Craig Wiley's guest appearances

Craig Wiley

Google Cloud Platform Podcast

Permission To Lead with Cindy Monroe

Dave Elliott

Andrew Walker

Peter Norvig

Eric Anderson

John Bohannon

Manuel Lima

Margaret Mitchell

Jessie Frazelle

Joanna Smith

Juliet Hougland

Michelle Casbon

Jesse Houston

Mark Chmarny

Ville Aikas

Dale Markowitz

OwlTail

Have you ever reached a point where leadership feels a lot more exhausting than it does fun? I’ve been there. With sales declining and my frustration at myself and the business growing, I knew I needed help. And that’s when I met my coach and guest on today’s podcast, Craig Wiley. Craig helped me get unstuck and focus on what I knew to be true about the business, our consultants, customers, and myself. When Craig first started coaching me, I remember telling him, “I want to stop being a hot mess of a leader.” Well, that changed dramatically once we started working together!Today, Craig reveals what to do if you feel like you’ve lost your inner coach and don’t trust yourself anymore. Plus, the surprising difference between a leader that reacts and a leader that responds. Then, Craig gives us a little rapid-fire coaching session on 5 specific areas high-achieving female leaders struggle with. If you’re feeling burnt out from growing your business or struggling to trust yourself, this is the episode for you.Learn more about Craig HERE. Download your exclusive goal-setting FREE PDF HERE.Buy your copy of Cindy’s new book, More Than a Bag, HERE. For daily leadership + business tips, follow Cindy on Instagram HERE.

Have you ever reached a point where leadership feels a lot more exhausting than it does fun? I’ve been there. With sales declining and my frustration at myself and the business growing, I knew I needed help. And that’s when I met my coach and guest on today’s podcast, Craig Wiley.  Craig helped me get unstuck and focus on what I knew to be true about the business, our consultants, customers, and myself. When Craig first started coaching me, I remember telling him, “I want to stop being a hot mess of a leader.” Well, that changed dramatically once we started working together! Today, Craig reveals what to do if you feel like you’ve lost your inner coach and don’t trust yourself anymore. Plus, the surprising difference between a leader that reacts and a leader that responds. Then, Craig gives us a little rapid-fire coaching session on 5 specific areas high-achieving female leaders struggle with.  If you’re feeling burnt out from growing your business or struggling to trust yourself, this is the episode for you. Learn more about Craig <a href="https://transcendbusiness.com/coaches/craig-wiley/" rel="nofollow" target="_blank">HERE</a>. Download your exclusive goal-setting <a href="https://view.flodesk.com/pages/63b497dc37a7fb86b1f98c50" rel="nofollow" target="_blank">FREE PDF HERE</a>.Buy your copy of Cindy’s new book, More Than a Bag, <a href="https://www.amazon.com/More-than-Bag-Celebrating-Thirty-One/dp/1955051119/ref=sr_1_1?crid=1AAYT0P73YFVA&amp;keywords=more+than+a+bag&amp;qid=1673547185&amp;sprefix=more+than+a+bag%2Caps%2C108&amp;sr=8-1" rel="nofollow" target="_blank">HERE</a>. For daily leadership + business tips, follow Cindy on Instagram <a href="https://www.instagram.com/cindymmonroe/" rel="nofollow" target="_blank">HERE</a>.

Episode 7: How to Combat Leadership Burnout: Exclusive Coaching Session with Craig Wiley

