Ninety percent of information transmitted to the human brain is visual. The importance of sight in understanding the world makes computer vision essential for AI systems.

By simplifying computer vision development, startup Roboflow helps bridge the gap between AI and people looking to harness it. Trusted by over a million developers and half of the Fortune 100 companies, Roboflow’s mission is to make the world programmable through computer vision. Roboflow Universe is home to the largest collection of open-source computer vision datasets and models.

Cofounder and CEO Joseph Nelson joined the NVIDIA AI Podcast to discuss how Roboflow empowers users in manufacturing, healthcare and automotive to solve complex problems with visual AI.

A member of the NVIDIA Inception program for cutting-edge startups, Roboflow streamlines model training and deployment, helping organizations extract value from images and video using computer vision. For example, using the technology, automotive companies can improve production efficiency, and scientific researchers can identify microscopic cell populations.

Over $50 trillion in global GDP is dependent on applying AI to problems in industrial settings, and NVIDIA is working with Roboflow to deliver those solutions. Nelson also shares insights from his entrepreneurial journey, emphasizing perseverance, adaptability and community in building a mission-driven company. Impactful technology isn’t just about innovation, he says. It’s about making powerful tools accessible to the people solving real problems.

Looking ahead, Nelson highlights the potential of multimodal AI, where vision integrates with other data types to unlock new possibilities, and the importance of running models on the edge, especially on real-time video. Learn more about the latest advancements in visual agents and edge computing at NVIDIA GTC, a global AI conference taking place March 17-21 in San Jose, California.

Time Stamps

2:03 – Nelson explains Roboflow’s aim to make the world programmable through computer vision.

7:26 – Real-world applications of computer vision to improve manufacturing efficiency, quality control and worker safety.

22:15 – How multimodalilty allows AI to be more intelligent.

33:01 – Lessons learned and perspectives on leadership, mission-driven work and what it takes to scale a company successfully.

29:43 – Teasing Roboflow’s upcoming announcements at GTC.

You Might Also Like…

How World Foundation Models Will Advance Physical AI With NVIDIA’s Ming-Yu Liu

AI models that can accurately simulate and predict outcomes in physical, real-world environments will enable the next generation of physical AI systems. Ming-Yu Liu, vice president of research at NVIDIA and an IEEE Fellow, explains the significance of world foundation models — powerful neural networks that can simulate physical environments.

Snowflake’s Baris Gultekin on Unlocking the Value of Data With Large Language Models

Snowflake is using AI to help enterprises transform data into insights and applications. Baris Gultekin, head of AI at Snowflake, explains how the company’s AI Data Cloud platform separates the storage of data from compute, enabling organizations across the world to connect via cloud technology and work on a unified platform.

NVIDIA’s Annamali Chockalingam on the Rise of LLMs

LLMs are in the spotlight, capable of tasks like generation, summarization, translation, instruction and chatting. Annamalai Chockalingam, senior product manager of developer marketing at NVIDIA, discusses how a combination of these modalities and actions can build applications to solve any problem.

Subscribe to the AI Podcast

Get the AI Podcast through Amazon Music, Apple Podcasts, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, SoundCloud, Spotify, Stitcher and TuneIn.

Blog Article: Here