Platforms Windows, Linux, Apple all the Tech Info you can Handle on the Various Platforms

By Tech Podcast Network

About this podcast   English    United States

Whether you are a Windows Fan, Linux Fanatic or a Apple Fanboy this is the place to check out all the variety of platforms.
133 episodes · since Jul, 2016
In this podcast

Windows

Apple

Technology

Machine generated. There may be errors. Report errors to us.
Episodes published before March 14, 2018
March 7, 2018
Dr. Fei-Fei Li, the Chief Scientist of AI/ML at Google joins Melanie and Mark this week to talk about how we enable businesses to solve critical problems through AI solutions. We talk about the work she is doing at Google to help reduce AI barriers to entry for enterprise, her research with Stanford combing AI and healthcare, what is the next stage of AI research and her efforts to overcome one of the challenges in AI by drive more diversity in the field. Dr. Fei-Fei Li Dr. Fei-Fei Li is the Chief Scientist of AI/ML at Google Cloud. She is also an Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab. Dr. Fei-Fei Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She has published more than 150 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR, ICCV, NIPS, ECCV, IJCV, IEEE-PAMI, etc. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She joined Stanford in 2009 as an assistant professor, and was promoted to associate professor with tenure in 2012. Prior to that, she was on faculty at Princeton University (2007-2009) and University of Illinois Urbana-Champaign (2005-2006). Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder of Stanford’s renowned SAILORS outreach program for high school girls and the national non-profit AI4ALL. For her work in AI, Dr. Li is a speaker at the TED2015 main conference, a recipient of the IAPR 2016 J.K. Aggarwal Prize, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2012 Yahoo Labs FREP award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship and a number of Google Research awards. Work from Dr. Li’s lab have been featured in a variety of popular press magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al. Cool things of the week Terah Lyons appointed founding executive director of Partnership on AI article & site Fully managed export and import with Cloud Datastore now generally available blog How Color uses the new Variant Transforms tool for breakthrough clinical data science with BigQuery blog & repo Google Cloud and NCAA team up for a unique March Madness copmetition hosted on Kaggle blog Interview AI4All site, they are hiring and how to become a mentor Cloud AI site Cloud AutoML site Cloud Vision API site and docs Cloud Speech API site and docs Cloud Natural Language API site and docs Cloud Translation API site and docs Cloud Machine Learning Engine docs TensorFlow site, github and Dev Summit waitlist ImageNet site & Kaggle ImageNet Competition site Stanford Medicine site & Stanford Children’s Hospital site Melinda Gates and Fei-Fei Li Want to Liberate AI from “Guy with Hoodies” article Additional sample resources on Dr. Fei-Fei Li: Citations site Stanford Vision Lab site Fei-Fei Li | 2018 MAKERS Conference video Google Cloud’s Li Sees Transformative Time for Enterprise video Past, Present and Future of AI / Machine Learning Google I/O video Research Symposium 2017 - Morning Keynote Address at Harker School video How we’re teaching computers to understand pictures video Dr. Fei-Fei Li Question of the week Where can I learn more about machine learning? Listing of some of the many resources out there in no particular order: How Google does Machine Learning coursera Machine Learning with Andrew Ng coursera and Deep Learning Specialization coursera fast.ai site Machine Learning with John W. Paisley edx Machine Learning Columbia University edx International Women’s Day March 8th International Women’s Day site covers information on events in your area, and additional resources. Sample of recent women in tech events to keep on radar for next year: Women Techmakers site Lesbians Who Tech site Women in Data Science Conference site Where can you find us next? Mark will be at the Game Developer’s Conference | GDC in March.