Tracy Frey

Stephanie Wong and Priyanka Vergadia host the podcast this week as we talk responsible AI with guests Craig Wiley and Tracy Frey. Vertex AI, the newly released AI platform from Google, is where Craig starts, telling us that it helps seamlessly integrate AI best practices into AI projects. When designing and building machine learning projects, it’s important to plan and integrate functions that support a responsible model as well. Tracy and Craig help us understand the process of designing and building these responsible, efficient projects, from problem identification and data set collection and refinement to ethical model considerations and finally project construction. Part of Responsible AI is considering all the stakeholders of a project and how they will be impacted. Through examples, Tracy demonstrates how businesses can decide if the software solution affects stakeholders in a way the business would be proud of. Starting in the planning stages and continuing through data collection and model training, companies employing responsible AI techniques will consider input from groups that may use or be affected by the model, from social scientist who specialize in human behavior, and others. Craig elaborates on these principles in the context of Vertex AI and how the time savings of Vertex could be used to make thoughtful, responsible AI decisions. Craig teaches us more about Vertex as we wrap up the interview. Its ability to analyze data and perform ongoing model monitoring make for richer, more accurate projects. Tracy talks about the future of Responsible AI and how the marriage of tech and humanity will continue to produce ethical, effective AI projects. Craig Wiley Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, and he pushes to improve the tooling for experienced users while seeking to simplify it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects. Tracy Frey Tracy Frey is Google Cloud AI &amp; Industry Solution’s Managing Director of Outbound Product Management, Incubation and Responsible AI and is dedicated to ensuring Google Cloud AI &amp; Industry Solutions is responsible, thoughtful, and collaborative as it continues to advance artificial intelligence and machine learning. She has been at Google for more than 10 years where she has worked on many different products and areas. Before joining Google she worked at multiple early-stage tech startups where she held multiple functions including product management, developer relations, product marketing, business development and strategy. Prior to her life in tech she taught children traditional wilderness survival skills, taught in a traditional classroom, studied private reserves in Costa Rica and has been a professional hip hop dancer. Cool things of the week  Cloud CISO Perspectives: May 2021  blog The cloud developer’s guide to Google I/O 2021  blog  Interview  Vertex AI  site Responsible AI site Staying ahead of the curve – The business case for responsible AI  article Building responsible AI for everyone site Cloud Storage site BigQuery site Data Cloud Summit site Applied ML Summit site GCP Podcast Episode 249: ML Lifecycle with Dale Markowitz and Craig Wiley  podcast AI Edition Google’s Tracy Frey: Creating Responsible AI  podcast TensorFlow Responsible AI Toolkit site  What’s something cool you’re working on? Priyanka has been working on the Vertex AI video series. Episode 1 and episode 2 are available now!

<a href="https://twitter.com/stephr_wong" rel="nofollow" target="_blank">Stephanie Wong</a> and <a href="https://twitter.com/pvergadia" rel="nofollow" target="_blank">Priyanka Vergadia</a> host the podcast this week as we talk responsible AI with guests Craig Wiley and <a href="https://twitter.com/tracyfrey" rel="nofollow" target="_blank">Tracy Frey</a>. Vertex AI, the newly released AI platform from Google, is where Craig starts, telling us that it helps seamlessly integrate AI best practices into AI projects. When designing and building machine learning projects, it’s important to plan and integrate functions that support a responsible model as well. Tracy and Craig help us understand the process of designing and building these responsible, efficient projects, from problem identification and data set collection and refinement to ethical model considerations and finally project construction. Part of Responsible AI is considering all the stakeholders of a project and how they will be impacted. Through examples, Tracy demonstrates how businesses can decide if the software solution affects stakeholders in a way the business would be proud of. Starting in the planning stages and continuing through data collection and model training, companies employing responsible AI techniques will consider input from groups that may use or be affected by the model, from social scientist who specialize in human behavior, and others. Craig elaborates on these principles in the context of Vertex AI and how the time savings of Vertex could be used to make thoughtful, responsible AI decisions. Craig teaches us more about Vertex as we wrap up the interview. Its ability to analyze data and perform ongoing model monitoring make for richer, more accurate projects. Tracy talks about the future of Responsible AI and how the marriage of tech and humanity will continue to produce ethical, effective AI projects. Craig Wiley Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, and he pushes to improve the tooling for experienced users while seeking to simplify it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects. Tracy Frey Tracy Frey is Google Cloud AI &amp; Industry Solution’s Managing Director of Outbound Product Management, Incubation and Responsible AI and is dedicated to ensuring Google Cloud AI &amp; Industry Solutions is responsible, thoughtful, and collaborative as it continues to advance artificial intelligence and machine learning. She has been at Google for more than 10 years where she has worked on many different products and areas. Before joining Google she worked at multiple early-stage tech startups where she held multiple functions including product management, developer relations, product marketing, business development and strategy. Prior to her life in tech she taught children traditional wilderness survival skills, taught in a traditional classroom, studied private reserves in Costa Rica and has been a professional hip hop dancer. Cool things of the week <ul> <li>Cloud CISO Perspectives: May 2021 <a href="https://cloud.google.com/blog/products/identity-security/cloud-ciso-perspectives-may-2021" rel="nofollow" target="_blank"> blog</a></li> <li>The cloud developer’s guide to Google I/O 2021 <a href="https://cloud.google.com/blog/topics/developers-practitioners/cloud-developers-guide-google-io-2021" rel="nofollow" target="_blank"> blog</a></li> </ul> Interview <ul> <li>Vertex AI <a href="https://cloud.google.com/vertex-ai?utm_source=blog&amp;utm_medium=partner&amp;utm_campaign=CDR_swo_aiml_vertexai_gcppodcast_052021" rel="nofollow" target="_blank"> site</a></li> <li>Responsible AI <a href="https://cloud.google.com/responsible-ai" rel="nofollow" target="_blank">site</a></li> <li>Staying ahead of the curve – The business case for responsible AI <a href="https://www.eiu.com/n/staying-ahead-of-the-curve-the-business-case-for-responsible-ai/" rel="nofollow" target="_blank"> article</a></li> <li>Building responsible AI for everyone <a href="https://ai.google/responsibilities/" rel="nofollow" target="_blank">site</a></li> <li>Cloud Storage <a href="https://cloud.google.com/storage" rel="nofollow" target="_blank">site</a></li> <li>BigQuery <a href="https://cloud.google.com/bigquery" rel="nofollow" target="_blank">site</a></li> <li>Data Cloud Summit <a href="https://cloudonair.withgoogle.com/events/summit-data-cloud" rel="nofollow" target="_blank">site</a></li> <li>Applied ML Summit <a href="https://cloudonair.withgoogle.com/events/summit-ml-practitioners" rel="nofollow" target="_blank">site</a></li> <li>GCP Podcast Episode 249: ML Lifecycle with Dale Markowitz and Craig Wiley <a href="https://www.gcppodcast.com/post/episode-249-ml-lifecycle-with-dale-markowitz-and-craig-wiley/" rel="nofollow" target="_blank"> podcast</a></li> <li>AI Edition Google’s Tracy Frey: Creating Responsible AI <a href="https://open.spotify.com/episode/0OKZN2PhM9p6P8Lwn7oQrR?si=WXAYe353TfGsmOXGi_e4Yw" rel="nofollow" target="_blank"> podcast</a></li> <li>TensorFlow Responsible AI Toolkit <a href="https://www.tensorflow.org/responsible_ai" rel="nofollow" target="_blank">site</a></li> </ul> What’s something cool you’re working on? Priyanka has been working on the Vertex AI video series. <a href="https://www.youtube.com/watch?v=gT4qqHMiEpA" rel="nofollow" target="_blank">Episode 1</a> and <a href="https://www.youtube.com/watch?v=CN2X6oIlnmI" rel="nofollow" target="_blank">episode 2</a> are available now!

