Podcasts about Conda

The Rust Paradox: Systems Programming in the Epoch of Generative AII. Paradoxical Thesis ExaminationContradictory Technological NarrativesEpistemological inconsistency: programming simultaneously characterized as "automatable" yet Rust deemed "excessively complex for acquisition"Logical impossibility of concurrent validity of both propositions establishes fundamental contradictionNecessitates resolution through bifurcation theory of programming paradigmsRust Language Adoption Metrics (2024-2025)Subreddit community expansion: +60,000 users (2024)Enterprise implementation across technological oligopoly: Microsoft, AWS, Google, Cloudflare, CanonicalLinux kernel integration represents significant architectural paradigm shift from C-exclusive development modelII. Performance-Safety Dialectic in Contemporary EngineeringEmpirical Performance CoefficientsRuff Python linter: 10-100× performance amplification relative to predecessorsUV package management system demonstrating exponential efficiency gains over Conda/venv architecturesPolars exhibiting substantial computational advantage versus pandas in data analytical workflowsMemory Management ArchitectureOwnership-based model facilitates deterministic resource deallocation without garbage collection overheadPerformance characteristics approximate C/C++ while eliminating entire categories of memory vulnerabilitiesCompile-time verification supplants runtime detection mechanisms for concurrency hazardsIII. Programmatic Bifurcation HypothesisDichotomous Evolution TrajectoryApplication layer development: increasing AI augmentation, particularly for boilerplate/templated implementationsSystems layer engineering: persistent human expertise requirements due to precision/safety constraintsPattern-matching limitations of generative systems insufficient for systems-level optimization requirementsCognitive Investment CalculusInitial acquisition barrier offset by significant debugging time reductionCorporate training investment persisting despite generative AI proliferationMarket valuation of Rust expertise increasing proportionally with automation of lower-complexity domainsIV. Neuromorphic Architecture Constraints in Code GenerationLLM Fundamental LimitationsPattern-recognition capabilities distinct from genuine intelligenceAnalogous to mistaking k-means clustering for financial advisory servicesHallucination phenomena incompatible with systems-level precision requirementsHuman-Machine Complementarity FrameworkAI functioning as expert-oriented tool rather than autonomous replacementComparable to CAD systems requiring expert oversight despite automation capabilitiesHuman verification remains essential for safety-critical implementationsV. Future Convergence VectorsSynergistic Integration PathwaysAI assistance potentially reducing Rust learning curve steepnessRust's compile-time guarantees providing essential guardrails for AI-generated implementationsOptimal professional development trajectory incorporating both systems expertise and AI utilization proficiencyEconomic ImplicationsValue migration from general-purpose to systems development domainsIncreasing premium on capabilities resistant to pattern-based automationNatural evolutionary trajectory rather than paradoxical contradiction

Fri, 14 Feb 2025 04:45:00 +0000 https://jungeanleger.podigee.io/2005-borsepeople-im-podcast-s17-12-michael-regner ce5d10a546b5941cb4f068c5f0126d21 Michael Regner ist leidenschaftlicher Unternehmer in der Hotelindustrie, aktuell mit einem Crowdinvesting unterwegs. Wir reden über eine spannende Karriere bei grossen internationalen Namen, dies mit einem zufälligen Beginn. Michael konzentrierte sich meist auf den Finanzbereich, die strategische Planung und das operative Controlling, Private Equity Funds (Tauros, Limestone Capital) waren und sind auch aktuell immer Thema. Aktuell ist zudem ein Crowdinvesting für die Loisium Holding bei Conda am Start. Es geht um die Expansion der Weinhotel-Gruppe in weitere europäische Weinregionen. Dieses Anleihe-Angebot mit 7,5 Prozent Geldzins oder 10 Prozent Sachleistungs-Zins sowie weiteren Goodies je nach Investitionssumme gehen wir in der zweiten Hälfte der Folge konkret durch, denn ich habe als Stammgast viele Fragen. Finally sind auch Profifahrräder, Superfly und die Tatsache, dass die Branche Rekordnächtigungszahlen derzeit nicht in die EBITDAs übertragen kann (Kosten, Teuerung, Gäste geben weniger für Zusatzleistungen aus) Themen. - https://www.loisium.com - https://conda-capital.com/campaign/loisium/ - Börsepeople Daniel Horak (Conda): https://audio-cd.at/page/podcast/5874 - Börsepeople Thomas Bobek (Loisium Investor Tauros): https://audio-cd.at/page/podcast/3795 About: Die Serie Börsepeople des Podcasters Christian Drastil, der im Q4/24 in Frankfurt als "Finfluencer & Finanznetworker #1 Austria" ausgezeichnet wurde, findet im Rahmen von http://www.audio-cd.at und dem Podcast "Audio-CD.at Indie Podcasts" statt. Es handelt sich dabei um typische Personality- und Werdegang-Gespräche. Die Season 17 umfasst unter dem Motto „25 Börsepeople“ 25 Talks. Presenter der Season 17 ist die EXAA (Energy Exchange Austria) https://www.exaa.at. Welcher der meistgehörte Börsepeople Podcast ist, sieht man unter http://www.audio-cd.at/people. Der Zwischenstand des laufenden Rankings ist tagesaktuell um 12 Uhr aktualisiert. Bewertungen bei Apple (oder auch Spotify) machen mir Freude: http://www.audio-cd.at/spotify , http://www.audio-cd.at/apple . 2005 full no Christian Drastil Comm.

QuantStack is an open-source technology software company specializing in tools for data science, scientific computing, and visualization. They are known for maintaining vital projects such as Jupyter, the conda-forge package channel, and the Mamba package manager. Sylvain Corlay is the CEO of QuantStack. He joins the podcast to talk about his company, Conda, Mamba, the The post Mamba and Software Package Security with Sylvain Corlay appeared first on Software Engineering Daily.

QuantStack is an open-source technology software company specializing in tools for data science, scientific computing, and visualization. They are known for maintaining vital projects such as Jupyter, the conda-forge package channel, and the Mamba package manager. Sylvain Corlay is the CEO of QuantStack. He joins the podcast to talk about his company, Conda, Mamba, the The post Mamba and Software Package Security with Sylvain Corlay appeared first on Software Engineering Daily.

In this episode of the Nextflow Podcast, we dive into highlights from the recent Nextflow Summit held in Barcelona in 2024. The summit featured an incredible range of talks, demonstrations, and discussions showcasing the latest advancements in workflows, data analysis, and community collaboration. With so much exciting content to explore, we've picked out some of our favourite moments to share with you. From impactful new features to inspiring keynote addresses and humorous presentations, this episode offers a curated selection of clips that capture the energy and innovation from the event. Join us as we relive the summit's best bits and discuss their significance for the Nextflow community. 00:00 Start 00:10 Podcast introduction 00:47 Introductions: Group 1 01:56 Clip 1: Wave mirroring 04:32 Clip 2: Throwing cat food 06:00 Clip 3: crisprseq 08:03 Clip 4: nf-test 10:34 Clip 5: Workflow output definition 12:39 Clip 6: Open Science Software Foundation launch 15:08 Clip 7: FAIR code with nf-core 16:58 Clip 8: Teaching with Nextflow 18:56 Clip 9: Conda lock files 21:24 Clip 10: MultiQC in scripts 22:43 Clip 11: Small Nextflow Big Nextflow 25:17 Introduction: Team 2 26:11 Clip 12: Genomics England 29:47 Clip 13: Alphafold interactive reports 33:26 Clip 14: Data Studios 35:32 Clip 15: Covid and Ebola 37:35 Clip 16: Seqera AI 41:34 Clip 17: Nextflow VSCode DAGs 44:33 Clip 18: Fusion snapshots 48:38 Clip 19: Sustainable computing 52:38 Clip 20: nf-core/tools 56:37 Clip 21: Industry best practices with nf-core 58:58 Clip 22: Federated data queries 01:01:56 Clip 23: Nextflow Ambassadors 01:05:04 Conclusion

Two time runner up of RuPaul's Drag Race and international drag superstar Hannah Conda joins us in the bathroom this week. Hannah breaks it down and spills the tea on everything from RuPaul's Drag Race, her long time relationship with her partner and her relationship with her father. Hannah was vulnerable, honest and emotional and we couldn't love her more for it. LINKS: Follow Cam @camerondaddo on Instagram Follow Ali @alidaddo on Instagram Follow @hannahcondaofficial on Instagram Follow @hannahcondaofficial on TikTok Got a question for Cam & Ali? You can email them at separatebathrooms@novapodcasts.com.au. See omnystudio.com/listener for privacy information.

In this episode, we reconnect with the Pixi team after our last conversation in November 2023 to dive back into the world of Python packaging, with a special focus on the latest advancements in Pixi. Joining us are Tim and Ruben, both of whom bring their unique expertise in robotics and game development. Ruben shares his experience contributing to conda-forge, pixi and Python package management in general.We explore recent enhancements to Pixi, including its integration with VS Code, the evolution of pyproject.toml support, and the addition of PyPI dependency resolution along with Conda.We also discuss the current state of Pixi for enterprises, touching on its readiness for production and enterprise-specific features like package registries.The conversation also delves into how pixi resolves issues reported by the community, such as platform-specific Pixi.lock file regeneration - and how developers can contribute to the open source ecosystem. Finally, we look ahead to the future, discussing the team's vision for Python packaging over the next one to five years.Tune in for a deep dive into the present and future of Python packaging, packed with personal stories and expert insights.--Links:- Prefix-dev- Add pixi as an workflow/package manager PR- Our PDM coaching program

In this episode, JMo interviews Hannah Conda, who shares her personal journey with mental health struggles like depression and anxiety. She discusses facing criticism as a drag performer and finding validation through her art. Hannah also explores how she learned to accept himself and find joy in small moments, even during difficult periods.  Resources Check out ⁠⁠⁠⁠⁠⁠Gotcha4Life⁠⁠⁠⁠⁠ Call Lifeline anytime on 13 11 14 Send a text to Lifeline at 0477 131 114 ⁠⁠⁠⁠⁠Chat live with Lifeline⁠⁠⁠⁠⁠ Proudly produced in the ⁠⁠⁠⁠⁠Pro Podcast Studios⁠⁠⁠⁠⁠ Sponsors This series was made possible with the support of ⁠⁠⁠⁠⁠Chemist Warehouse⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠Gotcha4life⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠BYD⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠Wanderlust⁠

In this episode, I speak with Wolf Vollprecht  Co-founder of Prefix.dev and to key player in the condo forge ecosystem. We discuss the critical role of open source infrastructure, like PyPi aAnd the monthly cost associated with it emphasizing the importance of sustained investment for infrastructure. Wolf shares his journey from studying mechanical engineering and falling in love with open source to contributing, to Conda forge and creating Mamba and pixi, a fast package manager. We dive into the capabilities of pixie a Rust  based package management tool designed to be faster and more efficient than Conda. Pixie integrates well with both conda forge and PyPi environments and addresses the dependency and reproducibility issues, and supports cross-platform package management.  Wolf also talks about the open-core business model supported by VC funding and grants, aiming to build a sustainable and enhanced packaging management ecosystem. Support the Show.Subscribe to mailing list here.