March 7, 2018
Dr. Fei-Fei Li, the Chief Scientist of AI/ML at Google joins Melanie and Mark this week to talk about how Google enables businesses to solve critical problems through AI solutions. We talk about the work she is doing at Google to help reduce AI barriers to entry for enterprise, her research with Stanford combining AI and health care, where AI research is going, and her efforts to overcome one of the key challenges in AI by driving for more diversity in the field. Dr. Fei-Fei Li Dr. Fei-Fei Li is the Chief Scientist of AI/ML at Google Cloud. She is also an Associate Professor in the Computer Science Department at Stanford, and the Director of the Stanford Artificial Intelligence Lab. Dr. Fei-Fei Li’s main research areas are in machine learning, deep learning, computer vision and cognitive and computational neuroscience. She has published more than 150 scientific articles in top-tier journals and conferences, including Nature, PNAS, Journal of Neuroscience, CVPR, ICCV, NIPS, ECCV, IJCV, IEEE-PAMI, etc. Dr. Fei-Fei Li obtained her B.A. degree in physics from Princeton in 1999 with High Honors, and her PhD degree in electrical engineering from California Institute of Technology (Caltech) in 2005. She joined Stanford in 2009 as an assistant professor, and was promoted to associate professor with tenure in 2012. Prior to that, she was on faculty at Princeton University (2007-2009) and University of Illinois Urbana-Champaign (2005-2006). Dr. Li is the inventor of ImageNet and the ImageNet Challenge, a critical large-scale dataset and benchmarking effort that has contributed to the latest developments in deep learning and AI. In addition to her technical contributions, she is a national leading voice for advocating diversity in STEM and AI. She is co-founder of Stanford’s renowned SAILORS outreach program for high school girls and the national non-profit AI4ALL. For her work in AI, Dr. Li is a speaker at the TED2015 main conference, a recipient of the IAPR 2016 J.K. Aggarwal Prize, the 2016 nVidia Pioneer in AI Award, 2014 IBM Faculty Fellow Award, 2011 Alfred Sloan Faculty Award, 2012 Yahoo Labs FREP award, 2009 NSF CAREER award, the 2006 Microsoft Research New Faculty Fellowship and a number of Google Research awards. Work from Dr. Li’s lab have been featured in a variety of popular press magazines and newspapers including New York Times, Wall Street Journal, Fortune Magazine, Science, Wired Magazine, MIT Technology Review, Financial Times, and more. She was selected as a 2017 Women in Tech by the ELLE Magazine, a 2017 Awesome Women Award by Good Housekeeping, a Global Thinker of 2015 by Foreign Policy, and one of the “Great Immigrants: The Pride of America” in 2016 by the Carnegie Foundation, past winners include Albert Einstein, Yoyo Ma, Sergey Brin, et al. Cool things of the week Terah Lyons appointed founding executive director of Partnership on AI article & site Fully managed export and import with Cloud Datastore now generally available blog How Color uses the new Variant Transforms tool for breakthrough clinical data science with BigQuery blog & repo Google Cloud and NCAA team up for a unique March Madness copmetition hosted on Kaggle blog Interview AI4All site, they are hiring and how to become a mentor Cloud AI site Cloud AutoML site Cloud Vision API site and docs Cloud Speech API site and docs Cloud Natural Language API site and docs Cloud Translation API site and docs Cloud Machine Learning Engine docs TensorFlow site, github and Dev Summit waitlist ImageNet site & Kaggle ImageNet Competition site Stanford Medicine site & Stanford Children’s Hospital site Additional sample resources on Dr. Fei-Fei Li: Citations site Stanford Vision Lab site Fei-Fei Li | 2018 MAKERS Conference video Google Cloud’s Li Sees Transformative Time for Enterprise video Past, Present and Future of AI / Machine Learning Google I/O video Research Symposium 2017 - Morning Keynote Address at Harker School video How we’re teaching computers to understand pictures video Melinda Gates and Fei-Fei Li Want to Liberate AI from “Guy with Hoodies” article Dr. Fei-Fei Li Question of the week Where can I learn more about machine learning? Listing of some of the many resources out there in no particular order: How Google does Machine Learning coursera Machine Learning with Andrew Ng coursera and Deep Learning Specialization coursera fast.ai site Machine Learning with John W. Paisley edx Machine Learning Columbia University edx International Women’s Day March 8th International Women’s Day site covers information on events in your area, and additional resources. Sample of recent women in tech events to keep on radar for next year: Women Techmakers site Lesbians Who Tech site Women in Data Science Conference site Where can you find us next? Mark will be at the Game Developer’s Conference | GDC in March.