Responsible AI with Craig Wiley and Tracy Frey

Jenny Brown co-hosts with Mark Mirchandani this week for a great conversation about the ML lifecycle with our guests Craig Wiley and Dale Markowitz. Using a real-life example of bus cameras detecting potholes, Dale and Craig walk us through the steps of designing, building, implementing, and improving on a piece of machine learning software. The first step, Craig tells us, is to identify the data collected and determine its viability in an ML model. He describes how to get the best data for your project and how to keep the data, code, and libraries consistent to allow better analysis by your ML models. He talks about the importance of a Feature Store to aid in data consistency. Craig explains how machine learning pipelines like TensorFlow are great tools to improve consistency in the ML environment as well, making it easier to improve your model and even to build new ones using the same data. Keeping this consistency from data scientist analyzation to ML developer to model deployment means a more efficient process and product. Evaluating models after production is an important step in the lifecycle as well to ensure accuracy, validity, and performance of the model. Craig gives us some examples and tips on monitoring models after they’ve been deployed. We talk about the challenges of scaling ML projects and Craig offers advice for developers and companies looking to build ML projects. Dale Markowitz Dale Markowitz is an Applied AI Engineer for ML on Google Cloud. Before that, she was a software engineer in Google Research and an engineer at the online dating site OkCupid. Craig Wiley Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon, as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, he pushes to improve the tooling for experienced users while seeking to simplifying it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects. Cool things of the week  Introducing GKE Autopilot: a revolution in managed Kubernetes  blog At your service! With schedule-based autoscaling, VMs are at the ready  blog  Interview  Google Cloud AI and Machine Learning Products site GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark  podcast Using machine learning to improve road maintenance  blog Key requirements for an MLOps foundation  blog TensorFLow site Kubeflow Pipelines site TensorBoard site How to dub a video with AI video Can AI make a good baking recipe? video Machine learning without code in the browser video  What’s something cool you’re working on? Jenny started a new podcast that reads interesting Google blog posts over at Google Cloud Reader. Our friend Dr. Anton Chuvakin started the Cloud Security Podcast by Google. Read more about it and listen  here. Follow the show and hosts on Twitter Cloud Security Podcast Anton and Tim And listen to Anton on the  GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniak.

