cloud technology

Private cloud remains an important aspect of an effective cloud posture. But it might not be how you remember it. This episode of Cloud Talk goes in-depth with three IT leaders to explore the history of private cloud, how it has evolved and where it’s going.

Cloud Do You Do, Petr? Special guest Petr Baudiš from a czech startup Rossum.ai talks about the next “evolution phase” of AI, customer centric approach, sustainability and his love for a Go game. Listen to what does an expert with a PhD. in AI has to say.

Try www.rossum.ai and explore their AI product in a free trial. Rossum automates document communication between you and your business partners. No matter if they use snail mail or send millions of different PDFs to hundreds of your inboxes.  Let us know how you like it.

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We are Revolgy - a leading European cloud partner with cloud teams around the world. Our cloud engineers and architects provide professional and managed services for your projects on GCP and AWS. In a nutshell, we help to make life digital-native companies and SMBs in the cloud easier. Check our website revolgy.com for more information.

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On this episode of The Artists of Data Science, we get a chance to hear from Carl Osipov, who has nearly two decades of information technology experience spanning roles such as program manager at Google, an IT executive at IBM, and as an adviser to Fortune 500 companies. Today, he's here to talk about his book, “Serverless Machine Learning In Action”, which is targeted at teams and individuals who are interested in building machine learning system implementations efficiently at scale. Carl shares with us his take on the future impacts of machine learning, the creative process in feature engineering, and important soft skills that data scientists need to develop. Carl’s expertise and advice will resonate with beginners and senior data scientists alike. It was a great pleasure speaking with him! WHAT YOU'LL LEARN [5:01] Hype in machine learning and how it’s changed [8:58] The potential negative impacts of machine learning [38:21] Is machine learning an art or science? [51:47] Important soft skills you need to succeed [54:23] Tips on communicating with executives QUOTES [12:00] “I think what will make data scientists of tomorrow successful is going to be more about the understanding of human culture.” [58:03] “The most important lesson is to be persistent and continue focusing on that one successful outcome. You only need to be successful once, so don't worry about any of those individual failures.” [58:50] “Whenever you collaborate with someone and you're willing to learn from them, you're going to come away as a person who really grows as an individual…” SHOW NOTES [00:01:33] Introduction for our guest today [00:03:03] What drew you to this field? What were some of the challenges you faced breaking into the field? [00:04:46] How much more hyped has machine learning become since you first kind of broke into this? [00:05:59] Where do you see now the field of machine learning headed in the next two to five years? [00:07:41] What do you see being the biggest positive impact coming from machine learning in the next two to five years? [00:08:52] What do you think would be the scariest application of machine learning in the next two to five years? [00:10:55] What are some things that we should keep on top of our mind as areas of concern so that we can kind of mitigate the risk of these scary applications? [00:11:45] What do you think will separate the great Data scientists from just the good ones? [00:13:48] What is serverless machine learning and how is it different from regular old fashioned machine learning? [00:17:10] So what is the difference between machine learning code and machine learning platform? [00:19:14] What is it about the contemporary practice of machine learning that tends to just suck our productivity from the practitioner? [00:21:24] At what point then does it make sense for us to start using serverless machine learning? [00:23:05] The difference between row-oriented and column-oriented storage. [00:27:21] A hypothetical scenario where serverless machine learning would an ideal use case. [00:28:52] What tips you can share with our audience so that we can be more thoughtful with our feature engineering. [00:31:55] What are some tips that you can share with our audience so that we can be more thoughtful in our hyperparameter tuning? [00:34:17] What do we do once a model is put into production? [00:38:07] Is data science an art? Or is it purely a science? [00:39:51] The creative process in data science [00:43:19] The democratization of machine learning [00:45:21] What would you say was the biggest lesson you learned about democratization of A.I. while you're over at Google? [00:46:16] We discuss the many patents Carl has published [00:48:53] Which of your publications, your patents do you think are most applicable to our current times? [00:51:24] What soft-skills do you need to be successful? [00:53:49] How to communicate with executives [00:55:54] How to develop your product sense and business acumen [00:57:10] Why you shouldn’t be discouraged by these insane job descriptions [00:58:16] What’s the one thing you want to people to learn from your story? [00:59:03] Where can people find your book? [00:59:44] What's your data science superpower? [00:59:59] If AI could answer any question for you, what would you ask? [01:00:05] What do you believe that other people think is crazy? [01:00:21] If you could have a billboard anywhere. What would you put on it? [01:00:31] What is an academic topic outside of Data science that you think every data scientist should spend some time studying and researching on? [01:00:48] What would be the number one book? Fiction, nonfiction, or maybe one of each that you would recommend our audience read. And what was your most impactful takeaway from it? [01:01:21] If we can get a magic telephone that allowed you to contact 18 year old Carl, what would you tell him? [01:01:39] What's the best advice you have ever received? [01:01:43] What motivates you? [01:01:46] What song do you currently have on repeat? [01:01:56] How can people connect with you and what can they find you online? Special Guest: Carl Osipov.

Of all the ways to answer the question, “How do I become cloud native?” the first answer that typically comes to mind – technology – is also the wrong one. Listen in as Rackspace Technology's VP of AWS Solutions, and Myles Anderson, Rackspace Technology's VP of AWS Professional Services, discuss the mindsets and processes that drive cloud native success. Special Guests: Myles Anderson and Taylor Bird.

Millions suddenly find themselves working from home, forcing companies to rethink key aspects of their business. This episode of Cloud Talk explores the importance of communications, security, equipping and supporting staff, disaster planning, critical spending, and the importance of flexibility — all to position your organization for success in an uncertain future. Special Guest: Mike Woolard.

Domo for Good connects nonprofits with Domo customers for best-in-class data support, says Domo's Chief Communications Officer, Julie Kehoe. 

Many businesses are beginning to trial methods to share their technology, people, skills and expertise with the wider world for the simple benefit of improving the wider world. In practice it is anything but simple, and yet Domo, a Utah-based data visualization and cloud software company, has become one of the first in its sector to create a purpose-driven arm: Domo for Good. 

Learn how Domo for Good was created after a chance encounter between a client and a nonprofit at its event, Domopalooza, and why data is a resource most lacking in businesses that need it the most, as well as the challenges of setting up a purpose brand within a profit-making enterprise.

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