Today we’re joined by Bryan Carstens, a professor in the Department of Evolution, Ecology, and Organismal Biology & Head of the Tetrapod Division in the Museum of Biological Diversity at The Ohio State University. In our conversation with Bryan, who comes from a traditional biology background, we cover a ton of ground, including a foundational layer of understanding for the vast known unknowns in species and biodiversity, and how he came to apply machine learning to his lab’s research. We explore a few of his lab’s projects, including applying ML to genetic data to understand the geographic and environmental structure of DNA, what factors keep machine learning from being used more frequently used in biology, and what’s next for his group. The complete show notes for this episode can be found at twimlai.com/go/449.

Facebook routinely deploys recommendation systems and predictive models that affect the lives of billions of people everyday. That kind of reach comes with great responsibility — among other things, the responsibility to develop AI tools that ethical, fair and well characterized. This isn’t an easy task. Human beings have spent thousands of years arguing about what “fairness” and “ethics” mean, and haven’t come close to a consensus. Which is precisely why the responsible AI community has to involve as many disparate perspectives as possible in determining what policies to explore and recommend — a practice that Facebook’s Responsible AI team has applied itself. For this episode of the podcast, I’m joined by Joaquin Quiñonero-Candela, the Distinguished Tech Lead for Responsible AI at Facebook. Joaquin has been at the forefront of the AI ethics and fairness movements for years, and has overseen the formation of Facebook’s responsible AI team. As a result, he’s one of relatively few people with hands-on experience making critical AI ethics decisions at scale, and seeing their effects. Our conversation covered a lot of ground, from philosophical questions about the definition of fairness, to practical challenges that arise when implementing certain ethical AI frameworks.

Simon takes you through more updates and new things to explore! Chapters: 01:03 AWS Marketplace, 01:43 Analytics, 12:03 Application Integration, 13:41 Block Chain, 14:06 Business Applications, 14:16 Compute, 17:37 Cost Management, 18:09 Customer Engagement, 18:33 Database, 20:46 Developer Tools, 22:07 End User Computing, 22:33 Game Tech, 22:50 Internet of Things (IoT), 25:33 Machine Learning, 26:39 Management & Governance, 31:43 Migration & Transfer, 32:10 Mobile, 32:47 Networking & Content Delivery, 37:14 Quantum Technologies, 37:36 Security, Identity and Compliance, 39:22 Storage Extended Shownotes: https://d29iemol7wxagg.cloudfront.net/420ExtendedShownotes.html

Jeremy Burton (@jburton, CEO @Observe_Inc; board member @SnowflakeDB ) talks about the differences between traditional IT companies and Cloud-First companies, from product planning and roadmaps, to customer engagements and marketing messaging.  *SHOW: *484 *SHOW SPONSOR LINKS:* * Okta - You should not be building your own Auth * Learn how Okta helped Cengage improve student success rates during COVID. * BMC Wants to Know if your business is on its A-Game * BMC Autonomous Digital Enterprise * Datadog Security Monitoring Homepage - Modern Monitoring and Analytics * Try Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirt. *CLOUD NEWS OF THE WEEK *- http://bit.ly/cloudcast-cnotw *CHECK OUT OUR NEW PODCAST - **"CLOUDCAST BASICS"* *SHOW NOTES:* * Observe Homepage * Snowflake Homepage - The Data Cloud *Topic 1 *- Welcome to the show. We’ve known each other for a while. You’ve had tremendous success in Leadership, Product and Marketing roles in the past. Tell our audience a little bit of your background and what ultimately brought you to your role at CEO of Observe.  *Topic 1a* - For people that aren’t familiar, what does Observe bring to the market?  *Topic 2 *- We wanted to do a little “before-and-after”, and focus on what it means to be a “Cloud-First” company. What are the most obvious differences between a company like Observe and a company like Dell or EMC? *   * *Topic 3 *- From a product perspective, how do you think about roadmaps and the ways in which you enable new features for customers? Since Observe runs only in the public cloud, how much do you need to think about integrating with the native cloud services?  *Topic 4 *- You have deep expertise in creating marketing messaging, but so much of how customers learn about your products is no longer the company website. How do you think about reaching potential customers, or generally getting your message into the market? *Topic 5 *- Traditional IT was often aligned to centralized buying and architecture groups. How much does Cloud-First change the consumption models for companies - experimentation, on-demand usage, dealing with scaling issues, etc. *Topic 6 *- Overall, what are some of the biggest lessons you’ve learned about the Cloud-First approach as you’ve transitioned over the last 3+ years.  *FEEDBACK?* * Email: show at thecloudcast dot net * Twitter: @thecloudcastnet

Shawn Wildermuth of The Hello World film discusses diversity and inclusivity in software development. Host Felienne  spoke with Wildermuth about why diversity matters to make better software, and how teams can create a culture in which more people feel welcome and safe. They also discuss how to do code reviews, feedback sessions and job interviews […]