Fri, 14 Jun 2024 03:45:00 +0000 https://jungeanleger.podigee.io/1552-borsepeople-im-podcast-s13-08-daniel-horak 968e8c792a3253ef0542b4a952903f09 Daniel Horak ist Co-Gründer und CEO von Conda. Wir sprechen über eine frühe KI-Idee, über eine Zeit bei Kapsch Business.com, über die Conda-Gründung mit Paul Pöltner, über die Phase zunächst mit Rapid und Austria und dann mit startup300, über 61.000 registrierte UserInnen, 76 Mio. eingeworbenes Crowd Capital und 235 Cases. Wir reden aber auch über das Scheitern, den Fit & Proper Test der FMA, Radfahren, die neue Conda Capital Market und noch einmal ganz aktuell und ausführlich über Rapid Wien. https://www.conda.at About: Die Serie Börsepeople findet im Rahmen von http://www.audio-cd.at und dem Podcast "Audio-CD.at Indie Podcasts" statt. Es handelt sich dabei um typische Personality- und Werdegang-Gespräche. Die Season 13 umfasst unter dem Motto „24 Börsepeople“ 24 Talks. Presenter der Season 13 ist Vierfeld, https://www.vierfeld.com .Welcher der meistgehörte Börsepeople Podcast ist, sieht man unter http://www.audio-cd.at/people. Der Zwischenstand des laufenden Rankings ist tagesaktuell um 12 Uhr aktualisiert. Bewertungen bei Apple (oder auch Spotify) machen mir Freude: https://podcasts.apple.com/at/podcast/audio-cd-at-indie-podcasts-wiener-boerse-sport-musik-und-mehr/id1484919130 . 1552 full no Christian Drastil Comm.

Oracle has been actively focusing on bringing AI to the enterprise at every layer of its tech stack, be it SaaS apps, AI services, infrastructure, or data.   In this episode, hosts Lois Houston and Nikita Abraham, along with senior instructors Hemant Gahankari and Himanshu Raj, discuss OCI AI and Machine Learning services. They also go over some key OCI Data Science concepts and responsible AI principles.   Oracle MyLearn: https://mylearn.oracle.com/ou/learning-path/become-an-oci-ai-foundations-associate-2023/127177   Oracle University Learning Community: https://education.oracle.com/ou-community   LinkedIn: https://www.linkedin.com/showcase/oracle-university/   X (formerly Twitter): https://twitter.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Himanshu Raj, and the OU Studio Team for helping us create this episode.   --------------------------------------------------------   Episode Transcript:   00:00 The world of artificial intelligence is vast and everchanging. And with all the buzz around it lately, we figured it was the perfect time to revisit our AI Made Easy series. Join us over the next few weeks as we chat about all things AI, helping you to discover its endless possibilities. Ready to dive in? Let's go! 00:33 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:46 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Principal Technical Editor. Nikita: Hey everyone! In our last episode, we dove into Generative AI and Language Learning Models.  Lois: Yeah, that was an interesting one. But today, we're going to discuss the AI and machine learning services offered by Oracle Cloud Infrastructure, and we'll look at the OCI AI infrastructure. Nikita: I'm also going to try and squeeze in a couple of questions on a topic I'm really keen about, which is responsible AI. To take us through all of this, we have two of our colleagues, Hemant Gahankari and Himanshu Raj. Hemant is a Senior Principal OCI Instructor and Himanshu is a Senior Instructor on AI/ML. So, let's get started! 01:36 Lois: Hi Hemant! We're so excited to have you here! We know that Oracle has really been focusing on bringing AI to the enterprise at every layer of our stack.  Hemant: It all begins with data and infrastructure layers. OCI AI services consume data, and AI services, in turn, are consumed by applications.  This approach involves extensive investment from infrastructure to SaaS applications. Generative AI and massive scale models are the more recent steps. Oracle AI is the portfolio of cloud services for helping organizations use the data they may have for the business-specific uses.  Business applications consume AI and ML services. The foundation of AI services and ML services is data. AI services contain pre-built models for specific uses. Some of the AI services are pre-trained, and some can be additionally trained by the customer with their own data.  AI services can be consumed by calling the API for the service, passing in the data to be processed, and the service returns a result. There is no infrastructure to be managed for using AI services.  02:58 Nikita: How do I access OCI AI services? Hemant: OCI AI services provide multiple methods for access. The most common method is the OCI Console. The OCI Console provides an easy to use, browser-based interface that enables access to notebook sessions and all the features of all the data science, as well as AI services.  The REST API provides access to service functionality but requires programming expertise. And API reference is provided in the product documentation. OCI also provides programming language SDKs for Java, Python, TypeScript, JavaScript, .Net, Go, and Ruby. The command line interface provides both quick access and full functionality without the need for scripting.  03:52 Lois: Hemant, what are the types of OCI AI services that are available?  Hemant: OCI AI services is a collection of services with pre-built machine learning models that make it easier for developers to build a variety of business applications. The models can also be custom trained for more accurate business results. The different services provided are digital assistant, language, vision, speech, document understanding, anomaly detection.  04:24 Lois: I know we're going to talk about them in more detail in the next episode, but can you introduce us to OCI Language, Vision, and Speech? Hemant: OCI Language allows you to perform sophisticated text analysis at scale. Using the pre-trained and custom models, you can process unstructured text to extract insights without data science expertise. Pre-trained models include language detection, sentiment analysis, key phrase extraction, text classification, named entity recognition, and personal identifiable information detection.  Custom models can be trained for named entity recognition and text classification with domain-specific data sets. In text translation, natural machine translation is used to translate text across numerous languages.  Using OCI Vision, you can upload images to detect and classify objects in them. Pre-trained models and custom models are supported. In image analysis, pre-trained models perform object detection, image classification, and optical character recognition. In image analysis, custom models can perform custom object detection by detecting the location of custom objects in an image and providing a bounding box.  The OCI Speech service is used to convert media files to readable texts that's stored in JSON and SRT format. Speech enables you to easily convert media files containing human speech into highly exact text transcriptions.  06:12 Nikita: That's great. And what about document understanding and anomaly detection? Hemant: Using OCI document understanding, you can upload documents to detect and classify text and objects in them. You can process individual files or batches of documents. In OCR, document understanding can detect and recognize text in a document. In text extraction, document understanding provides the word level and line level text, and the bounding box, coordinates of where the text is found.  In key value extraction, document understanding extracts a predefined list of key value pairs of information from receipts, invoices, passports, and driver IDs. In table extraction, document understanding extracts content in tabular format, maintaining the row and column relationship of cells. In document classification, the document understanding classifies documents into different types.  The OCI Anomaly Detection service is a service that analyzes large volume of multivariate or univariate time series data. The Anomaly Detection service increases the reliability of businesses by monitoring their critical assets and detecting anomalies early with high precision. Anomaly Detection is the identification of rare items, events, or observations in data that differ significantly from the expectation.  07:55 Nikita: Where is Anomaly Detection most useful? Hemant: The Anomaly Detection service is designed to help with analyzing large amounts of data and identifying the anomalies at the earliest possible time with maximum accuracy. Different sectors, such as utility, oil and gas, transportation, manufacturing, telecommunications, banking, and insurance use Anomaly Detection service for their day-to-day activities.  08:23 Lois: Ok…and the first OCI AI service you mentioned was digital assistant… Hemant: Oracle Digital Assistant is a platform that allows you to create and deploy digital assistants, which are AI driven interfaces that help users accomplish a variety of tasks with natural language conversations. When a user engages with the Digital Assistant, the Digital Assistant evaluates the user input and routes the conversation to and from the appropriate skills.  Digital Assistant greets the user upon access. Upon user requests, list what it can do and provide entry points into the given skills. It routes explicit user requests to the appropriate skills. And it also handles interruptions to flows and disambiguation. It also handles requests to exit the bot.  09:21 Nikita: Excellent! Let's bring Himanshu in to tell us about machine learning services. Hi Himanshu! Let's talk about OCI Data Science. Can you tell us a bit about it? Himanshu: OCI Data Science is the cloud service focused on serving the data scientist throughout the full machine learning life cycle with support for Python and open source.  The service has many features, such as model catalog, projects, JupyterLab notebook, model deployment, model training, management, model explanation, open source libraries, and AutoML.  09:56 Lois: Himanshu, what are the core principles of OCI Data Science?  Himanshu: There are three core principles of OCI Data Science. The first one, accelerated. The first principle is about accelerating the work of the individual data scientist. OCI Data Science provides data scientists with open source libraries along with easy access to a range of compute power without having to manage any infrastructure. It also includes Oracle's own library to help streamline many aspects of their work.  The second principle is collaborative. It goes beyond an individual data scientist's productivity to enable data science teams to work together. This is done through the sharing of assets, reducing duplicative work, and putting reproducibility and auditability of models for collaboration and risk management.  Third is enterprise grade. That means it's integrated with all the OCI Security and access protocols. The underlying infrastructure is fully managed. The customer does not have to think about provisioning compute and storage. And the service handles all the maintenance, patching, and upgrades so user can focus on solving business problems with data science.  11:11 Nikita: Let's drill down into the specifics of OCI Data Science. So far, we know it's cloud service to rapidly build, train, deploy, and manage machine learning models. But who can use it? Where is it? And how is it used? Himanshu: It serves data scientists and data science teams throughout the full machine learning life cycle.  Users work in a familiar JupyterLab notebook interface, where they write Python code. And how it is used? So users preserve their models in the model catalog and deploy their models to a managed infrastructure.  11:46 Lois: Walk us through some of the key terminology that's used. Himanshu: Some of the important product terminology of OCI Data Science are projects. The projects are containers that enable data science teams to organize their work. They represent collaborative work spaces for organizing and documenting data science assets, such as notebook sessions and models.  Note that tenancy can have as many projects as needed without limits. Now, this notebook session is where the data scientists work. Notebook sessions provide a JupyterLab environment with pre-installed open source libraries and the ability to add others. Notebook sessions are interactive coding environment for building and training models.  Notebook sessions run in a managed infrastructure and the user can select CPU or GPU, the compute shape, and amount of storage without having to do any manual provisioning. The other important feature is Conda environment. It's an open source environment and package management system and was created for Python programs.  12:53 Nikita: What is a Conda environment used for? Himanshu: It is used in the service to quickly install, run, and update packages and their dependencies. Conda easily creates, saves, loads, and switches between environments in your notebooks sessions. 13:07 Nikita: Earlier, you spoke about the support for Python in OCI Data Science. Is there a dedicated library? Himanshu: Oracle's Accelerated Data Science ADS SDK is a Python library that is included as part of OCI Data Science.  ADS has many functions and objects that automate or simplify the steps in the data science workflow, including connecting to data, exploring, and visualizing data. Training a model with AutoML, evaluating models, and explaining models. In addition, ADS provides a simple interface to access the data science service mode model catalog and other OCI services, including object storage.  13:45 Lois: I also hear a lot about models. What are models? Himanshu: Models define a mathematical representation of your data and business process. You create models in notebooks, sessions, inside projects.  13:57 Lois: What are some other important terminologies related to models? Himanshu: The next terminology is model catalog. The model catalog is a place to store, track, share, and manage models.  The model catalog is a centralized and managed repository of model artifacts. A stored model includes metadata about the provenance of the model, including Git-related information and the script. Our notebook used to push the model to the catalog. Models stored in the model catalog can be shared across members of a team, and they can be loaded back into a notebook session.  The next one is model deployments. Model deployments allow you to deploy models stored in the model catalog as HTTP endpoints on managed infrastructure.  14:45 Lois: So, how do you operationalize these models? Himanshu: Deploying machine learning models as web applications, HTTP API endpoints, serving predictions in real time is the most common way to operationalize models. HTTP endpoints or the API endpoints are flexible and can serve requests for the model predictions. Data science jobs enable you to define and run a repeatable machine learning tasks on fully managed infrastructure.  Nikita: Thanks for that, Himanshu.  15:18 Did you know that Oracle University offers free courses on Oracle Cloud Infrastructure? You'll find training on everything from cloud computing, database, and security, artificial intelligence, and machine learning, all free to subscribers. So, what are you waiting for? Pick a topic, leverage the Oracle University Learning Community to ask questions, and then sit for your certification. Visit mylearn.oracle.com to get started.  15:46 Nikita: Welcome back! The Oracle AI Stack consists of AI services and machine learning services, and these services are built using AI infrastructure. So, let's move on to that. Hemant, what are the components of OCI AI Infrastructure? Hemant: OCI AI Infrastructure is mainly composed of GPU-based instances. Instances can be virtual machines or bare metal machines. High performance cluster networking that allows instances to communicate to each other. Super clusters are a massive network of GPU instances with multiple petabytes per second of bandwidth. And a variety of fully managed storage options from a single byte to exabytes without upfront provisioning are also available.  16:35 Lois: Can we explore each of these components a little more? First, tell us, why do we need GPUs? Hemant: ML and AI needs lots of repetitive computations to be made on huge amounts of data. Parallel computing on GPUs is designed for many processes at the same time. A GPU is a piece of hardware that is incredibly good in performing computations.  GPU has thousands of lightweight cores, all working on their share of data in parallel. This gives them the ability to crunch through extremely large data set at tremendous speed.  17:14 Nikita: And what are the GPU instances offered by OCI? Hemant: GPU instances are ideally suited for model training and inference. Bare metal and virtual machine compute instances powered by NVIDIA GPUs H100, A100, A10, and V100 are made available by OCI.  17:35 Nikita: So how do we choose what to train from these different GPU options?  Hemant: For large scale AI training, data analytics, and high performance computing, bare metal instances BM 8 X NVIDIA H100 and BM 8 X NVIDIA A100 can be used.  These provide up to nine times faster AI training and 30 times higher acceleration for AI inferencing. The other bare metal and virtual machines are used for small AI training, inference, streaming, gaming, and virtual desktop infrastructure.  18:14 Lois: And why would someone choose the OCI AI stack over its counterparts? Hemant: Oracle offers all the features and is the most cost effective option when compared to its counterparts.  For example, BM GPU 4.8 version 2 instance costs just $4 per hour and is used by many customers.  Superclusters are a massive network with multiple petabytes per second of bandwidth. It can scale up to 4,096 OCI bare metal instances with 32,768 GPUs.  We also have a choice of bare metal A100 or H100 GPU instances, and we can select a variety of storage options, like object store, or block store, or even file system. For networking speeds, we can reach 1,600 GB per second with A100 GPUs and 3,200 GB per second with H100 GPUs.  With OCI storage, we can select local SSD up to four NVMe drives, block storage up to 32 terabytes per volume, object storage up to 10 terabytes per object, file systems up to eight exabyte per file system. OCI File system employs five replicated storage located in different fault domains to provide redundancy for resilient data protection.  HPC file systems, such as BeeGFS and many others are also offered. OCI HPC file systems are available on Oracle Cloud Marketplace and make it easy to deploy a variety of high performance file servers.  20:11 Lois: I think a discussion on AI would be incomplete if we don't talk about responsible AI. We're using AI more and more every day, but can we actually trust it? Hemant: For us to trust AI, it must be driven by ethics that guide us as well. Nikita: And do we have some principles that guide the use of AI? Hemant: AI should be lawful, complying with all applicable laws and regulations. AI should be ethical, that is it should ensure adherence to ethical principles and values that we uphold as humans. And AI should be robust, both from a technical and social perspective. Because even with the good intentions, AI systems can cause unintentional harm. AI systems do not operate in a lawless world. A number of legally binding rules at national and international level apply or are relevant to the development, deployment, and use of AI systems today. The law not only prohibits certain actions but also enables others, like protecting rights of minorities or protecting environment. Besides horizontally applicable rules, various domain-specific rules exist that apply to particular AI applications. For instance, the medical device regulation in the health care sector.  In AI context, equality entails that the systems' operations cannot generate unfairly biased outputs. And while we adopt AI, citizens right should also be protected.  21:50 Lois: Ok, but how do we derive AI ethics from these? Hemant: There are three main principles.  AI should be used to help humans and allow for oversight. It should never cause physical or social harm. Decisions taken by AI should be transparent and fair, and also should be explainable. AI that follows the AI ethical principles is responsible AI.  So if we map the AI ethical principles to responsible AI requirements, these will be like, AI systems should follow human-centric design principles and leave meaningful opportunity for human choice. This means securing human oversight. AI systems and environments in which they operate must be safe and secure, they must be technically robust, and should not be open to malicious use.  The development, and deployment, and use of AI systems must be fair, ensuring equal and just distribution of both benefits and costs. AI should be free from unfair bias and discrimination. Decisions taken by AI to the extent possible should be explainable to those directly and indirectly affected.  23:21 Nikita: This is all great, but what does a typical responsible AI implementation process look like?  Hemant: First, a governance needs to be put in place. Second, develop a set of policies and procedures to be followed. And once implemented, ensure compliance by regular monitoring and evaluation.  Lois: And this is all managed by developers? Hemant: Typical roles that are involved in the implementation cycles are developers, deployers, and end users of the AI.  23:56 Nikita: Can we talk about AI specifically in health care? How do we ensure that there is fairness and no bias? Hemant: AI systems are only as good as the data that they are trained on. If that data is predominantly from one gender or racial group, the AI systems might not perform as well on data from other groups.  24:21 Lois: Yeah, and there's also the issue of ensuring transparency, right? Hemant: AI systems often make decisions based on complex algorithms that are difficult for humans to understand. As a result, patients and health care providers can have difficulty trusting the decisions made by the AI. AI systems must be regularly evaluated to ensure that they are performing as intended and not causing harm to patients.  24:49 Nikita: Thank you, Hemant and Himanshu, for this really insightful session. If you're interested in learning more about the topics we discussed today, head on over to mylearn.oracle.com and search for the Oracle Cloud Infrastructure AI Foundations course.  Lois: That's right, Niki. You'll find demos that you watch as well as skill checks that you can attempt to better your understanding. In our next episode, we'll get into the OCI AI Services we discussed today and talk about them in more detail. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 25:25 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Timestamps: 8:49 - Pivoting your marketing 12:17 - The key ingredients for sports recovery 17:43 - Distributing through several channels  23:22 - Importing CONDA to Switzerland  33:25 - Developing crowdfunding momentum  This episode was co-produced with CONDA.ch. If you want to invest in CONDA.ch with preferential conditions, contact them at investor@conda.ch. About Pedro Schmidt & Linus Gabrielsson: Pedro Schmidt is the founder and CEO of KaEx, the world's first sports-recovery drink to significantly reduce the stress hormone. He holds a MSc in Management, Technology and Economics from ETH Zürich, and previously worked for companies like Siemens Management Consulting, Bristol-Myers Squibb and Teva Pharmaceuticals before founding KaEx in 2016.  Linus Gabrielsson is the managing director at CONDA.ch, the leading platform providing Swiss startups access to crowd investment capital as well as community building and campaigning opportunities. He holds a MSc in Technology Management from ETH and previously worked for companies like IBM Business Consulting Services, PwC and HSBC Private Bank before founding CONDA.ch in 2021. KaEx was the result of many years of research for Pedro, whose undergraduate education is in Pharmaceutical Sciences. He originally branded it as a hangover remedy, and that's how it began to be sold in pharmacies and at Coop supermarkets. At some point, Pedro and his team started getting messages from people who swore on the benefits of drinking KaEx post-workout. Pedro ignored these messages at first, since as a resource-constrained founder he couldn't afford to split his focus — but then pro-athletes started contacting him as well, asking if drinking KaEx could be considered doping (which it couldn't). This made Pedro and his team seriously question whether they should pivot their product's branding and focus. They eventually did do so, and nowadays KaEx is known primarily as a sports drink, though it is of course also useful for hangovers or after a particularly stressful day. In 2021, CONDA.ch was already one of the most successful crowdfunding platforms in Austria and Germany. Rather than try to compete with them, Linus and his co-founder Christian Klumpe decided to strike a franchising deal with their DACH counterparts in order to bring CONDA to Switzerland. As a crowdfunding platform, they focus on startups, SMEs and real estate, and allow users to invest as little as CHF 100. CONDA.ch always runs a 2 week pre-round with preferential conditions open only to VIP investors: that way, when the deal goes public, it never starts at 0, which helps it gain momentum. KaEx has crowdfunded on CONDA.ch several times.  