Feb. 28, 2018
We have the pleasure this week of having the Director of Solutions for Google Cloud Miles Ward and Cloud Solutions Architect Grace Mollison join Mark and Melanie to discuss Solution Architects, what they do and how they interact with Customers at Google Cloud Platform. Miles Ward Miles Ward is a three-time technology startup entrepreneur with a decade of experience building cloud infrastructures. Miles is Director of Solutions for Google Cloud; focused on delivering next-generation solutions to challenges in big data and analytics, application migration, infrastructure automation, and cost optimization. He worked as a core part of the Obama for America 2012 “TECH” team, crashed Twitter a few times, helped NASA stream the Curiosity Mars Rover landing, put Skype back online in a pinch, and plays a mean electric sousaphone. Grace Mollison Based in London, UK, Grace Mollison is a Cloud Solutions Architect where she helps customers to understand how to apply policies to their Google cloud platform environments as well as how to architect and deploy applications on the Google Cloud platform. In her spare time she spends time attempting to teach her international team how to speak the Queens english! Before Google Grace was a Solutions Architect at AWS where she worked with the AWS ecosystem and customers to ensure well architected solutions. Cool things of the week We have awesome new intro and outro music. Did you notice? The thing is … Cloud IoT Core is now generally available blog site JupyterLab is Ready for Users blog github Announcing Google Cloud Spanner as a Vault storage backend blog How to handle mutating JSON schemas in a streaming pipeline, with Square Enix blog FAT* livestream Interview Google Cloud Platform Solutions site Tutorials and Solutions site Machine Learning with Financial Time Series Data solution Implementing GCP Policies for Customer Use Cases solution #87 Customer Engineers with Jonathan Cham podcast Google Cloud Next Solution Architects are hiring! careers Question of the week How do I get a Docker image into Minikube without uploading it to an external registry and then downloading it all over again? Is there an easy way to do this locally? Minikube github $ docker save <image> | (eval $(minikube docker-env) && docker load) Original references github Stack Overflow Where can you find us next? Mark will be at the Game Developer’s Conference | GDC in March.
Feb. 21, 2018
In this episode, Google Play Marketing is the customer of Google Cloud Platform. Melanie and Mark chat with Dom Elliott (Google Play) and Stewart Bryson (Red Pill Analytics) about how they use our big data processing and visualisation tools to introspect what is happening in the Google play ecosystem. Dom Elliott Dom Elliott lead global developer marketing communications for Google Play. My goal is to help Android app and game developers improve their app quality and business performance on Google Play, by raising awareness and understanding of features that can help them find success. Stewart Bryson Stewart Bryson is the Owner & Co-founder of Red Pill Analytics, a products and services company specializing in Cloud Analytics delivery. Red Pill is 4 years old and has about 30 employees in the US, UK and Brazil. We work with customers to accelerate their use of the public cloud for analytics, including migrating current on-premises workloads. Red Pill Analytics was engaged by Google Play to build the digital channel ingestion processes, as well as build all the Data Studio content for analyzing those channels. Cool things of the week Easy distributed training with TensorFlow using tf.estimator.train_and_evaluate on Cloud ML Engine blog tweet CI/CD with Less Fluff & More Awesome blog 96 vCPU Compute Engine instances are now generally available announcement site Interview Google Play site Google Data Studio site docs Adding charts to Data Studio docs Google BigQuery Data Transfer Service site docs Google App Engine site docs Cloud Cloud PubSub site docs Cloud Functions site docs Google Cloud Pub/Sub Triggers docs tutorial Cloud Natural Language site docs Google Play Question of the week If you want to be able to unit test your integrations with Kubernetes with client-go, how can you mock what happens inside the cluster in your unit tests? fake.Clientset godoc code example testing.Fake godoc Where can you find us next? Melanie will be at Fat* in New York very shortly! Mark will be at the Game Developer’s Conference | GDC in March.