In this episode I speak with Daniel McKenna about Rust, machine learning and artificial intelligence. You can find Daniel from * http://github.com/xd009642 * https://twitter.com/xd009642 Don't forget to come join me in our Discord channel speaking about all things data science. Subscribe to the official Newsletter and never miss an episode

In this episode, we'll be discussing two powerful tools for data reporting and exploration: Datasette and Dogsheep. Datasette helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API. Dogsheep is a collection of tools for personal analytics using SQLite and Datasette. Imagine a unified search engine for everything personal in your life such as twitter, photos, google docs, todoist, goodreads, and more, all in once place and outside of cloud companies. On this episode we talk with Simon Willison who created both of these projects. He's also one of the co-creators of Django and we'll discuss some early Django history! Links from the show *Datasette*: datasette.io *Dogsheep*: dogsheep.github.io *Datasheet newsletter*: datasette.substack.com *Video: Build your own data warehouse for personal analytics with SQLite and Datasette*: youtube.com *Examples* *List*: github.com *Personal data warehouses*: github.com *Global power plants*: datasettes.com *SF data*: datasettes.com *FiveThirtyEight*: fivethirtyeight.datasettes.com *Lahman’s Baseball Database*: baseballdb.lawlesst.net *Live demo of current main*: datasette.io Sponsors Linode Talk Python Training

Returning today is the great and brilliant Peter Durlach, Senior Vice President of Healthcare Strategy for Nuance Communications, one of the pioneer and leading companies in conversational AI innovations, servicing the Healthcare space with AI products for well over a decade. Peter today helps us understand who in Healthcare is adopting AI, what common factors make businesses more or less common to adopt AI, and provides us insights into the technical ability, resources, and culture required for AI adoption. Want to learn more about adopting and applying Artificial Intelligence? Get Emerj's PDF guide: https://emerj.com/beg1

Want to be featured as a guest on Making Data Simple? Reach out to us at [almartintalksdata@gmail.com] and tell us why you should be next. *Abstract* Hosted by Al Martin, VP, IBM Expert Services Delivery, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. * *This week on Making Data Simple, we have Lynne Snead. Lynne is the founder of Talent Evolution Systems, a behavioral analyst, consultant, training specialist, speaker, coach. Lynne has a back ground in Educational Psychology, and has specialized in organizational performance for over 20 years. Lynne is one of the original Franklin Covey co-authors, has a best seller, she created Franklin Covey’s signature Project Development process and programs, worked directly with Stephen R Covey Senior and Stephen MR Covey Junior. Lynne started her own company in 2003. *Show Notes* 3:40 – Any advice on soft skills and hard skills? 8:35 – Telltale signs such as stress 10:40 – Settings goals  *Connect with the Team *Producer Kate Brown - LinkedIn Producer Steve Templeton - LinkedIn Host Al Martin - LinkedIn and Twitter Books Thinking Fast and Slow  Financial Intelligence  Other notable names Brene Brown Judith Glaser Marshall Goodsmith Daniel Goleman Lynne’s List of Recommended Leadership Books * Leadership and Self Deception, Arbinger Institute * 7 Habits of Highly Effective People, Stephen R. Covey (Senior) * 5 Levels of Leadership, John Maxwell.  * What Got You Here Won’t Get You There, Marshall Goldsmith * Conversational Intelligence, Judith Glaser * The Speed of Trust, Stephen M.R. Covey (Junior)  * Emotional Intelligence, Daniel Goleman * The New Art of Managing People, Tony Alessandra and Phil Hunsaker * How to Influence People, John Maxwell * Humble Inquiry, Edgar H. Schein  * Humble Leadership, Edgar H. Schein and Peter Schein * Leadership is an Art, Max De Pree * The Secrets to Winning at Office Politics, Marie G. McIntyre * The Power of Focus, Jack Canfield, Mark Victor Hansen, Les Hewitt * The Power of Self-Confidence, Brian Tracy

Scott Piper is an AWS security consultant at Summit Route, a company he founded in 2017. He’s also the developer of flaws.cloud and an organizer for the virtual fwd:cloudsec conference. Scott brings 15 years of tech experience to his current position, having worked as director of security at a cybersecurity company, a security engineer at Yelp, and a software engineer at the NSA, among other positions. Join Corey and Scott as they talk about why Scott decided to start an AWS security consultancy, what it was like for Scott to quit his job only to find out the people he thought needed his services wanted him to work for free, how Scott came around to building CloudMapper and CloudTracker, what both of those tools do, why it’s important to define what kind of consultant you are going to be and find your niche, the psychological aspect of running your own business, and more.