Topics covered in this episode: NumFOCUS concerns leaping pytest debugger llm Extra, Extra, Extra, PyPI has completed its first security audit Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Brian #1: NumFOCUS concerns Suggested by Pamphile Roy Write up of the current challenges faced by NumFOCUS, by Paul Ivanov (one of the OG of Scientific Python: Jupyter, Matplotlib, etc.) Struggling to meet the needs of sponsored and affiliated projects. In February, NumFOCUS announced it is moving in a new direction. NumFOCUS initiated an effort to run an election for open board seats and proposed changing its governance structure. Some projects are considering and actively pursuing alternative venues for fiscal sponsorship. Quite a bit more detail and discussion in the article. NumFOCUS covers a lot of projects NumPy, Matplotlib, pandas, Jupyter, SciPy, Astropy, Bokeh, Dask, Conda, and so many more. Michael #2: leaping pytest debugger llm You can ask Leaping questions like: Why am I not hitting function x? Why was variable y set to this value? What was the value of variable x at this point? What changes can I make to this code to make this test pass? Brian #3: Extra, Extra, Extra, 2024 Developer Summit Also suggested by Pamphile, related to Scientific Python The Second Scientific Python Developer Summit , June 3-5, Seattle, WA Lots of great work came out of the First Summit in 2023 pytest-regex - Use regexs to specify tests to run Came out of the '23 summit I'm not sure if I'm super happy about this or a little afraid that I probably could use this. Still, cool that it's here. Cool short example of using __init__ and __call__ to hand-roll a decorator. ruff got faster Michael #4: PyPI has completed its first security audit Trail of Bits spent a total of 10 engineer-weeks of effort identifying issues, presenting those findings to the PyPI team, and assisting us as we remediated the findings. Scope: The audit was focused on "Warehouse", the open-source codebase that powers pypi.org As a result of the audit, Trail of Bits detailed 29 different advisories discovered across both codebases. When evaluating severity level of each advisory, 14 were categorized as "informational", 6 as "low", 8 as "medium" and zero as "high". Extras Brian: pytest course community to try out Podia Communities. Anyone have a podia community running strong now? If so, let me know through Mastodon: @brianokken@fosstodon.org Want to join the community when it's up and running? Same. Or join our our friends of the show list, and read our newsletter. I'll be sure to drop a note in there when it's ready. Michael: VS Code AMA @ Talk Python [video] Gunicorn CVE Talk submissions are now open for both remote and in-person talks at the 2024 PyConZA? The conference will be held on 3 and 4 October 2024 in Cape Town, South Africa. Details are on za.pycon.org. FlaskCon 2024 will be happening Friday, May 17 inside PyCon US 2024. Call for proposals are now live! Joke: Debugging with your eyes

Australia's Hannah Conda has been doing her country proud in the reality comp Drag Race UK VS the World, not only looking drop dead gorgeous, she's been serving up plenty... LEARN MORE The post Could Hannah Conda take the World Drag Race Crown? appeared first on JOY Breakfast.

