Enterprise Investing with Ed Sim
51 min

Investing in enterprise software has become a competitive business. Lots of venture capital firms compete for the good deals at every stage. This level of competition has driven more capital into the early stages. 

Ed Sim is a partner with Boldstart, an early stage enterprise investment firm. He joins the show to talk about modern enterprise investment strategy and his own varied personal experiences in working at funds.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post Enterprise Investing with Ed Sim appeared first on Software Engineering Daily.

Google Cloud Platform Podcast
Google Cloud Platform Podcast
Google Cloud Platform
2020 Year End Wrap Up
This week, four of the podcast’s greatest hosts come together to celebrate all of the fun and informative episodes we’ve been privileged to do this year! Join Mark Mirchandani, Jon Foust, Priyanka Vergadia, and Brian Dorsey as we talk about our favorite guests and shows, some cool things that happened this year, and what we’re looking forward to in 2021! Cool things of the week * A Giant List of Google Cloud Resources blog * Google Cloud 4 Words site Our favorite episodes * Jon’s Favorites * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast * GCP Podcast Episode 237: NVIDIA with Bryan Catanzaro podcast * Priyanka’s Favorite * GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark podcast * Mark’s Favorites * GCP Podcast Episode 242: NASA and FDL with James Parr and Madhulika Guhathakurta podcast * GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast * GCP Podcast Episode 228: Fastly with Tyler McMullen podcast * Brian’s Favorites * GCP Podcast Episode 223: Voice Coding with Emily Shea and Ryan Hileman podcast * GCP Podcast Episode 233: Bare Metal Solution with James Harding and Gurmeet Goindi podcast * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast Sound Effects Attribution * “Bad Beep” by RicherLandTV of Freesound.org * “Small Group Laugh 6” by Tim.Kahn of Freesound.org * “It’s Always Night in Space” by JamesSilvera of HDInteractive.com * “Easy Cheesy” by LoboLoco of FreeMusicArchive.org
36 min
AWS Podcast
AWS Podcast
Amazon Web Services
#411: Enabling Rapid Innovation and Resiliency with AWS
As customers leverage the cloud across industries, new waves of rapid innovation have emerged to adapt to these unprecedented times. In this episode, Simon is joined by Iain Rouse, AWS public sector country director for Australia and New Zealand, and Cindy Schwartz, AWS senior practice manager professional services team. Listen to dive deep into our customer solutions and the different ways organisations can be agile and scale with AWS to become more resilient and sustainable. Also, hear a preview of our latest webinars with Dan Beeston from Juniper Aged Care, Dr. George Margelis from Aged Care Industry Information Technology Council, and Associate Professor Michael Kasumovic from EdTech company Arludo. Links: 1. Innovation for Life: Cities Powered by the Cloud eBook - https://pages.awscloud.com/APAC-acq-DL-intc-inv_innovationforlife_ANZ-2020-reg.html?sc_channel=el&sc_campaign=awspodcast_enablingrapidinnovation_2020&sc_geo=apac&sc_country=mult&sc_outcome=acq&trk=podcast_anz 2. A Guide to Building Organizational Resilience - https://pages.awscloud.com/GLOBAL-public-DL-resiliency-ebook-2020-reg.html?sc_channel=el&sc_campaign=awspodcast_enablingrapidinnovation_2020&sc_geo=apac&sc_country=mult&sc_outcome=acq&trk=podcast_anz 3. Taking Classrooms to the Cloud - https://blog.aboutamazon.com.au/innovation/taking-classrooms-to-the-cloud?sc_channel=el&sc_campaign=awspodcast_enablingrapidinnovation_2020&sc_geo=apac&sc_country=mult&sc_outcome=acq&trk=podcast_anz 4. On-Demand: Digital Innovation in Support of Residential Aged Care: https://pages.awscloud.com/APAC-public-OE-ANZ-health-webinar-2020-reg.html?sc_channel=el&sc_campaign=awspodcast_enablingrapidinnovation_2020&sc_geo=apac&sc_country=mult&sc_outcome=reg&trk=podcast_anz
41 min
Towards Data Science
Towards Data Science
The TDS team
58. David Duvenaud - Using generative models for explainable AI
