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Closing Remarks

Posted Jun 21
# Transform (March 2021)
# Keynote
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SPEAKER
Brad Porter
Brad Porter
Brad Porter
Chief Technology Officer @ Scale AI, Formerly, VP of Robotics and Distinguished Engineer @ Amazon

Brad is the CTO of Scale AI. Prior to Scale, Brad was the VP of Robotics and a Distinguished Engineer at Amazon where he was responsible for driving improvements in the safety and autonomy of Amazon's global operations. His experiences at Amazon as well as Tellme Networks has given him a deep understanding of AI's engineering challenges as well as opportunities.

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Brad is the CTO of Scale AI. Prior to Scale, Brad was the VP of Robotics and a Distinguished Engineer at Amazon where he was responsible for driving improvements in the safety and autonomy of Amazon's global operations. His experiences at Amazon as well as Tellme Networks has given him a deep understanding of AI's engineering challenges as well as opportunities.

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SUMMARY

Closing Remarks with Brad Porter, Chief Technology Officer at Scale AI

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TRANSCRIPT

Brad Porter:

Thank you, Alex. And thank you Fei-Fei. What an incredible conversation to close out the day. Before we wrap up and go into the networking and social events. I want to thank all our speakers for their time and their insights. I know, I for one I’m incredibly enthusiastic about the AI community that’s emerged and incredibly honored that our speakers graciously volunteered their time to share their insights and that you all took your time to attend our conference today.

I also wanted to take a moment to reinforce a couple of the key themes I’ve picked up on throughout the day today. The first is the critical importance of data. Our industry recognizes that more and more data and computer can logarithmically improve model performance. But as Dr. Andrew Ng discussed in his thought, it’s not just the volume of data that matters, but the quality of that data. For some use cases, we may have a lot of data and in others, we may not have much to work with, but bigger or small, we need to improve the quality of our datasets to ensure model accuracy.

And while the model work often takes center stage in ML development, your models are ultimately learning the intrinsics of your data. I hope all of us take Andrew’s words to heart and champion the importance of data quality to unlock the full potential of machine learning. The second theme that came through loud and clear was the critical importance of making our field more diverse and more inclusive. Kevin Scott spoke earlier in the day about making the field more accessible to ensure the benefits of AI and machine learning are evenly distributed. Just now Fei-Fei Li spoke about the unintended consequences of AI.

The example she gave was a healthcare model developed up a dataset, primarily collected in coastal states without regional diversity in the dataset, such a model may unintentionally misdiagnose patients in other regions of the US. This ultimately serves an important reminder to all of us that how the datasets are collected matters, how datasets are labeled matters, making AI accessible matters, fostering diversity in our fields is even more important because of the potential of AI and machine learning.

I hope all the insights shared by our speakers today leaves you as hopeful for the future of our industry as I am. If you missed any of the sessions, video recordings of all sessions will be made available on the Scale website. Thank you again to all of our speakers and thank you all for joining us for our inaugural Scale Transform Conference.

If you enjoyed the sessions today, I’m really excited to announce that we’ll be hosting another virtual conference this fall. For more information on our next conference, please follow us on Twitter, LinkedIn, and Facebook. With that, we encourage you all to connect in our virtual networking platform. The link is located in the conference chat to the right of your screen. Thank you again and have a great weekend.

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