Hi Guys, welcome back to TV Reload. Thank you for clicking or downloading on today's episode with Hannah Conda from RuPaul's Drag Race: UK vs The World Season 2. The hugely successful Drag Race UK spin-off returns with the most international cast ever assembled! The famed Drag Race competition is elevated to Olympian level as RuPaul invites Drag Race Glamazons from around the world to the UK arena. The second series began airing on Stan Australia over a month ago and I thought it would be a real treat to check with how Hannah and see how she is going.  Hannah has been celebrated in the drag queen universe after being a runner up on our down under spin off series in 2022 but now is our strongest hope to win against some overseas legends.  I will ask about the reaction from Spanky and Kween Kong when she told them she had been asked to star in the UK Spin off and if they were jealous.  We will unpack what parts of Australian culture she chose to weave into her aesthetic and what 'Australianisms' she taught the internationals.  There is some interesting tidbits bits on what you can prepare before taking on a Rupauls season and we will find out what RuPaul was like in the UK over filming Down Under. Plus we will get some  brilliant insights into my favourites Tia Coffee and Scarlet envy and find out if there is an order in the hyrachy behind the scenes of the franchises. There is so much to unpack with Hannah  and he is really fun to talk to. So sit back and relax as we dive just that little bit deeper into the world of RuPaul's Drag Race Uk VS The World. See omnystudio.com/listener for privacy information.

Oracle has been actively focusing on bringing AI to the enterprise at every layer of its tech stack, be it SaaS apps, AI services, infrastructure, or data. In this episode, hosts Lois Houston and Nikita Abraham, along with senior instructors Hemant Gahankari and Himanshu Raj, discuss OCI AI and Machine Learning services. They also go over some key OCI Data Science concepts and responsible AI principles. Oracle MyLearn: https://mylearn.oracle.com/ou/learning-path/become-an-oci-ai-foundations-associate-2023/127177 Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X (formerly Twitter): https://twitter.com/Oracle_Edu Special thanks to Arijit Ghosh, David Wright, Himanshu Raj, and the OU Studio Team for helping us create this episode. ------------------------------------------------------- Episode Transcript: 00:00 Welcome to the Oracle University Podcast, the first stop on your cloud journey. During this series of informative podcasts, we'll bring you foundational training on the most popular Oracle technologies. Let's get started! 00:26 Lois: Welcome to the Oracle University Podcast! I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Principal Technical Editor. Nikita: Hey everyone! In our last episode, we dove into Generative AI and Language Learning Models.  Lois: Yeah, that was an interesting one. But today, we're going to discuss the AI and machine learning services offered by Oracle Cloud Infrastructure, and we'll look at the OCI AI infrastructure. Nikita: I'm also going to try and squeeze in a couple of questions on a topic I'm really keen about, which is responsible AI. To take us through all of this, we have two of our colleagues, Hemant Gahankari and Himanshu Raj. Hemant is a Senior Principal OCI Instructor and Himanshu is a Senior Instructor on AI/ML. So, let's get started! 01:16 Lois: Hi Hemant! We're so excited to have you here! We know that Oracle has really been focusing on bringing AI to the enterprise at every layer of our stack.  Hemant: It all begins with data and infrastructure layers. OCI AI services consume data, and AI services, in turn, are consumed by applications.  This approach involves extensive investment from infrastructure to SaaS applications. Generative AI and massive scale models are the more recent steps. Oracle AI is the portfolio of cloud services for helping organizations use the data they may have for the business-specific uses.  Business applications consume AI and ML services. The foundation of AI services and ML services is data. AI services contain pre-built models for specific uses. Some of the AI services are pre-trained, and some can be additionally trained by the customer with their own data.  AI services can be consumed by calling the API for the service, passing in the data to be processed, and the service returns a result. There is no infrastructure to be managed for using AI services.  02:37 Nikita: How do I access OCI AI services? Hemant: OCI AI services provide multiple methods for access. The most common method is the OCI Console. The OCI Console provides an easy to use, browser-based interface that enables access to notebook sessions and all the features of all the data science, as well as AI services.  The REST API provides access to service functionality but requires programming expertise. And API reference is provided in the product documentation. OCI also provides programming language SDKs for Java, Python, TypeScript, JavaScript, .Net, Go, and Ruby. The command line interface provides both quick access and full functionality without the need for scripting.  03:31 Lois: Hemant, what are the types of OCI AI services that are available?  Hemant: OCI AI services is a collection of services with pre-built machine learning models that make it easier for developers to build a variety of business applications. The models can also be custom trained for more accurate business results. The different services provided are digital assistant, language, vision, speech, document understanding, anomaly detection.  04:03 Lois: I know we're going to talk about them in more detail in the next episode, but can you introduce us to OCI Language, Vision, and Speech? Hemant: OCI Language allows you to perform sophisticated text analysis at scale. Using the pre-trained and custom models, you can process unstructured text to extract insights without data science expertise. Pre-trained models include language detection, sentiment analysis, key phrase extraction, text classification, named entity recognition, and personal identifiable information detection.  Custom models can be trained for named entity recognition and text classification with domain-specific data sets. In text translation, natural machine translation is used to translate text across numerous languages.  Using OCI Vision, you can upload images to detect and classify objects in them. Pre-trained models and custom models are supported. In image analysis, pre-trained models perform object detection, image classification, and optical character recognition. In image analysis, custom models can perform custom object detection by detecting the location of custom objects in an image and providing a bounding box.  The OCI Speech service is used to convert media files to readable texts that's stored in JSON and SRT format. Speech enables you to easily convert media files containing human speech into highly exact text transcriptions.  05:52 Nikita: That's great. And what about document understanding and anomaly detection? Hemant: Using OCI document understanding, you can upload documents to detect and classify text and objects in them. You can process individual files or batches of documents. In OCR, document understanding can detect and recognize text in a document. In text extraction, document understanding provides the word level and line level text, and the bounding box, coordinates of where the text is found.  In key value extraction, document understanding extracts a predefined list of key value pairs of information from receipts, invoices, passports, and driver IDs. In table extraction, document understanding extracts content in tabular format, maintaining the row and column relationship of cells. In document classification, the document understanding classifies documents into different types.  The OCI Anomaly Detection service is a service that analyzes large volume of multivariate or univariate time series data. The Anomaly Detection service increases the reliability of businesses by monitoring their critical assets and detecting anomalies early with high precision. Anomaly Detection is the identification of rare items, events, or observations in data that differ significantly from the expectation.  07:34 Nikita: Where is Anomaly Detection most useful? Hemant: The Anomaly Detection service is designed to help with analyzing large amounts of data and identifying the anomalies at the earliest possible time with maximum accuracy. Different sectors, such as utility, oil and gas, transportation, manufacturing, telecommunications, banking, and insurance use Anomaly Detection service for their day-to-day activities.  08:02 Lois: Ok.. and the first OCI AI service you mentioned was digital assistant… Hemant: Oracle Digital Assistant is a platform that allows you to create and deploy digital assistants, which are AI driven interfaces that help users accomplish a variety of tasks with natural language conversations. When a user engages with the Digital Assistant, the Digital Assistant evaluates the user input and routes the conversation to and from the appropriate skills.  Digital Assistant greets the user upon access. Upon user requests, list what it can do and provide entry points into the given skills. It routes explicit user requests to the appropriate skills. And it also handles interruptions to flows and disambiguation. It also handles requests to exit the bot.  09:00 Nikita: Excellent! Let's bring Himanshu in to tell us about machine learning services. Hi Himanshu! Let's talk about OCI Data Science. Can you tell us a bit about it? Himanshu: OCI Data Science is the cloud service focused on serving the data scientist throughout the full machine learning life cycle with support for Python and open source.  The service has many features, such as model catalog, projects, JupyterLab notebook, model deployment, model training, management, model explanation, open source libraries, and AutoML.  09:35 Lois: Himanshu, what are the core principles of OCI Data Science?  Himanshu: There are three core principles of OCI Data Science. The first one, accelerated. The first principle is about accelerating the work of the individual data scientist. OCI Data Science provides data scientists with open source libraries along with easy access to a range of compute power without having to manage any infrastructure. It also includes Oracle's own library to help streamline many aspects of their work.  The second principle is collaborative. It goes beyond an individual data scientist's productivity to enable data science teams to work together. This is done through the sharing of assets, reducing duplicative work, and putting reproducibility and auditability of models for collaboration and risk management.  Third is enterprise grade. That means it's integrated with all the OCI Security and access protocols. The underlying infrastructure is fully managed. The customer does not have to think about provisioning compute and storage. And the service handles all the maintenance, patching, and upgrades so user can focus on solving business problems with data science.  10:50 Nikita: Let's drill down into the specifics of OCI Data Science. So far, we know it's cloud service to rapidly build, train, deploy, and manage machine learning models. But who can use it? Where is it? And how is it used? Himanshu: It serves data scientists and data science teams throughout the full machine learning life cycle.  Users work in a familiar JupyterLab notebook interface, where they write Python code. And how it is used? So users preserve their models in the model catalog and deploy their models to a managed infrastructure.  11:25 Lois: Walk us through some of the key terminology that's used. Himanshu: Some of the important product terminology of OCI Data Science are projects. The projects are containers that enable data science teams to organize their work. They represent collaborative work spaces for organizing and documenting data science assets, such as notebook sessions and models.  Note that tenancy can have as many projects as needed without limits. Now, this notebook session is where the data scientists work. Notebook sessions provide a JupyterLab environment with pre-installed open source libraries and the ability to add others. Notebook sessions are interactive coding environment for building and training models.  Notebook sessions run in a managed infrastructure and the user can select CPU or GPU, the compute shape, and amount of storage without having to do any manual provisioning. The other important feature is Conda environment. It's an open source environment and package management system and was created for Python programs.  12:33 Nikita: What is a Conda environment used for? Himanshu: It is used in the service to quickly install, run, and update packages and their dependencies. Conda easily creates, saves, loads, and switches between environments in your notebooks sessions. 12:46 Nikita: Earlier, you spoke about the support for Python in OCI Data Science. Is there a dedicated library? Himanshu: Oracle's Accelerated Data Science ADS SDK is a Python library that is included as part of OCI Data Science.  ADS has many functions and objects that automate or simplify the steps in the data science workflow, including connecting to data, exploring, and visualizing data. Training a model with AutoML, evaluating models, and explaining models. In addition, ADS provides a simple interface to access the data science service mode model catalog and other OCI services, including object storage.  13:24 Lois: I also hear a lot about models. What are models? Himanshu: Models define a mathematical representation of your data and business process. You create models in notebooks, sessions, inside projects.  13:36 Lois: What are some other important terminologies related to models? Himanshu: The next terminology is model catalog. The model catalog is a place to store, track, share, and manage models.  The model catalog is a centralized and managed repository of model artifacts. A stored model includes metadata about the provenance of the model, including Git-related information and the script. Our notebook used to push the model to the catalog. Models stored in the model catalog can be shared across members of a team, and they can be loaded back into a notebook session.  The next one is model deployments. Model deployments allow you to deploy models stored in the model catalog as HTTP endpoints on managed infrastructure.  14:24 Lois: So, how do you operationalize these models? Himanshu: Deploying machine learning models as web applications, HTTP API endpoints, serving predictions in real time is the most common way to operationalize models. HTTP endpoints or the API endpoints are flexible and can serve requests for the model predictions. Data science jobs enable you to define and run a repeatable machine learning tasks on fully managed infrastructure.  Nikita: Thanks for that, Himanshu.  14:57 Did you know that Oracle University offers free courses on Oracle Cloud Infrastructure? You'll find training on everything from cloud computing, database, and security, artificial intelligence, and machine learning, all free to subscribers. So, what are you waiting for? Pick a topic, leverage the Oracle University Learning Community to ask questions, and then sit for your certification. Visit mylearn.oracle.com to get started.  15:25 Nikita: Welcome back! The Oracle AI Stack consists of AI services and machine learning services, and these services are built using AI infrastructure. So, let's move on to that. Hemant, what are the components of OCI AI Infrastructure? Hemant: OCI AI Infrastructure is mainly composed of GPU-based instances. Instances can be virtual machines or bare metal machines. High performance cluster networking that allows instances to communicate to each other. Super clusters are a massive network of GPU instances with multiple petabytes per second of bandwidth. And a variety of fully managed storage options from a single byte to exabytes without upfront provisioning are also available.  16:14 Lois: Can we explore each of these components a little more? First, tell us, why do we need GPUs? Hemant: ML and AI needs lots of repetitive computations to be made on huge amounts of data. Parallel computing on GPUs is designed for many processes at the same time. A GPU is a piece of hardware that is incredibly good in performing computations.  GPU has thousands of lightweight cores, all working on their share of data in parallel. This gives them the ability to crunch through extremely large data set at tremendous speed.  16:54 Nikita: And what are the GPU instances offered by OCI? Hemant: GPU instances are ideally suited for model training and inference. Bare metal and virtual machine compute instances powered by NVIDIA GPUs H100, A100, A10, and V100 are made available by OCI.  17:14 Nikita: So how do we choose what to train from these different GPU options?  Hemant: For large scale AI training, data analytics, and high performance computing, bare metal instances BM 8 X NVIDIA H100 and BM 8 X NVIDIA A100 can be used.  These provide up to nine times faster AI training and 30 times higher acceleration for AI inferencing. The other bare metal and virtual machines are used for small AI training, inference, streaming, gaming, and virtual desktop infrastructure.  17:53 Lois: And why would someone choose the OCI AI stack over its counterparts? Hemant: Oracle offers all the features and is the most cost effective option when compared to its counterparts.  For example, BM GPU 4.8 version 2 instance costs just $4 per hour and is used by many customers.  Superclusters are a massive network with multiple petabytes per second of bandwidth. It can scale up to 4,096 OCI bare metal instances with 32,768 GPUs.  We also have a choice of bare metal A100 or H100 GPU instances, and we can select a variety of storage options, like object store, or block store, or even file system. For networking speeds, we can reach 1,600 GB per second with A100 GPUs and 3,200 GB per second with H100 GPUs.  With OCI storage, we can select local SSD up to four NVMe drives, block storage up to 32 terabytes per volume, object storage up to 10 terabytes per object, file systems up to eight exabyte per file system. OCI File system employs five replicated storage located in different fault domains to provide redundancy for resilient data protection.  HPC file systems, such as BeeGFS and many others are also offered. OCI HPC file systems are available on Oracle Cloud Marketplace and make it easy to deploy a variety of high performance file servers.  19:50 Lois: I think a discussion on AI would be incomplete if we don't talk about responsible AI. We're using AI more and more every day, but can we actually trust it? Hemant: For us to trust AI, it must be driven by ethics that guide us as well. Nikita: And do we have some principles that guide the use of AI? Hemant: AI should be lawful, complying with all applicable laws and regulations. AI should be ethical, that is it should ensure adherence to ethical principles and values that we uphold as humans. And AI should be robust, both from a technical and social perspective. Because even with the good intentions, AI systems can cause unintentional harm. AI systems do not operate in a lawless world. A number of legally binding rules at national and international level apply or are relevant to the development, deployment, and use of AI systems today. The law not only prohibits certain actions but also enables others, like protecting rights of minorities or protecting environment. Besides horizontally applicable rules, various domain-specific rules exist that apply to particular AI applications. For instance, the medical device regulation in the health care sector.  In AI context, equality entails that the systems' operations cannot generate unfairly biased outputs. And while we adopt AI, citizens right should also be protected.  21:30 Lois: Ok, but how do we derive AI ethics from these? Hemant: There are three main principles.  AI should be used to help humans and allow for oversight. It should never cause physical or social harm. Decisions taken by AI should be transparent and fair, and also should be explainable. AI that follows the AI ethical principles is responsible AI.  So if we map the AI ethical principles to responsible AI requirements, these will be like, AI systems should follow human-centric design principles and leave meaningful opportunity for human choice. This means securing human oversight. AI systems and environments in which they operate must be safe and secure, they must be technically robust, and should not be open to malicious use.  The development, and deployment, and use of AI systems must be fair, ensuring equal and just distribution of both benefits and costs. AI should be free from unfair bias and discrimination. Decisions taken by AI to the extent possible should be explainable to those directly and indirectly affected.  23:01 Nikita: This is all great, but what does a typical responsible AI implementation process look like?  Hemant: First, a governance needs to be put in place. Second, develop a set of policies and procedures to be followed. And once implemented, ensure compliance by regular monitoring and evaluation.  Lois: And this is all managed by developers? Hemant: Typical roles that are involved in the implementation cycles are developers, deployers, and end users of the AI.  23:35 Nikita: Can we talk about AI specifically in health care? How do we ensure that there is fairness and no bias? Hemant: AI systems are only as good as the data that they are trained on. If that data is predominantly from one gender or racial group, the AI systems might not perform as well on data from other groups.  24:00 Lois: Yeah, and there's also the issue of ensuring transparency, right? Hemant: AI systems often make decisions based on complex algorithms that are difficult for humans to understand. As a result, patients and health care providers can have difficulty trusting the decisions made by the AI. AI systems must be regularly evaluated to ensure that they are performing as intended and not causing harm to patients.  24:29 Nikita: Thank you, Hemant and Himanshu, for this really insightful session. If you're interested in learning more about the topics we discussed today, head on over to mylearn.oracle.com and search for the Oracle Cloud Infrastructure AI Foundations course.  Lois: That's right, Niki. You'll find demos that you watch as well as skill checks that you can attempt to better your understanding. In our next episode, we'll get into the OCI AI Services we discussed today and talk about them in more detail. Until then, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 25:05 That's all for this episode of the Oracle University Podcast. If you enjoyed listening, please click Subscribe to get all the latest episodes. We'd also love it if you would take a moment to rate and review us on your podcast app. See you again on the next episode of the Oracle University Podcast.