Feb. 14, 2018
This week, we dive into machine learning bias and fairness from a social and technical perspective with machine learning research scientists Timnit Gebru from Microsoft and Margaret Mitchell (aka Meg, aka M.) from Google. They share with Melanie and Mark about ongoing efforts and resources to address bias and fairness including diversifying datasets, applying algorithmic techniques and expanding research team expertise and perspectives. There is not a simple solution to the challenge, and they give insights on what work in the broader community is in progress and where it is going. Timnit Gebru Timnit Gebru works in the Fairness Accountability Transparency and Ethics (FATE) group at the New York Lab. Prior to joining Microsoft Research, she was a PhD student in the Stanford Artificial Intelligence Laboratory, studying computer vision under Fei-Fei Li. Her main research interest is in data mining large-scale, publicly available images to gain sociological insight, and working on computer vision problems that arise as a result, including fine-grained image recognition, scalable annotation of images, and domain adaptation. The Economist and others have recently covered part of this work. She is currently studying how to take dataset bias into account while designing machine learning algorithms, and the ethical considerations underlying any data mining project. As a cofounder of the group Black in AI, she works to both increase diversity in the field and reduce the impact of racial bias in the data. Margaret Mitchell M. Mitchell is a Senior Research Scientist in Google’s Research & Machine Intelligence group, working on artificial intelligence. Her research involves vision-language and grounded language generation, focusing on how to evolve artificial intelligence toward positive goals. Margaret’s work combines machine learning, computer vision, natural language processing, social media, and insights from cognitive science. Before Google, Margaret was a founding member of Microsoft Research’s “Cognition” group, focused on advancing artificial intelligence, and a researcher in Microsoft Research’s Natural Language Processing group. Cool things of the week GPS/Cellular Asset Tracking using Google Cloud IoT Core, Firestore and MongooseOS blog GPUs in Kubernetes Engine now available in beta blog Announcing Spring Cloud GCP - integrating your favorite Java framework with Google Cloud blog Interview PAIR | People+AI Research Initiative site FATE | Fairness, Accountability, Transparency and Ethics in AI site Fat* Conference site & resources Joy Buolamwini site Algorithmic Justice Leaguge site ProPublica Machine Bias article AI Ethics & Society Conference site Ethics in NLP Conference site FACETS site TensorFlow Lattice repo Sample papers on bias and fairness: Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification paper Facial Recognition is Accurate, if You’re a White Guy article Mitigating Unwanted Biases with Adversarial Learning paper Improving Smiling Detection with Race and Gender Diversity paper Fairness Through Awareness paper Avoiding Discrimination through Casual Reasoning paper Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings paper Satisfying Real-world Goals with Dataset Constraints paper Axiomatic Attribution for Deep Networks paper Monotonic Calibrated Interpolated Look-Up Tables paper Equality of Opportunity in Machine Learning blog Additional links: Bill Nye Saves the World Episode 3: Machines Take Over the World (includes Margaret Mitchell) site “We’re in a diversity crisis”: Black in AI’s founder on what’s poisoning the algorithms in our lives article Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru TWiML & AI podcast Security and Safety in AI: Adversarial Examples, Bias and Trust with Mustapha Cisse TWiML & AI podcast Question of the week “Is there a gcp service that’s cloud identity-aware proxy except for a static site that you host via cloud storage?” Answer between Mark & KF Cloud Identity-Aware Proxy site & docs Cloud Storage site & docs Hosting a Static Website on Cloud Storage site Google App Engine site & docs weasel repo Where can you find us next? Melanie will be at Fat* in New York in Feb. Mark will be at the Game Developer’s Conference | GDC in March.