In the early 1900s, all of our predictions were the direct product of human brains. Scientists, analysts, climatologists, mathematicians, bankers, lawyers and politicians did their best to anticipate future events, and plan accordingly. Take physics, for example, where every task we think of as part of the learning process, from data collection to cleaning to feature selection to modeling, all had to happen inside a physicist’s head. When Einstein introduced gravitational fields, what he was really doing was proposing a new feature to be added to our model of the universe. And the gravitational field equations that he put forward at the same time were an update to that very model. Einstein didn’t come up with his new model (or “theory” as physicists call it) of gravity by running model.fit() in a jupyter notebook. In fact, he never outsourced any of the computations that were needed to develop it to machines. Today, that’s somewhat unusual, and most of the predictions that the world runs on are generated in part by computers. But only in part — until we have fully general artificial intelligence, machine learning will always be a mix of two things: first, the constraints that human developers impose on their models, and second, the calculations that go into optimizing those models, which we outsource to machines. The human touch is still a necessary and ubiquitous component of every machine learning pipeline, but it’s ultimately limiting: the more of the learning pipeline that can be outsourced to machines, the more we can take advantage of computers’ ability to learn faster and from far more data than human beings. But designing algorithms that are flexible enough to do that requires serious outside-of-the-box thinking — exactly the kind of thinking that University of Toronto professor and researcher David Duvenaud specializes in. I asked David to join me for the latest episode of the podcast to talk about his research on more flexible and robust machine learning strategies.
37 min
Kubernetes Podcast from Google
Kubernetes Podcast from Google
Adam Glick and Craig Box
KubeCon NA 2020, with Stephen Augustus
Join us for all the news from KubeCon NA 2020, and a conversation with conference co-chair Stephen Augustus. Stephen is a Senior Open Source Engineer on the VMware Tanzu team, a chair of Kubernetes’ SIG Release, and a leader in many other parts of the project, past and present. Do you have something cool to share? Some questions? Let us know: * web: kubernetespodcast.com * mail: kubernetespodcast@google.com * twitter: @kubernetespod Chatter of the week * The kākāpō wins Bird of the Year * We’re off for 2 weeks. See you on December 8! News of the week * Cisco acquires Banzai Cloud * CNCF announces Cloud Native Survey 2020 results * Red Hat: New edge features, industrial AI/ML blueprint and AWS launch * CNCF End User Tech Radar for storage * New End User benefits * Envoy Mobile joins the CNCF * New sandbox projects * cert-manager * cdk8s * Kyverno * OpenKruise * Pravega * SchemaHero * Tinkerbell * k8ssandra from Datastax * Episode 98 with Sam Ramji * k0s from Mirantis * Solo.io announces Gloo Mesh Enterprise and rebrands products * Episode 55, with Idit Levine * Pinniped * Shipa launches Ketch * Kinvolk launches Headlamp * The SPIFFE book “Solving The Bottom Turtle” * Episode 45, with Andrew Jessup * Anthos Developer Sandbox * GKE ingress features * Ambassador Labs takes in $18m and launches v1.9 * Tanzu SQL: Postgres on Kubernetes * Lightning round: * Accurics extends Terrascan * AWS adds containers to Lightsail * Arrikto takes $10m in funding * Brobridge releases Gravity * CircleCI runner is GA * Cloud66 for agencies and multiple database support * Cloudflare Origin CA cert-manager plugin * Cloudical Vanillastack * Cloudify version 5.1 * Codefresh launches GitOps 2.0 features * Commvault backup-as-a-service * Diamanti Spektra 3.1 and customer portal * Dynatrace PurePath 4 * Elastisys Compliant Kubernetes * The Fairwinds Kubernetes Maturity Model * Garden takes “seed” funding * Gremlin adds soundproofing * Humio Operator * Instana adds