Auch im Jahr 2024 ist es für Jungunternehmen nicht mehr so leicht wie noch beispielsweise 2021, größere Finanzierungen aufzustellen. Könnte Crowdinvesting für Startups im Wachstum die Antwort sein? Diese und weitere Fragen besprechen wir im Podcast mit Daniel Horak, dem CEO der Crowdinvesting-Plattform Conda. Die Themen: - Die aktuelle Lage in der Welt der Crowdfinanzierungen - Welche Startups sich durch Crowdinvestments finanzieren können - Crowdinvesting vs. Finanzierungsrunde - Die aktuellen Vorhaben von Conda - Crowdfinanzierung als Rettungsseil für angeschlagene Firmen Wenn dir diese Folge gefallen hat, lass uns doch vier, fünf Sterne als Bewertung da und folge dem Podcast auf Spotify, Apple Music und Co. Für Anregungen, Kritik, Feedback oder Wünsche zu künftigen Gästen schick uns jederzeit gerne eine Mail an ⁠feedback@trendingtopics.at⁠. --- Send in a voice message: https://podcasters.spotify.com/pod/show/trending-topics/message

See omnystudio.com/listener for privacy information.

Topics covered in this episode: Python 3.13 gets a JIT UniDep - Unified Conda and Pip Dependency Management Don't Start Pull Requests from Your Main Branch instld: The simplest package management Extras Joke Watch on YouTube About the show Sponsored by us! Support our work through: Our courses at Talk Python Training The Complete pytest Course Patreon Supporters Connect with the hosts Michael: @mkennedy@fosstodon.org Brian: @brianokken@fosstodon.org Show: @pythonbytes@fosstodon.org Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesdays at 11am PT. Older video versions available there too. Brian #1: Python 3.13 gets a JIT Anthony Shaw Great article that walks through JIT concepts with a small example as if you were writing a parser in Python instead of C. Covers What is a JIT? What is a copy-and-patch JIT? and Why? How does the Python JIT work? Is it faster? This is a building block to future improvements Michael #2: UniDep - Unified Conda and Pip Dependency Management

Recorded while Hannah Conda was visiting over Perth PRIDE weekend, this episode is bloody long and supercharged with ridiculous stories, anecdotes and a tonne of gossip to really get you chuckling! A special appearance also by Hannahs wonderful brother, TIKTOK star 100% That Tim!

In our new podcast episode, we chat with Wolf Vollprecht, the creator of Pixi, a groundbreaking package manager merging Poetry and Conda's approaches.Discover how Pixi leverages Conda Forge's open-source community for robust package management.Wolf takes us behind the scenes, explaining Pixi's technical innovations, seamless Pip integration, and project-specific Pixi toml configurations.Learn why developing Pixi in public and collaborating with other package managers like Rye are key to its success.Get ready for an insightful journey into the future of Python package management with Pixi.And as always, we discuss wins and books as well. ---Get started with Pixi here.Connect with Wolf here.Notable book: Loved

On this episode we have Wolf Vollprecht and Ruben Arts from the pixi project here to talk about pixi, a high performance package manager for Python and other languages that actually manages Python itself too. They have a lot of interesting ideas on where Python packaging should go and are putting their time and effort behind them. Will pixi become your next package manager? Listen in to find out. Links from the show Black Friday at Talk Python: talkpython.fm/blackfriday Guests Wolf Vollprecht: github.com/wolfv Ruben Arts: github.com/ruben-arts pixi: prefix.dev Prefix: prefix.dev Launching pixi: prefix.dev Conda: docs.conda.io Conda Forge: conda-forge.org NixOS: nixos.org Packaging Con 2023: packaging-con.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Posit Python Tutor Talk Python Training

