AI & RoboticsNews

How AI is improving the web for the visually impaired

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today! There are almost 350 million people worldwide with blindness or some other form of visual impairment who need to use the internet and mobile apps just like anyone else. Yet, they can only do so if…
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AI & RoboticsNews

How AI-driven robots and drones bring cognitive intelligence to Industry 4.0

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today! Over the past few years, smart manufacturing initiatives such as digital twins and the internet of things have caused Industry 4.0 –  the trend towards digital transformation in manufacturing and…
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AI & RoboticsNews

Inscribes battles fraud with AI-powered detection and automation tools

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today! When applying for financial services, applicants need to prove that they are who they say they are and that the information they’re providing isn’t misleading, fudged or blatantly…
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AI & RoboticsNews

Finding AI’s low-hanging fruit

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today! Delivering AI solutions from the test bed to production environments will…
AI & RoboticsNews

To optimize data curation for AI, Lightly turns to self-supervised learning

All machine learning models are bound by a critical factor: The quality of the data on which the model is trained. The challenge of data curation to improve the quality of machine learning and AI models is one that is well-understood. A 2021 MIT research study found systemic issues in how training data was labeled, leading to inaccurate outcomes in AI systems. A study in the journal Quantitative…
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