Feb. 7, 2018
Yifei Feng talks with Mark and Melanie about working on the open source TensorFlow platform, the recent 1.5 release, and how her team engages and supports the growing community. She provides a great overview of what its like to work on an open source project and ways to get involved especially for anyone new to contributing. Yifei Feng Yifei is a software engineer on TensorFlow team. Her main focus is building tools and infractures to help TensorFlow engineers do their best work. She works on release and the open source process of TensorFlow. She also worked on TensorFlow’s high level API and TensorFlow Serving. Cool things of the week TensorFlow 1.5 Release blog Use Forseti to make sure your Google Kubernetes Engine clusters are updated for Meltdown and Spectre blog GCP arrives in Canada with launch of Montreal region blog Interview TensorFlow site and github TensorFlow Contributing Guidelines page TensorFlow Summit site Stack Overflow site TensorFlow with Eli Bixby podcast Cloud Machine Learning Engine with Yufeng Guo podcast Learn TensorFlow without a PhD blog AI Adventures YouTube Question of the week How do I design identity and access management policies policies for a GCP? Toward effective cloud governance: designing policies for GCP customers large and small blog Where can you find us next? Melanie will be at Fat* in New York in Feb. Mark will be at the Game Developer’s Conference | GDC in March.
Jan. 31, 2018
We return once again to Continuous Integration tooling, this time with a visual spin. Mike Fotinakis joins Mark and Melanie to discuss how they use Google Cloud Platform to develop Percy, the platform for continuous visual reviews for web apps. Mike Fotinakis Mike is Co-Founder and CEO of Percy, where he is working on problems at the intersection of design, development, and deployment. Mike has previously worked as an engineer at companies including Google, Science Exchange, and AltSchool, and is now enjoying building his first company from the ground up. Sometimes, he even enjoys things that don’t involve computers at all, including rock climbing, coffee, classical singing, and scuba diving. Cool things of the week OpenCensus: A Stats Collection and Distributed Tracing Framework blog medium London Zoo trials facial recognition technology to help track elephants in the wild blog Cloud Dataflow and the Tram Challenge youtube Interview Percy site docs Google Kubernetes Engine site docs Google Cloud Storage site docs Google Cloud SQL site docs Redis Labs Cloud site Google Cloud Platform Pricing Calculator site Ember Conf site Percy.io Question of the week I would love a weekly roundup of news about Google Cloud Platform - where can I get one? This week in GCP medium Where can you find us next? Melanie will be at FOSDEM in Brussels this weekend. Mark will be at the Game Developer’s Conference | GDC in March.
Jan. 24, 2018
The delightful Sam Ramji joins Mark and Melanie this week to talk about Google Cloud Platform, Open Source, Distributed Systems and Philosophy and how they are all interrelated. Sam Ramji A 20+ year veteran of the Silicon Valley and Seattle technology scenes, Sam Ramji is VP Product Management for Google Cloud Platform (GCP). He was the founding CEO of Cloud Foundry Foundation, was Chief Strategy Officer for Apigee (APIC), designed and led Microsoft’s open source strategy, founded the Outercurve Foundation, and drove product strategy for BEA WebLogic Integration. Previously he built distributed systems and client software at firms including Broderbund, Fair Isaac, and Ofoto. He is an advisor to multiple companies including Accenture, Insight Engines, and the Linux Foundation, and served on the World Economic Forum’s Industrial Internet Working Group. He received his B.S. in Cognitive Science from UCSD in 1994. Cool things of the week An example escalation policy — CRE life lessons blog The new Google Arts & Culture, on exhibit now blog Five Days of Kubernetes 1.9 blog Kubernetes Comic site Interview The Case for Learned Index Structures paper CAP Theorem wikipedia Databricks site Spinnaker site Tensor Processing Units site 38 Special - Hold On Loosely youtube Question of the week I would like to run a Google Cloud Function every day/week/hour etc - but there is no cron ability in Cloud Functions (yet?). How can I do this now? Functions Cron github Where can you find us next? Melanie is speaking at AI Congress in London Jan 30th and she will be at FOSDEM in Brussels in Feb. Mark will be at the Game Developer’s Conference | GDC in March.