Jenny Brown co-hosts with <a href="https://twitter.com/markmirch" rel="nofollow" target="_blank">Mark Mirchandani</a> this week for a great conversation about the ML lifecycle with our guests Craig Wiley and Dale Markowitz. Using a real-life example of bus cameras detecting potholes, Dale and Craig walk us through the steps of designing, building, implementing, and improving on a piece of machine learning software. The first step, Craig tells us, is to identify the data collected and determine its viability in an ML model. He describes how to get the best data for your project and how to keep the data, code, and libraries consistent to allow better analysis by your ML models. He talks about the importance of a Feature Store to aid in data consistency. Craig explains how machine learning pipelines like TensorFlow are great tools to improve consistency in the ML environment as well, making it easier to improve your model and even to build new ones using the same data. Keeping this consistency from data scientist analyzation to ML developer to model deployment means a more efficient process and product. Evaluating models after production is an important step in the lifecycle as well to ensure accuracy, validity, and performance of the model. Craig gives us some examples and tips on monitoring models after they’ve been deployed. We talk about the challenges of scaling ML projects and Craig offers advice for developers and companies looking to build ML projects. Dale Markowitz Dale Markowitz is an Applied AI Engineer for ML on Google Cloud. Before that, she was a software engineer in Google Research and an engineer at the online dating site OkCupid. Craig Wiley Craig is the Director of Product for Google Cloud’s AI Platform. Previous to Google, Craig spent nine years at Amazon, as the General Manager of Amazon SageMaker, AWS’ machine learning platform as well as in Amazon’s 3rd Party Seller Business. Craig has a deep belief in democratizing the power of data, he pushes to improve the tooling for experienced users while seeking to simplifying it for the growing set of less experienced users. Outside of work he enjoys spending time with his family, eating delicious meals, and enthusiastically struggling through small home improvement projects. Cool things of the week <ul> <li>Introducing GKE Autopilot: a revolution in managed Kubernetes <a href="https://cloud.google.com/blog/products/containers-kubernetes/introducing-gke-autopilot" rel="nofollow" target="_blank"> blog</a></li> <li>At your service! With schedule-based autoscaling, VMs are at the ready <a href="https://cloud.google.com/blog/products/compute/introducing-schedule-based-autoscaling-for-compute-engine" rel="nofollow" target="_blank"> blog</a></li> </ul> Interview <ul> <li>Google Cloud AI and Machine Learning Products <a href="https://cloud.google.com/products/ai" rel="nofollow" target="_blank">site</a></li> <li>GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark <a href="https://www.gcppodcast.com/post/episode-240-recaptcha-enterprise-kelly-anderson-springml-potholes-eric-clark/" rel="nofollow" target="_blank"> podcast</a></li> <li>Using machine learning to improve road maintenance <a href="https://cloud.google.com/blog/products/ai-machine-learning/video-intelligence-machine-learning-improves-pothole-detection" rel="nofollow" target="_blank"> blog</a></li> <li>Key requirements for an MLOps foundation <a href="https://cloud.google.com/blog/products/ai-machine-learning/key-requirements-for-an-mlops-foundation" rel="nofollow" target="_blank"> blog</a></li> <li>TensorFLow <a href="https://www.tensorflow.org" rel="nofollow" target="_blank">site</a></li> <li>Kubeflow Pipelines <a href="https://www.kubeflow.org/docs/pipelines/" rel="nofollow" target="_blank">site</a></li> <li>TensorBoard <a href="https://www.tensorflow.org/tensorboard" rel="nofollow" target="_blank">site</a></li> <li>How to dub a video with AI <a href="https://www.youtube.com/watch?v=T2TAAHmNBnE" rel="nofollow" target="_blank">video</a></li> <li>Can AI make a good baking recipe? <a href="https://www.youtube.com/watch?v=7sn8df97-JU" rel="nofollow" target="_blank">video</a></li> <li>Machine learning without code in the browser <a href="https://www.youtube.com/watch?v=i9tjzr1KME0" rel="nofollow" target="_blank">video</a></li> </ul> What’s something cool you’re working on? Jenny started a new podcast that reads interesting Google blog posts over at <a href="https://feeds.transistor.fm/google-cloud-reader" rel="nofollow" target="_blank">Google Cloud Reader</a>. Our friend Dr. Anton Chuvakin started the Cloud Security Podcast by Google. Read more about it and listen <a href="https://cloud.google.com/blog/products/identity-security/introducing-google-clouds-new-cloud-security-podcast" rel="nofollow" target="_blank"> here</a>. Follow the show and hosts on Twitter <a href="https://twitter.com/CloudSecPodcast" rel="nofollow" target="_blank">Cloud Security Podcast</a> <a href="https://twitter.com/anton_chuvakin" rel="nofollow" target="_blank">Anton</a> and <a href="https://twitter.com/_TimPeacock" rel="nofollow" target="_blank">Tim</a> And listen to Anton on the <a href="https://www.gcppodcast.com/post/episode-218-chronicle-security-with-dr-anton-chuvakin-and-ansh-patniak/" rel="nofollow" target="_blank"> GCP Podcast Episode 218: Chronicle Security with Dr. Anton Chuvakin and Ansh Patniak</a>.

ML Lifecycle with Dale Markowitz and Craig Wiley