In this edition of the Superb AI Roundup, we will dive into our new Gen AI features and showcase how to use Generative AI to effectively augment your datasets, boosting your model's performance!
Superb AI Inc.
软件开发
San Mateo ，California 4,902 位关注者
Curate datasets you can trust, cut down on labeling time and errors, and launch and scale AI products faster than ever.
关于我们
Superb AI is a leading computer vision platform and professional services provider that provides enterprise-grade, end-to-end MLOps and DataOps workflows to accelerate the adoption and development of data-centric AI. Through the practical application of AI-based automation, Superb AI helps teams manage the entire ML lifecycle more efficiently, from data annotation to curation, model training, and deployment, while ensuring optimal data accuracy and consistency. Used by top ML practitioners, including teams at Samsung, LG, Hyundai, Kakao, and Nippon Steel, Superb AI is on a mission to democratize AI by significantly reducing the time, cost, and effort required to go from proof-of-concept to production. To learn more or get started for free: www.superb-ai.com
- 网站
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https://www.superb-ai.com
Superb AI Inc.的外部链接
- 所属行业
- 软件开发
- 规模
- 51-200 人
- 总部
- San Mateo ，California
- 类型
- 私人持股
- 创立
- 2018
- 领域
- Data Processing、Machine Learning、Deep Learning、Human-in-the-loop AI、Computer Vision、MLOps、AI、Data Labeling、Data Annotation、NLP、Ground Truth Data、Training Data、Deep Learning、Data Curation、Data Ops、Healthcare、Agriculture、Agritech、Transportation、Robotics、Safety & Security、Retail、Government、Sports & Wellness、Gaming和AR / VR
地点
Superb AI Inc.员工
动态
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Congrats to the whole team for achieving another milestone! With this latest round of funding, we will continue to push the technical boundaries of what’s achievable in computer vision, aiming to drive innovation to new heights. Reach out to find out what we're building next!
Superb AI Inc. (YC W19) has raised $10.2 million in Series C funding for its comprehensive computer vision AI platform, which simplifies dataset curation, management, model training, diagnostics, and deployment. Founded in 2018, Superb AI offers a complete toolset for companies looking to utilize AI, particularly in computer vision. Their platform handles everything from data collection and labeling to model building and deployment. With offices in Seoul, San Mateo, and Tokyo, the startup boasts over 100 clients, including Hyundai, Samsung, and Toyota. CEO and co-founder Hyun Kim sees potential partnerships with their Series C investors, particularly in manufacturing— pointing out that current manual inspections of factory parts are inefficient and costly, which their technology could automate. Superb AI's software could also support Hyundai’s self-driving initiatives and assist Samsung in enhancing its AI capabilities for its smartphones. Next month, Superb AI will launch an on-premise version of its tools, catering to industries that can’t use cloud services due to security concerns. They plan to utilize Nvidia's GPU chips for training these models while exploring deployment options. The new funds will be used for general working-capital purposes as the company prepares for a public listing in South Korea in 2026. Congrats on the Series C, Hyun, Moonsu Cha, Jonghyuk Lee, Jung Kwon Lee, and team! https://lnkd.in/d9cmktfB
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?? ?Join us in celebrating our successful Series C funding!??? Since our founding in 2018, Superb AI has relentlessly pursued technological innovation and customer satisfaction. This hard work has paid off, with investors recognizing our value, leading to this significant Series C investment. This achievement wouldn’t have been possible without the incredible support from our team, clients, and partners. We are deeply grateful for your trust and collaboration.?We’re committed to continuing our growth and reaching even greater heights! Read the full press release:?https://lnkd.in/gtZVGjmh
South Korean AI Firm Superb AI Raises $10.2 Million in Series C Funding.
thepickool.com
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Take a look at our latest Academy video that showcases our Model Diagnosis feature in the Curate module! In this video you'll learn how to do the following : - How to examine models trained within the Model module or externally - How to identify overfitting - How to identify and address data imbalance - How to use Confusion Matrix to identify true positives, false positives, true negatives, and false negatives while comparing the predicted classes by the model to the actual classes. - How to fix any and all issues within your training data quickly for rapid model fine-tuning https://lnkd.in/gSaM4jUK #computervision #artificialintelligence #datacuration #superbai #groundtruth
Academy 6.4 - Model Diagnosis in Superb Curate
https://www.youtube.com/
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Our very own Tyler McKean and team set out to create some tangible use cases that highlight the strengths of the Superb Platform. Just recently, using all 3 Superb modules (Label / Curate / Model), along with the BDD 100K dataset, they were able to build and deploy a computer vision model, assess and diagnose performance and fine tune the model all within the platform, improving mAP by 10% (!!). Read the blog post to understand the teams approach and process! https://hubs.li/Q02fJmWP0
A Guide to Improving Model Performance in Just 3 Hours with Superb Platform’s Model Diagnosis: Experiment on BDD 100K
superb-ai.com
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What a year 2023 has been for the Superb AI team! Read our end of year blog post from our CEO, Hyun Kim as he recaps some of the exciting milestones from 2023 and our outlook and positioning for not just 2024 but years to come! Happy New Year from the Superb AI team! ????https://hubs.li/Q02dYjBT0
Superb AI : A Look Back At 2023
superb-ai.com
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Thank you Johann Beukes for eloquently packaging our mission into a well thought out post! Lowering the barrier of entry to rapid vision model development is our never-ending mission and hope that we can continue to contribute to an industry that is poised to reshape our future!
Founder of DeepLearning.AI; Managing General Partner of AI Fund; Exec Chairman of Landing AI
The LVM (large vision model) revolution is coming a little after the LLM (large language model) one, and will transform how we process images. But there’s an important difference between LLMs and LVMs: - Internet text is similar enough to proprietary text documents that an LLM trained on internet text can understand your documents.? - But internet images – such as Instagram pictures – contain a lot of pictures of people, pets, landmarks, and everyday objects. Many practical vision applications (manufacturing, aerial imagery, life sciences, etc.) use images that look nothing like most? internet images. So a generic LVM trained on internet images fares poorly at picking out the most salient features of images in many specialized domains. That’s why domain specific LVMs – ones adapted to images of a particular domain (such as semiconductor manufacturing, or pathology) – do much better. At Landing AI, by using ~100K unlabeled images to adapt an LVM to a specific domain, we see significantly improved results, for example where only 10-30% as much labeled data is now needed to achieve a certain level of performance. For companies with large sets of images that look nothing like internet images, I think domain specific LVMs can be a way to unlock considerable value from their data. Dan Maloney and I share more details in the video.?
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The team at Superb AI just recently released Model Diagnosis, a feature that serves as the quantitative layer when iterating and fine-tuning models. Read part 1 of a 2 part blog series that dives into the metrics and applications of the feature itself and how teams can better utilize Model Diagnosis within their MLOps pipeline. https://lnkd.in/efa67hXR #computervision #superbai #artificialintelligence #deeplearning #ai
Superb AI's Model Diagnosis Tool
superb-ai.com