observability tools on Kubernetes * Intuit runs TurboTax on Kubernetes * Kioxia announces a new storage offering * Kubecost adds features for monitoring outside a cluster * KubeMQ adds automatic network creation * Kubermatic updates KubeOne to v1.1 * Kubernative SINA * Kublr 1.19 * Lablup announced Backend.ai 20.09 RC * Magalix launches KubeAdvisor 2.0 * Mayadata launches Kubera Propel and Kubera Chaos * Mirantis adds extensions to Lens * Puppet Labs adds Relay to Puppet Enterprise * Reblaze announces Curiefense to add WAF to Envoy * Replicates wants to help you Troubleshoot * Styra adds new editions to DAS * Sysdig introduces Kubernetes-native network security (ZTNSK) and partners with IBM Cloud * TrilioVault for Kubernetes v2.0 * Zerto for Kubernetes * Google Open Source Live Kubernetes Links from the interview * KubeCon NA 2020 * Episode 117, with Constance Caramanolis * CNCF Twitch * SIG Friday: ping Stephen for the current link * Slack * CNCF Slack * Kubernetes Slack * Hallway Track * Kubernetes Podcast chat * CoreOS * CoreOS Tectonic * CoreOS acquired by Red Hat * Tectonic on Azure * SIG Azure * SIG Release * SIG PM (retired) * Kubernetes Enhancement Process * Receipts process KEP * Sidecar containers - KEP closed! * Production readiness review * Episode 10, with Josh Berkus and Tim Pepper * Release managers * Black Lives Matter announcement banner * Better announcements * Kubernetes Naming working group * Inclusive Naming project * Dan Kohn memorial * Stephen Augustus on Twitter and on the web
53 min
The Cloudcast
The Cloudcast
Cloudcast Media
Great Data Models Need Great Features
Mike Del Balso (@mikedelbalso, CEO at @TectonAI) talks about lessons learned from Uber’s Michelangelo ML platform, enabling DevOps for ML data, and how Tecton enables features for data models.   *SHOW: *477 *SHOW SPONSOR LINKS:* * Learn more about Fauna: https://www.fauna.com/serverless * Try FaunaDB for Free: https://dashboard.fauna.com/accounts/register * CloudAcademy -Build hands-on technical skills. Get measurable results.  * Get 50% of the monthly price of CloudAcademy by using code CLOUDCAST * 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 *PodCTL Podcast is Back (Enterprise Kubernetes) *- http://podctl.com *SHOW NOTES:* * *Tecton homepage* * *Tecton emerges from stealth with veterans from Uber* * *Michelangelo: Uber’s Machine Learning Platform* * *Tecton: The Data Platform for Machine Learning** (blog)* * *“**Why We Need DevOps for Machine Learning Data**” (blog)* *Topic 1 - *Welcome to the show. It’s always exciting to talk to new companies. You were doing some pretty interesting things at Uber prior to starting Tecton, so tell us a little bit about that experience and then what motivated you to start Tecton?  *Topic 2 - *There are lots of Data/AI/ML tools and platforms out there. Tecton talks about “great models need great features”. Give us a high-level overview of the Tecton platform and the perspective you bring to solving complex business problems. *Topic 3 - *After reading the papers on the Uber Michelangelo platform, it’s clear that today’s interactions aren’t a bunch of individual “decisions”, but layers of decisions made on ever-changing data (the UberEATS example). Why does business need a new approach to how they interact with data?* * *Topic 4 -* When I think about earlier approaches for companies to “harness data for analytics”, there was always the problem of data silos. Do you find that companies need to organize themselves different, not just organize their data, to be able to overcome those silo challenges? Does it take a much more product-centric approach vs. the traditional “analyst” approach? *Topic 5 - *Every new company and platform needs to find product-market fit. What do you see as early “fits” for the Tecton platform?  *Topic 6 - *How much data-science expertise does a company need today to be able to leverage Tecton, and how much does the platform lower the barrier to entry?  *FEEDBACK?* * Email: show at thecloudcast dot net * Twitter: @thecloudcastnet
35 min
More episodes
Search
Clear search
Close search
Google apps
Main menu