Jan. 17, 2018
Amy Unruh and Sara Robinson join the podcast this week to talk with Mark and Melanie about the alpha launch of Cloud AutoML Vision. Cloud AutoML is a suite of products enabling developers with limited ML expertise to build high quality models using transfer learning and Neural Architecture Search techniques. AutoML Vision is the first product out the gate with a focus on making it easy to train customized vision models. About Amy Unruh Amy is a developer relations engineer for the Google Cloud Platform, where she focuses on machine learning and data analytics as well as other Cloud Platform technologies. Amy has an academic background in CS/AI and has also worked at several startups, done industrial R&D, and published a book on App Engine. About Sara Robinson Sara is a developer relations engineer on Google’s Cloud Platform team, focusing on big data and machine learning. She worked on providing initial product feedback and building a demo for the AutoML Vision launch. Cool things of the week Google Brain Looking Back on 2017 blog Shout-out to Kaz Sato for his TensorFlow Rock Paper Scissors example Running dedicated game servers in Kubernetes Engine blog Kaggle Learn site Honorable mention… - Scientists put a worm brain in a lego robot blog Interview Cloud AutoML: Making AI accessible to every business blog Cloud AutoML Vision site Cloud AutoML Vision Access Request | Whitelist Application form Cloud images example video Shout-out thanks to Rob Carver for domain expertise in helping label cloud images. Coastline images example readme and filenames csv Using Machine Learning to Explore Neural Network Architecture blog Learning Transferable Architecture for Scalable Image Recognition arXiv paper Neural Architecture Search with Reinforcement Learning arXiv paper Progressive Neural Architecture Search arXiv paper Learning2learn video Cloud Vision site docs Question of the week How does someone in academia get GCP credits? Google Cloud Platform Education Grants site Where can you find us next? Melanie is speaking at AI Congress in London Jan 30th and she will be at FOSDEM in Brussels in Feb. Mark will be at the Game Developer’s Conference | GDC in March.
Jan. 17, 2018
Bringing you a special second episode this week with Matt Linton and Paul Turner sharing insights with Mark and Melanie about the CPU vulnerabilities, Spectre & Meltdown, and how Google coordinated and managed security with the broader community. We talked about how there has been minimal to no performance impact for GCP users and GCP’s Live Migration helped deploy patches and mitigations without requiring maintenance downtime. Due to the special nature, no cool things or question included on this podcast. About Matt Linton Matt is an Incident Manager (aka Chaos Specialists) for Google, which means his team is on-call to handle suspected security incidents and other major urgent issues. About Paul Turner Paul is a Software Engineer specializing in operating systems, concurrency, and performance. Interview Protecting our Google Cloud customers from new vulnerabilities without impacting performance blog What Google Cloud, G Suite and Chrome customers need to know about the CPU vulnerability blog Google Security Blog, Today’s CPU vulnerability: what you need to know blog ProjectZero News and Updates by Yann Horn blog Spectre Attack paper Meltdown Paper paper Intel Security Center site Intel Analysis of Speculative Side Channels site An Update on AMD Processor Security: site ARM Processor Security Update site GCP Compute Engine Live Migration docs GCP Security Overview site Patch your operating systems and all the things. Keep updated.

Podcasts like "Platforms Windows, Linux, Apple all the Tech Info you can Handle on the Various Platforms"   ·   View all

By AVpodcast
By Larry Bushey and Bill Smith
By Jon Masters
By Linux Luddites
By Graham Morrison
Disclaimer: The podcast and artwork embedded on this page are from Tech Podcast Network, which is the property of its owner and not affiliated with or endorsed by Listen Notes, Inc.