**Private data, Data Science friendly** Data Scientists are always eager to get their hands on more data, in particular, if that data has any value that can be extracted. Nevertheless, in real-world situations, data does not exist in the abundance that we thought existed, in other situations, the data might exist, but not possible to share it with different entities due to privacy concerns, which makes the work of data scientists not only hard, but sometimes even impossible. // Abstract: In the last episode of this series, we've decided to bring not one, but two guests to tells us how Synthetic data can unlock the use of data for Data Science teams whenever privacy concerns are a reality.  Jean-François Rajotte, Researcher and Resident data Scientist at the University of Columbia and Sumit Mukherjee, Senior Applied Scientist at Microsoft's AI for Good, bring us into more detail their expertise not only, in Synthetic data generation, but in it's mind blowing combination with Federated Learning to take the healthcare sector into the next level of AI adoption. //Other links to check on Jean-François Rajotte: https://venturebeat.com/2021/01/20/microsofts-felicia-taps-ai-to-enable-health-providers-to-share-data-anonymously/ https://dsi.ubc.ca/ https://leap-project.github.io/ //Other links to check on Sumit Mukherjee: www.sumitmukherjee.com (Sumit research) https://arxiv.org/abs/2101.07235 https://arxiv.org/pdf/2009.05683.pdf https://github.com/microsoft/privGAN (PrivGan) //Final thoughts Feel free to drop some questions into our slack channel (https://go.mlops.community/slack)  Watch some of the other podcast episodes and old meetups on the channel: https://www.youtube.com/channel/UCG6qpjVnBTTT8wLGBygANOQ ----------- Connect With Us ✌️------------- Join our Slack community:  https://go.mlops.community/slack Follow us on Twitter:  @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Fabiana on LinkedIn: https://www.linkedin.com/in/fabiana-clemente/ Connect with Jean-François on LinkedIn: https://www.linkedin.com/in/jfraj/ Connect with Sumit on LinkedIn: https://www.linkedin.com/in/sumitmukherjee2/

Aside from victory questions like “can black force a checkmate on white in 5 moves?” many novel questions can be asked about a game of chess. Some questions are trivial (e.g. “How many pieces does white have?") while more computationally challenging questions can contribute interesting results in computational complexity theory. In this episode, Josh Brunner, Master's student in Theoretical Computer Science at MIT, joins us to discuss his recent paper Complexity of Retrograde and Helpmate Chess Problems: Even Cooperative Chess is Hard. Works Mentioned Complexity of Retrograde and Helpmate Chess Problems: Even Cooperative Chess is Hard by Josh Brunner, Erik D. Demaine, Dylan Hendrickson, and Juilian Wellman 1x1 Rush Hour With Fixed Blocks is PSPACE Complete by Josh Brunner, Lily Chung, Erik D. Demaine, Dylan Hendrickson, Adam Hesterberg, Adam Suhl, Avi Zeff

Joocelyn hosts the Git Cute podcast, which you can find here. She's working on a book about seniority in the software industry, which you can pre-order here. You can follow her on Twitter at javavvitch. Our lifeboat badge goes to LMc for explaining how one can: Count the Letter Frequency in a String with Python

What is it like to design a Python library for three different audiences? This week on the show, we have Nir Aides, creator of Jupylet. His new library is designed for deep reinforcement learning researchers, musicians interested in live music coding, and kids interested in learning to program. Everything is designed to run inside of a Jupyter notebook.

All about section 230 of the Communications Decency Act -- what does and doesn't it say? How does this law play out against broader questions and debates around platforms, content moderation, and free speech? This conversation between Mike Masnick (founder and editor in chief of Techdirt) and a16z editor in chief Sonal Chokshi was originally published May 2020, in the context of_ previous _protests and presidential tweets (and an executive order then to prevent “online censorship”)-- but is exactly as relevant today... perhaps now more than ever. https://a16z.com/2020/05/31/16mins-section-230-communications-decency-act-content-moderation-free-speech-internet-past-present-future/ _image: presidential tweet activity/ Wikimedia Commons_

Cost management is growing in importance for companies that want to manage their significant cloud bill. Kubernetes plays an increasing role in modern infrastructure, so managing cost of Kubernetes clusters becomes important as well. Kubecost is a company focused on giving visibility into Kubernetes resources and reducing spend. Webb Brown is a founder of Kubecost The post Kubecost with Webb Brown appeared first on Software Engineering Daily.

A vast array of powerful data visualization tools are gaining traction in enterprises looking to make sense of their data sets, for instance D3, Bokeh, Shiny and Dash. In this episode, our team explores to concept of data visualization as part of a complete digital experience, with the workflows and journeys of a wide variety of users.

Claudia Perlich joins us to discuss her work at one of the world’s largest hedge funds and how she got to work there, as well as her history of winning data science competitions. In this episode you will learn: • Life and work during the pandemic [2:23] • Claudia’s history with horses and riding [8:28] • Claudia’s work at Two Sigma [12:00] • Claudia’s role on a daily basis [20:51] • Tools of the trade [30:27] • What Claudia looks for when hiring [36:37] • What skills do future hires need? [40:32] • Claudia’s history with data science competitions [48:22] • Why work in finance and at Two Sigma? [1:00:19] Additional materials: www.superdatascience.com/437