Today's guest is Braedon Hebert.    Braedon is the Co-founder of CondoWorks, an accounts payable automation platform built for property management companies (condo/HOA/commercial/residential). He is also an accountant turned entrepreneur.   Show summary:  In this episode of the How to Scale Commercial Real Estate Show, Braden Hebert, co-founder of Condo Works, discusses the role of technology and automation in the property management industry. Hebert explains how Condo Works, an accounts payable automation platform, streamlines the accounts payable process for property management companies, reducing errors and saving time. He also emphasizes the need for strategic thinking when implementing technology. The discussion also covers the challenges of balancing customer needs with revenue potential, and highlights key features of the Condo Works software. -------------------------------------------------------------- [00:00:00] Intro [00:01:33] The Challenges in Property Management [00:09:29] The Importance of Technology in Scaling a Business [00:11:27] The importance of technology and automation [00:13:04] Using technology to establish escape velocity [00:18:07] Automating utility downloading and invoice approval -------------------------------------------------------------- Connect with Braedon:  Linkedin: https://www.linkedin.com/in/braedonhebert/   Web: www.condoworks.co   Connect with Sam: I love helping others place money outside of traditional investments that both diversify a strategy and provide solid predictable returns.     Facebook: https://www.facebook.com/HowtoscaleCRE/ LinkedIn: https://www.linkedin.com/in/samwilsonhowtoscalecre/ Email me → sam@brickeninvestmentgroup.com   SUBSCRIBE and LEAVE A RATING. Listen to How To Scale Commercial Real Estate Investing with Sam Wilson Apple Podcasts: https://podcasts.apple.com/us/podcast/how-to-scale-commercial-real-estate/id1539979234 Spotify: https://open.spotify.com/show/4m0NWYzSvznEIjRBFtCgEL?si=e10d8e039b99475f -------------------------------------------------------------- Want to read the full show notes of the episode? Check it out below: Braedon Hebert (00:00:00) - So part of our technology will automatically download all those all those types of utility invoices then extract the data. So to eliminate any sort of data entry required then it can be approved and paid.   Intro (00:00:15) - Welcome to the how to Scale Commercial Real Estate show. Whether you are an active or passive investor, we'll teach you how to scale your real estate investing business into something big.   Sam Wilson (00:00:28) - Braden Hebert is the co-founder of Condo Works, which is an accounts payable automation platform built for property management companies. Braden is also an accountant turned entrepreneur. Braden, welcome to the show.   Braedon Hebert (00:00:40) - Yes. Thanks, Sam. Glad to be here.   Sam Wilson (00:00:42) - Absolutely. The pleasure is mine. Braden. There are three questions I ask every guest who comes on the show in 90s or less. Can you tell me where did you start? Where are you now? And how did you get there?   Braedon Hebert (00:00:52) - So as you alluded to, my I got my start as an accountant working for one of the big accounting firms, then went to a big company. But I entered the the startup and tech world about a decade ago in that role.   Braedon Hebert (00:01:05) - And that's where I met my current co-founder, who's the who was the chief technology officer of that first company. And so my path was was in the startup tech world in those finance roles. I went through some acquisition acquisitions throughout that, but wanted to take the leap into the the early stage incubation stage of a company and joined him as a as a co-founder of Condor Works.   Sam Wilson (00:01:33) - That's really cool. What is the what is the opportunity that you guys see? I guess you know, one, the startup tech world is highly competitive. And, you know, I can't imagine jumping into that. That's something that kudos to you guys, you know, for being willing to take those those risks I think that's really cool. But what's the opportunity that you guys see in what you're doing right now. And why is now the time to do it?   Braedon Hebert (00:01:58) - So maybe I'll go back to the to the very beginning. So one of the things that my, my co-founder did, in addition to helping build and develop companies, is he also became the treasurer on his condo board.   Braedon Hebert (00:02:10) - And that's where he saw firsthand some of the the challenges that face property management companies when it comes to processing and paying their bills. So there's there's a high invoice volume. There's multiple stakeholders plus complexity, not from the accounting side, but operationally, if you're trying to keep track of discrete financial records across all of your properties, the the accuracy and routing and recording of those invoices is critical. But but complex because paired with those challenges, it's also an industry that has been slower to adopt some of the more modern technological solutions. And so, for example, he was signing hundreds of checks every month. He was seeing vendors taking six months to get paid. And, you know, when you calculate the internal cost to the property management companies, it can cost 15 to $20 per per invoice just to pay that. So he said, well, this is awful. Ben being the tech guy he is, he said there's there must be a better way and I'm going to build it. And so that's that's how calendar works was born.   Braedon Hebert (00:03:17) - And it was. And we see that that pain that still exists across across many property management companies.   Sam Wilson (00:03:23) - Got it. No, that's really interesting. How does this differ. And forgive my ignorance here because I neither run a tech startup. I don't run a accounts payable automation platform. And um, yeah, anyway, forget what else, I don't run. But anyway, all of those being said. When it comes to accounts payable. In my mind, I think, gosh, I mean, it seems like you could just get ACH set up out of your various bank accounts, you receive your invoices, you ACH or vendors, and off you go. Why is it not so simple?   Braedon Hebert (00:03:56) - So I would I would back up. You know, paying it can sometimes be the easy part. It's it's the, the full cycle being receiving or getting the invoices than having it properly approved, entering that information into the accounting system. So recording that invoice and then and then issuing payment. So you know our platform handles that end to end with with tech and automation built in throughout that process.   Braedon Hebert (00:04:26) - So I'll you know, one of our my favorite examples is is a utility bill. So you know, gas power, water even, you know, the telecom bills. Um, either they're they're coming in the mail a couple of weeks later, then you're rushing to pay them, or someone has to spend time logging in and clicking, downloading, download, invoice, download, invoice downloading. So we we know some of our customers were spending days just doing that. So part of our technology will automatically download all those all those types of utility invoices then extract the data. So to eliminate any sort of data entry required then it can be approved and paid. And so a lot of that upfront work in terms of just handling the invoices can be eliminated, which once you get to a certain scale, you know, some some of our customers are processing thousands, 10,000 invoices a month. And so that that can really add up, uh, across the team.   Sam Wilson (00:05:26) - And the opportunity for.   Sam Wilson (00:05:29) - Error.   Sam Wilson (00:05:30) - I mean, just becomes magnified where it's like, did we get that utility invoice that's emailed, actually paid, and did it get logged properly? And we're counting on, which is just crazy in 2023, we're still counting on human touch on some of those things where it's like.   Sam Wilson (00:05:48) - And so no, I see what you're saying. And that makes a lot of sense, especially for property management companies that are handling, like you said, you know, thousands potentially of invoices a month and going, gosh, is this is this being properly logged? I mean, even for us at just the handful of facilities that we own it, we're trying to put those processes in place where it's like, hey, this is. The is that paid this month, I don't know. So there are some similar meetings we were having just recently were like, is that okay? No, this needs to be a system like very, very tight knit system. Maybe we're not saying.   Braedon Hebert (00:06:16) - Hey Sam, our lights went out. What happened? Oh, shoot. That that invoice that I guess we didn't get it didn't forgot to pay it. And. Yeah, that's the worst that can happen.   Sam Wilson (00:06:27) - Absolutely. Absolutely. Yeah. You get a disconnect notice and you're like, how do we. And which we haven't had a disconnect notice.   Sam Wilson (00:06:33) - But I'm just thinking worst case like you're saying like lights went out or you get a disconnect. How is this happening. And I can see.   Braedon Hebert (00:06:38) - How it happens. That was a theoretical example of course.   Sam Wilson (00:06:41) - Right, right. Luckily it has not happened to us. But that is I mean, I could see it very easily happening accidentally or it's like we don't know how we missed that. So that's that's really cool. Can you tell me we talked about this a little bit before we kicked off the show? You use the word condo more broadly maybe than what I would say here in the States. Can you define really kind of the the broader scale of the product that you guys are developing in the, in the what condo means?   Braedon Hebert (00:07:09) - Yeah. So yeah, I had said our current branding gives away a bit of our origin. So maybe if I say the word aboot or process or process, I'll also give away my Canadian roots. So we got our start in Ontario. In Canada where we're condo is kind of the catch all term for a HOA or community or association.   Braedon Hebert (00:07:32) - And that's that's where we got our start. And that was the the branding and the website that was that we've been developing. But our goal more broadly is to be is to be a solution for, for all types of, of property management companies. So whether it's the condo HOA association as well as commercial residential. And I was actually looking up our customer roster. We have a senior lifestyle management company in the Tennessee area as well. So it's it's you know, the the challenges are similar. And it's from a branding. It's something that's on the on the strategic table for us. But yeah, thank thanks for bringing that up. Uh, just to be able to help. Yeah. Broaden the conversation and to help to clarify that.   Sam Wilson (00:08:18) - Right. Right. Because I mean, your product could very easily be deployed across industrial facilities or industrial property managers to multifamily property managers to, I mean, anybody that's managing a large portfolio of assets that, like you said, you know, has has an incredible accounts, payroll.   Sam Wilson (00:08:35) - Or accounts payable. Excuse me. If I could speak today, you know, invoices coming in. You need to have that product where you can reasonably take those in, make sure they get paid, and then do it again without without making sure that there's a manual process to keep track of that. So, Braden, one of the things that you said in the onboarding question, I always asked us and again, for those of you that listen, what's a fun fact or surprising view in one of the views that you put in there, Braden, was that tell me a company's tech stack, and I can tell you the growth rate. I think that's really, really interesting. What does that mean?   Braedon Hebert (00:09:08) - I. Yeah. Like the the question prompted. Trying to be a bit controversial or edgy but so we've. You know in building this company and talking to hundreds or property management companies, you start to see different patterns. And as a, as a business, it's in you know, real estate in general is often it's is quite local.   Braedon Hebert (00:09:29) - And there are, you know, there are companies that's, that's that's their focus. That's that's where they want to go. But there's others that I call it a bit. I use the term escape velocity for those that are able to, to, to build a company that expands. Into a wider geographic area. And so there's there's a, you know, in property management specifically, there's there's their startup costs, although the switching costs are low. So it's really it's relatively easy to create your own. If you're a property manager, you get four properties. You can you can exist as a standalone business. But those that obtain the escape velocity are the ones that, that, that, that have that extra is that whether it's ambition or operational excellence, to be able to, to grow and specifically think manage people is a huge part of that. Beyond, you know, beyond their local area, beyond the, the, the, the greater metropolitan areas that they ran into to, to, to to grow into a much, much bigger footprint.   Braedon Hebert (00:10:31) - Um, and so I and I the other pattern is that the, the use of technology is a common characteristic of those companies that are able to obtain that escape velocity. So operationally they have to be be sold. They the managing of people is is a huge part of that. But the being able to adapt and and effectively use with the modern technological tools that exist can really help those companies to, to, to grow at a higher rate than, than others who, who aren't necessarily doing that.   Sam Wilson (00:11:10) - I think that's a really insightful observation. It's not something I would have thought about, but what are some of the things, I guess, that as as you see those various companies that are willing to embrace technology, willing to embrace automation, like.   Sam Wilson (00:11:27) - What.   Sam Wilson (00:11:27) - Does that say about them? Because there's more to it than just, hey, I like technology and automation. There's something about their mindset. And their approach.   Braedon Hebert (00:11:37) - Is, yeah, it's not chasing the new shiny thing, but it is a it is a mindset that exists that they're thinking about how to how to improve their business.   Braedon Hebert (00:11:48) - So they're they're not chasing the, you know, every the everyday fires. They're able to elevate it and think strategically. So, you know, it's not about, hey, we're it's not just, hey, we're we have these cool tech toys. It's it's they're thinking strategically about how to just effectively manage their business. And, you know, the the tech they use is a part of that. But it is a common pattern that we've observed amongst those companies that do seem to have a have a higher growth rate than others that aren't there.   Sam Wilson (00:12:18) - Yeah. No, I think that's, that's that's really insightful. And you said not putting out fires because it takes time. I mean, it takes time to think through. Yeah. There's automations. There's there's there's technology out there. But implementing it is a discipline I think. I know at least it is for me. Maybe I'm not that bright and I'm certainly not tech savvy. And so for me, it's harder to be like, okay, how are we going to use this tool effectively in our business? And then how does it act? Or how can we structure it such that it solves problems without creating a whole pile of new ones that now is now just more work? And so I think that's but figuring those things out to where you're getting beyond the day to day, like, okay, hey, this is how this technology solves problems and saves us time and money is really, really cool.   Sam Wilson (00:13:04) - What how did how do you view that as it pertains to your business? Like what are what are you guys currently doing to use tech to establish or get that escape velocity that you need?   Braedon Hebert (00:13:19) - Yes. Yeah. It's it's. So I, we had a meeting with our or some of our investors last night and they, we're also guilty of that as well in that being able to focus on your current customers and you want to provide a good, good level of service for them and a really good experience. And that can often trump, you know, you know, Trump thinking about, okay, this is this is I need I need time to work on the business. So I was working in the business, working on the business and carving that out. And that's where one of the benefits of of having, you know, whether it's a board of advisors or your business, business groups that you may be in is is it does act as a forcing function for you to, to to think about the business and how to how to improve it.   Braedon Hebert (00:14:08) - Um, for, for tech, one of the benefits of being a tech company is that we can build a lot of our own, our own solutions, right, to help that. So we we've we got our start in in about late 2019 and we've seen it growing across Canada, United States, different different types of property management companies. But we've managed to do so and and multiply the footprint of the company without multiplying the amount of people that we need to support that customer base. And so that's that's having a discipline from a product development standpoint, not to just focus on new features or the shiny things for us are being, you know, new things for us develop. It's also being able to focus on, you know, how do we make our system as efficient. That not only helps us, but it does also help our customers in that they're they they have less, less questions. And there's there's things that make it easier for them. So it does come down to to discipline though, at the end of the day, to, to force yourself to take that step back.   Sam Wilson (00:15:10) - It is hard. It is absolutely hard. We in the in our laundry facility business, you know, we use software inside of that and it's interesting to watch and it's newer, not completely new, but they're still constantly solving problems. And there's even, you know, there's even forums where we can put in feature requests where it's like, hey, you know, we'd love to see, you know, XYZ on our point of sale or whatever, you know, whatever the the feature is. And I would think for you guys, that same thing probably is true where people are constantly saying, hey, what's, you know, can we have this feature? Can we add that? Can we add this? How do you prioritize those in what's maybe a problem that you guys are actively internally trying to solve that you haven't solved yet?   Braedon Hebert (00:15:53) - The prioritization question is is tough because everybody has their. Yeah has has. Yeah that's what they want. So you have to balance. One is is this a is this a one off for this one customer.   Braedon Hebert (00:16:08) - Some of them are are louder than others. And so you have to consider is this broadly applicable. Will feature customers find this attractive. And also you have to also wait that as to the revenue potential as well. And so we've had some of our as we've grown we've gotten bigger customers that have have have pushed us in a good way to develop the features that they, as a bigger company, need for their scale. And so that's that's been, you know, how we have prioritized those, those features and. Terms of what's on our on our roadmap. The some of the ones that I'm, I'm personally most excited about is like is to help. There's a lot of similarities and applicability be going from, you know, HOA or communities to commercial and residential. Um, there are certain nuances to, you know, outside of the HOA space that that do differ. And so it's it's there are certain features that would be very well received by certain. Potential customers that we've had conversations with in the, in the commercial space, um, for example, or even in, in rather than being third party managers, you're an asset manager where you own everything versus in the space, you're managing independent hoa's.   Braedon Hebert (00:17:39) - And so, um, being able to, to achieve that vision, the more broad of of being able to cater to property management more broadly, um, building off of that, that HOA Association condo, um, base.   Sam Wilson (00:17:54) - Got it. That's really, really cool. All right. Last and final question for you is what's something about your software or your solution maybe that I haven't asked that you would want to make sure that we cover.   Braedon Hebert (00:18:07) - Well, we spoke about the the automated utility downloading, which is is one of those eye catching features as boring as it sounds. Um, yeah. But everyone, even personally, everyone hates dealing with their utility bills. So if we can automate that, that's that's something that that people really, really enjoy. I there's if I can say to you, so what if if, if, if you're if your current operations include handling paper whether that's receiving invoices on paper, having a cabinet that you store everything in or signing, signing paper checks, you know if that can if you can envision that going away.   Braedon Hebert (00:18:53) - That's that's yeah. Especially when we talk to owners, oftentimes they're the ones who sign the checks. And it's like, okay, what happens if you go on vacation? Well, you know, I signed a bunch before I leave and then I have a huge stack when I come back. Okay. Well, you know, the the the conveyor belt doesn't have to stop running. Uh, in those, in those scenarios. Um, so that's one and I think the other one that in the larger scales is, is being able to really configure, um, who needs to approve what invoice. And so it's reducing a lot of the noise, but also automating how who needs to approve what invoice and when and enforcing that. So one, it reduces work, but also it helps enhance internal controls to make sure that invoices are being properly, properly screened. So that's that's we're getting a little deep there. But that's know that's the stuff that we care about though.   Sam Wilson (00:19:43) - Those are huge pain points that you're solving for though especially that invoice.   Sam Wilson (00:19:49) - I mean, at least that one that invoice approval speaks to me where it's like, you know, as we grow, I go, my gosh, you know, I don't want to be in front of every invoice that comes through the door and have to be the one that signs off on like, oh, yeah, okay. You know, whatever it is we're say we're. Redoing a facility the paving contractor sends there. Like, I mean, there should be a way to and again, maybe that's just a, you know, small example that doesn't doesn't apply. But I think there's you're touching on some things that everyone thinks about and is trying to figure out a way to solve. So that's very, very cool. Braden, thank you for taking the time to come on the show today. I certainly enjoyed it. It was great learning about what you guys do, how you do it, and the opportunity you guys see in the market right now. And it sounds like it's being very well received.   Sam Wilson (00:20:34) - So this has been a blast having you on today. If our listeners want to get in touch with you and learn more about you or your product, what's the best way to do that?   Braedon Hebert (00:20:41) - So our website is Conoco. So not not.com but.co. And so that's that's our website. And then our we're most active on LinkedIn which where you can find me on there as well as as Conda works on LinkedIn.   Sam Wilson (00:20:59) - Fantastic. We'll make sure you include that there in the show notes. Braden, thank you again for your time today. This was certainly a blast. I do appreciate it.   Braedon Hebert (00:21:06) - Okay. Thank you. Sam.   Sam Wilson (00:21:07) - Hey, thanks for listening to the How to Scale Commercial Real Estate podcast. If you can do me a favor and subscribe and leave us a review on Apple Podcasts, Spotify, Google Podcasts, whatever platform it is you use to listen. If you can do that for us, that would be a fantastic help to the show. It helps us both attract new listeners as well as rank higher on those directories.   Sam Wilson (00:21:28) - So appreciate you listening. Thanks so much and hope to catch you on the next episode.

