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S2:E13 Data is NOT Boring with Josh Simons

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İçerik VMware Podcasts tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan VMware Podcasts veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
In this episode of Don’t Break the Bank, we talk to Josh Simons, Chief Technologist for High Performance Computing at VMware. Josh tells us about some of the things he’s working on in HPC as it relates to financial services. We also explore where ML and AI are fit and are heading...and consider some of the ethical implications as our ability to harness data evolves. This is a great episode for anyone thinking about the types of data that could be used for Machine Learning and how this could be used in your organisation. EPISODE NOTES 3 Takeaways, beyond Data is NOT boring: The data that you throw away is the data that tomorrow you might be able to use. For instance, as part of a machine learning model that could bring true value to an organization. It's important for organizations to have explicit statements about their AI ethics. Federated learning has some magical capabilities, especially for financial services customers, when it comes to building predictive models without violating local laws on how data is stored or used because the data never leaves the premises. Key Quotes: "In some sense, we all need to be pack rats when it comes to our data.” - Josh “I think it's critically important for organizations to speak explicitly about data ethics with the people or organizations from which you are collecting data and be very clear with them, as well as with your employees, about what it is that you're willing to do and not do with that information.” - Josh “Data is where it all happens. That's the fuel that runs all the ML stuff...The issue is how do we get our hands around all that data, and how do we get it to the point where it is appropriate for building predictive models? Just because you have the data doesn't mean that the data has been cleaned, curated and de biased - so that it's actually in shape to be used for building models.” - Josh -- Links Josh Simons LinkedIn -- About the Hosts Matthew O'Neill is a husband, dad, geek and Industry Managing Director, Advanced Technology Group in the Office of the CTO at VMware. You can find Matthew on LinkedIn and Twitter. Brian Hayes is an audiophile, dad, builder of sheds, maker of mirth, world traveller and EMEA Financial Services Industry Lead at VMware. You can find Brian on LinkedIn.
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S2:E13 Data is NOT Boring with Josh Simons

VMware Podcasts

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iconPaylaş
 
Manage episode 384162106 series 1322902
İçerik VMware Podcasts tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan VMware Podcasts veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
In this episode of Don’t Break the Bank, we talk to Josh Simons, Chief Technologist for High Performance Computing at VMware. Josh tells us about some of the things he’s working on in HPC as it relates to financial services. We also explore where ML and AI are fit and are heading...and consider some of the ethical implications as our ability to harness data evolves. This is a great episode for anyone thinking about the types of data that could be used for Machine Learning and how this could be used in your organisation. EPISODE NOTES 3 Takeaways, beyond Data is NOT boring: The data that you throw away is the data that tomorrow you might be able to use. For instance, as part of a machine learning model that could bring true value to an organization. It's important for organizations to have explicit statements about their AI ethics. Federated learning has some magical capabilities, especially for financial services customers, when it comes to building predictive models without violating local laws on how data is stored or used because the data never leaves the premises. Key Quotes: "In some sense, we all need to be pack rats when it comes to our data.” - Josh “I think it's critically important for organizations to speak explicitly about data ethics with the people or organizations from which you are collecting data and be very clear with them, as well as with your employees, about what it is that you're willing to do and not do with that information.” - Josh “Data is where it all happens. That's the fuel that runs all the ML stuff...The issue is how do we get our hands around all that data, and how do we get it to the point where it is appropriate for building predictive models? Just because you have the data doesn't mean that the data has been cleaned, curated and de biased - so that it's actually in shape to be used for building models.” - Josh -- Links Josh Simons LinkedIn -- About the Hosts Matthew O'Neill is a husband, dad, geek and Industry Managing Director, Advanced Technology Group in the Office of the CTO at VMware. You can find Matthew on LinkedIn and Twitter. Brian Hayes is an audiophile, dad, builder of sheds, maker of mirth, world traveller and EMEA Financial Services Industry Lead at VMware. You can find Brian on LinkedIn.
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