with over 20,000 developers, startups, and industry leaders. The event kicked off with the Intel AI Summit, where Machine Learning Engineer Francesco Mattioli showcased YOLOv8’s real-time performance with a live demo on an iPhone 15, demonstrating its seamless integration with Intel hardware.
At the main conference, Ultralytics hosted interactive demos at their booth, highlighting YOLOv8’s versatility and engaging with developers using the model for applications like defect detection and academic research.
Towards the end of the year, at the Maker Faire Shenzhen 2024 (Nov 16–17), Ultralytics was represented by Lakshantha Dissanayake, Embedded Computer Vision Engineer, and Jing Qiu, Senior Machine Learning Engineer. They showcased live YOLO11 demos and presented a keynote highlighting Vision AI’s role in driving sustainability.
While Ultralytics attended many events this year, the team also hosted YOLO Vision 2024 (YV24), our annual hybrid event. Held at the Google for Startups Campus in Madrid and streamed globally on September 27th, YV24 brought together experts, developers, and enthusiasts to celebrate advancements in Vision AI.
A key highlight was the announcement of YOLO11, featuring 30 new models. These models are faster, more efficient, and more accurate, with YOLO11m achieving better results on the COCO dataset while using 22% fewer parameters compared to YOLOv8m.
The event also featured engaging panels on topics like generative AI, women in AI leadership, and community-building strategies. Speakers from companies like Ultralytics, leading universities, and innovative startups shared insights to foster innovation and inclusivity.
Real-world applications of YOLO models were presented, including shark detection via drone surveillance and cattle behavior monitoring, demonstrating their versatility across industries. Collaborations with companies like Intel, NVIDIA, and Sony further highlighted Ultralytics YOLO’s seamless integration with cutting-edge hardware for optimized edge AI performance.
Ultralytics actively engaged with the Vision AI community in 2024, sharing insights, fostering collaboration, and showcasing the real-world impact of their technology. Here are some key highlights:
To get a better idea of how impactful 2024 has been for Ultralytics, the numbers speak for themselves. This year, Ultralytics tools were downloaded 64 million times via pip, demonstrating the growing adoption of Ultralytics YOLO models among developers worldwide. On GitHub, Ultralytics has surpassed 96.5K stars across its repositories, highlighting its influence and leadership in the open-source community.
The usage statistics are equally impressive. Ultralytics products saw 5 million monthly visits, with 3 million models trained daily using the Ultralytics package.
Ultralytics’ YOLO models offer various modes, like the “predict” mode, which is used to analyze images or videos and generate predictions about objects, and the “track” mode, which follows objects across frames in a video for continuous monitoring. In 2024 alone, the tracking mode was called 110 million times daily, while the prediction mode was used 650 million times per day, showcasing the integral role YOLO models play in real-world applications.
2024 has been a remarkable year for Ultralytics, marked by key advancements and milestones in Vision AI. The release of YOLO11 set new standards for performance and versatility, while tools like the Ultralytics Explorer empowered developers and researchers to elevate their projects.
Through global events, partnerships, and community initiatives, Ultralytics has continued to make a meaningful impact in the field of computer vision. This year’s achievements showcase not just technical innovation but also the strength of a global community driving progress together.
As 2025 approaches, the team at Ultralytics is more motivated than ever to push boundaries and create tools that support developers and enterprises worldwide.
To learn more, visit our GitHub repository, and engage with our community. Explore applications of AI in self-driving cars and Computer vision in agriculture on our solutions pages. 🚀
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