How well do you know your Python packaging tools? These are things like pip which install your project's dependencies and their dependencies and so on. In this mix, we have more modern tools such as Poetry, Flit, Hatch and others. And even tools outside of Python itself which may attempt to manage Python itself in addition to the libraries. To make sense of all of this, we welcome back Anna-Lena Popkes for an unbiased evaluation of environment and packaging tools. Links from the show Anna-Lena's website: alpopkes.com Anna-Lena on GitHub: github.com Accompanying Blog Post: alpopkes.com Talk from PyCon DE: youtube.com Talk from EuroPython: youtube.com Talk Python's Data Science Jumpstart with 10 Projects course: talkpython.fm Rye: github.com Poetry: python-poetry.org Material for MkDocs: squidfunk.github.io 100 Days of Python in a Magical Universe Episode: talkpython.fm pip-tools: pip-tools.readthedocs.io Hatch: hatch.pypa.io PDM: pdm.fming.dev Flit: flit.pypa.io Conda: docs.conda.io Pipenv: pipenv.pypa.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors IRL Podcast Sentry Error Monitoring, Code TALKPYTHON Talk Python Training

Environment Management und Packaging 6. Oktober 2023, Jochen Soooo, nach einer langen, dunklen, ungeplanten Sommerpause aufgrund unüberwindlicher Terminfindungsschwierigkeiten gibt es jetzt endlich wieder eine neue Episode

Mein Interviewpartner ist Dirk Littig, der als Co-Founder und Co-CEO für Conda arbeitet. Der Bänker und Finanzierungspezialist gibt uns einen Einblick in die Welt des Crowdinvestings rund um die Finanzierung von dem Mittelstand aus dem DACH Raum und erläutert die Chancen und Risiken. Shownotes Jetzt auf Conda investieren: https://investor-stories.de/conda

Justin catches up with drag race royalty Raven who drops her most underrated makeup tip, how to win Snatch Game and borrowing RuPaul's outfits PLUS Season 2 down under queen Hannah Conda joins him to break down the most recent episode! Follow Justin on social media @jus_hill and subscribe to the podcast on the FREE LiSTNR app now!See omnystudio.com/listener for privacy information.

In this episode with collage artist Jonathan Conda, we got really deep and quick.  We discussed the power of history and the nuance of storytelling along with  how history is incredibly limited as a form of truth telling.  We talked about bias and how that plays into what histories we remember and which ones we forget.  We also had a deep discussion around identity politics , social media, and why art is a necessary tool to penetrate down to the human spirit.  We discussed Jonathans creative process and how he sources the imagery in his incredible collage work.  We even talk about AI, technology, and how that is impacting art making.  --------------------- From Jonathan's Website: Hi, my name is Jonathan Conda. I create future nostalgia (ok, you might say it's just collage art) as The Quiet Fight. My work, while remaining politically neutral, seeks to challenge our feelings around culture, history and global citizenship. I try to elevate those who are ignored, forgotten or dehumanized. There's beauty in all of us, if we're willing to see it. Within my ~8 year professional art practice, I've created published editorial works (Noema Magazine, Atlas Obscura), podcast art (Pineapple St. Studios: The 11th, Radiotopia: Oprahdemics) and album artwork ( Ben Harper, “We Need to Talk About It”, Jaimi Faulkner, “Allen Keys & Broken Bits” ). I've collaborated with renown photographer Giles Duley and have been interviewed on Talking Pictures.I currently reside in Gilbert, AZ, USA but, thanks to the internet, enjoy a global clientele.   https://www.instagram.com/the_quiet_fight/ https://www.thequietfight.com/ See More from Martin Benson *To stay up on releases and content surrounding the show check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠my instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠ *To contribute to the creation of this show, along with access to other exclusive content, consider joining ⁠⁠⁠⁠⁠⁠⁠⁠⁠my Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠! Credits: Big Thanks to Matthew Blankenship of ⁠⁠⁠⁠⁠⁠⁠⁠⁠The Sometimes Island ⁠⁠⁠⁠⁠⁠⁠⁠⁠ for the podcast theme music! --- Support this podcast: https://podcasters.spotify.com/pod/show/martin-l-benson/support

In recent years, there has been a lot of experimenting how we work with dependencies and external libraries for our Python code. There is pip, pip-tools, Poetry, pdm, pyenv, pipenv, Hatch and others workflows. We dove into this deeply back on episode 406: Reimagining Python's Packaging Workflows. We're back with Ofek Lev to take a deeper look at Hatch. Links from the show Hatch: hatch.pypa.io Ofek on Twitter: @Ofekmeister Mamba: github.com Hatch env management: hatch.pypa.io Packaging a Python project tutorial: packaging.python.org Customize project generation: hatch.pypa.io Textual: textualize.io Ruff on Talk Python: talkpython.fm RustUp: rustup.rs Conda: docs.conda.io import antigravity: xkcd.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy Sponsors Microsoft Founders Hub 2023 Sentry Error Monitoring, Code TALKPYTHON Talk Python Training

Don't have time to listen to the full show? We got you covered on the Nathan, Nat & Shaun Quickie, all the best bits from Thursday, 19th of January's episode!See omnystudio.com/listener for privacy information.

Ding Dong! For In My Own Home's season 1 finale BarbieQ invites her longtime drag sister and friend Hannah Conda (RuPaul's Drag Race: Down Under Season 2) over to reminisce on old times, talk about the birth of Hannah Conda in the Perth drag scene and discuss the Drag Race: Down Under experience. Ronnie's story concludes.https://www.itdevents.com//tours/babz

Daniel bekommt bis zu 3.000 Finanzierungsanfragen pro Jahr. Firmen wie "All I Need" oder Ökostrom haben die Gelder von und über CONDA bekommen. Er hat Crowd-Investment im deutschen Sprachraum aufgebaut und leitet eines der führenden Finanz-Start-Ups im deutschen Sprachraum. Sein Unternehmen boomt nicht zuletzt auch durch und wegen den Krisen. Denn in diesen Phasen wird Eigenkapital für Unternehmen immer wichtiger. Die Finanzierung über die Bank reicht oft nicht mehr, um durch die Krisen zu kommen. Daniel hat durch seine charismatische Art schon zahlreiche Menschen ermuntert ihr eigene Company zu gründen, was Daniel auch abseits von CONDA freut. Das Highlight des Jahres war aber seine eigene Hochzeit.

You know her from RuPaul's Drag Race Down Under, and Courtney and Vanity know her from the antics of years gone by - it's Hannah Conda! Got something you want to ask us? Brenda in IT is awaiting your email at Brenda@novapodcasts.com.au Nova Entertainment acknowledges the traditional custodians of the land on which we recorded this podcast, the Gadigal People of the Eora Nation. We pay our respect to Elders past and present.  CREDITSHosts: Courtney Act and VanityGuest: Hannah Conda  Lead Senior Producer/Editor: Hannah BowmanProducer: Chae Rogan  LINKS Brenda, Call Me! Music Video https://bit.ly/2Nzlsya Courtney Act's Instagram @CourtneyAct Vanity's Instagram @wigsbyvanity Nova Podcast's Instagram @novapodcastsofficial Find more great podcasts like this at novapodcasts.com.auSee omnystudio.com/listener for privacy information.

Subscribe to the podcast on the LiSTNR app or wherever you get your podcasts now and follow Justin on social media @jus_hill for more now!See omnystudio.com/listener for privacy information.

This week on the podcast I have the top 3 queens from ‘RuPaul's Drag Race: Down Under Series 2” and on today's episode - I will hopefully give the fans a better insight into 'Hannah Conda' resume and and help you answer that question is 'Hannah' is our winner of the 2nd 'Down Under' series?  This Saturday is already the finale and while the series has been a wild ride, I think the finale is going to be an excellent celebration of three very popular queens who truely deserve to be there. 'Hannah Conda' for a long time was a standout from the 'Perth' drag circuit, however quickly outgrew the 'Golden State' and in 2015 moved to Sydney where she cemented her superstar status by being the only queen to have ever won both 'Rising Star' and 'Entertainer of the Year' at the 'Drag Industry Variety Awards' (DIVAs) in the same year. Hannah has been consistent and fantastic to watch. There is something very polished and on purpose with with everything she has done this season. Fans have said it is her show to lose - so we shall wait and see. We will talk about why she nearly didn't apply for this season, her connection with 'Molly Poppins,' why she couldn't be bothered with the drama and of course what she will do with her win if she snatches that crown! Plus for the last time we will play my ‘shady or lady' game - with a few surprising answers! Learn more about your ad choices. Visit megaphone.fm/adchoices

This week on the podcast I have the top 3 queens from ‘RuPaul's Drag Race: Down Under Series 2” and on today's episode - I will hopefully give the fans a better insight into 'Hannah Conda' resume and and help you answer that question is 'Hannah' is our winner of the 2nd 'Down Under' series? This Saturday is already the finale and while the series has been a wild ride, I think the finale is going to be an excellent celebration of three very popular queens who truely deserve to be there.'Hannah Conda' for a long time was a standout from the 'Perth' drag circuit, however quickly outgrew the 'Golden State' and in 2015 moved to Sydney where she cemented her superstar status by being the only queen to have ever won both 'Rising Star' and 'Entertainer of the Year' at the 'Drag Industry Variety Awards' (DIVAs) in the same year.Hannah has been consistent and fantastic to watch. There is something very polished and on purpose with with everything she has done this season. Fans have said it is her show to lose - so we shall wait and see.We will talk about why she nearly didn't apply for this season, her connection with 'Molly Poppins,' why she couldn't be bothered with the drama and of course what she will do with her win if she snatches that crown!Plus for the last time we will play my ‘shady or lady' game - with a few surprising answers! Learn more about your ad choices. Visit megaphone.fm/adchoicesSee omnystudio.com/listener for privacy information.

It's Joel's turn to take on Quick Draw this week and we brought in the one and only Hannah Conda from RuPaul's Drag Race Down Under to take him on. Who will win?See omnystudio.com/listener for privacy information.

RuPaul Down Under's very own Hannah Conda (and sister of the Bin Chicken) joined Nathan, Nat, & Shaun to talk them through her success on the show and what comes next! The latest hiccup from King Charles III is also dissected, and Jennifer Coolidge's hilarious acceptance speech at the Emmy's had the guys asking… what happened to you before a major event?See omnystudio.com/listener for privacy information.

This week, Mike is joined by Julia Delbel and first-time guest Jared Kirschenbaum from Murphy's Multiverse to discuss the MCU's Phase 5 and 6 slate announcement, the Black Panther Wakanda Forever trailer, and the rest of the major news spinning out of San Diego Comic-Con. --- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/app Support this podcast: https://anchor.fm/racial-draft-podcast/support

Guest Isabela Presedo-Floyd Panelists Eriol Fox | Georgia Bullen Show Notes Hello and welcome to Sustain Open Source Design! The podcast where we talk about sustaining open source with design. Learn how we, as designers, interface with open source in a sustainable way, how we integrate into different communities, and how we as coders, work with other designers. We have with us today, Isabela Presedo-Floyd, who's a UX/UI Designer at Quansight Labs. She helps build open source scientific software with an emphasis on improving accessibility of communities and their tools, which we will be discussing in depth with her today. We learn about some of the projects Isabela's been working on such as Jupyter, Spyder, Napari, and Conda. Also, we find out how accessibility is the guiding compass for most of Isabela's design things. Go ahead and download this episode now to learn more! [00:01:05] Isabela explains what she currently does, the different projects she works on, and the projects that she's had to do the most creative problem solving for. [00:03:46] We hear more about the imaging in bio fields and what that means to Isabela as a designer. [00:06:51] The topic of transfer of knowledge is brought up and Isabela tells us how that's made possible for her to contribute to these projects. [00:10:47] Eriol wonders if Isabela has found other ways to find that sense of collaboration, that sense of social within the design process when she doesn't have that many designers working in the open source and science space. [00:14:50] Georgia wonders if Isabela uses any tools with people about how she validates design directions. [00:18:52] How would Isabela sustain this work if she had a magic wand? We also hear about a manifesto document called Slow-Science. [00:24:49] Isabela details how she's worked with different kinds of accessibility needs in some of the complex tools, how designers within open source can pace themselves better to include them, and about the W3C and the alt text Decision Tree. [00:33:00] Find out where you can follow Isabela online. Quotes [00:09:26] “A lot of this is teaching people how to interact, teaching people the expectations they can transfer the knowledge, helping them transfer knowledge from other software.” [00:09:54] “I don't really hear people discussing that maintainers to me are also users. They're just users with a very different goal.” [00:13:13] “I feel that's one of my main ways to collaborate because people are coming in showing me what work they're doing and that gives me a better sense of what users are doing.” [00:21:14] “If that pace pressure wasn't on, maybe we would all be able to take that time to do the thoughtful things.” [00:26:00] “I personally believe that accessibility is just good UX and is the guiding compass for most of my design things because it helps me make a lot of my choices.” [00:28:40] “I've been working with trying to come up with contributing events that give that people that structure so that I can leverage whatever their skills are, and they can leverage mine.” Spotlight [00:33:39] Eriol's spotlights are OPEN AAC and Project Lima. [00:34:35] Isabela's spotlight is The A11Y Project. [00:35:28] Georgia's spotlight is a step forward in accessibility efforts with Figma. Links Open Source Design Twitter (https://twitter.com/opensrcdesign) Open Source Design (https://opensourcedesign.net/) Sustain Design & UX working group (https://discourse.sustainoss.org/t/design-ux-working-group/348) SustainOSS Discourse (https://discourse.sustainoss.org/) Sustain Open Source Twitter (https://twitter.com/sustainoss?lang=en) Richard Littauer Twitter (https://twitter.com/richlitt?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Eriol Fox Twitter (https://twitter.com/EriolDoesDesign?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Georgia Bullen Twitter (https://twitter.com/georgiamoon?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor) Isabela Presedo-Floyd GitHub (https://github.com/isabela-pf) Isabela Presedo-Floyd Twitter (https://twitter.com/isabelapf2) Isabela Presedo-Floyd LinkedIn (https://www.linkedin.com/in/isabela-presedo-floyd-32b99a160) Quansight Labs (https://labs.quansight.org/) Napari (https://napari.org/) Jupyter (https://jupyter.org/) Conda (https://docs.conda.io/en/latest/) Spyder (https://www.spyder-ide.org/) Slow-Science (http://slow-science.org/) W3C Web Accessibility Initiative-An alt Decision Tree (https://www.w3.org/WAI/tutorials/images/decision-tree/) OPEN AAC (https://www.openaac.org/aac.html) The A11Y Project (https://www.a11yproject.com/) Project a11y Lima (https://projectlima.co/inclusive-design-southeast-asia/) Figma-A step forward in our accessibility efforts (https://www.figma.com/blog/a-step-forward-in-our-accessibility-efforts/) UX Research & Design-pip.documentation v22.1.1 (https://pip.pypa.io/en/stable/ux_research_design/) Pip UX Research & Design-GitHub (https://github.com/simplysecure/pip-ux-docs/blob/main/pip-ux-docs/pip%20UX%20Research%20%26%20Design%20Final%20Draft.md) SimplySecure Slack (https://simplysecure.slack.com/join/shared_invite/zt-8ao6mfev-7QjlZYJsNh3ibBodc_Cl6w#/shared-invite/email) Credits Produced by Richard Littauer (https://www.burntfen.com/) Edited by Paul M. Bahr at Peachtree Sound (https://www.peachtreesound.com/) Show notes by DeAnn Bahr Peachtree Sound (https://www.peachtreesound.com/) Special Guest: Isabela Presedo-Floyd.

This week (well, last week, but who's counting) we talk with Anna(conda) Wood about fitness and nutrition, DSing, motivation for racing in ZRL when you're going for finish points only, and balancing Zwift races and outdoor rides

Welcome to Cannabis Daily - Your daily guide to cannabis news, industry trends and trade ideas in under 5 mins.Episode Summary:TLLTFFLGCINLBMadmenHosted & Produced By:Elliot LaneAaron Thomas Contact us at: cannabishour@benzinga.comFollow Benzinga Cannabis On Social MediaInstagramTwitterYouTubeLinkedInSubscribe to all Benzinga Podcasts at https://www.benzinga.com/podcastsSubscribe to the Cannabis Insider Newsletter to get more cannabis news and trending links delivered to your inbox.Tune in weekly to Cannabis Hour at 4 pm ET every Thursday for Cannabis News & Executive Interviews at bzcannabishour.comHit us up at https://www.benzinga.com/cannabis/ for more news today, tomorrow, and everyday.Access All The Cannabis Daily Episodes HereFor Top Gainers & Losers Cannabis stocks of the day check out https://www.benzinga.com/cannabis/stocksNOT FINANCIAL ADVICEThe Information Contained on this Podcast is not intended as, and shall not be understood or construed as, financial adviceUnedited Transcript:Friends it is feel good day today. What is cracking? This is Elliot Lane host of cannabis daily, as always thanks to my producer, Aaron Thomas, who will be joining us in five-ish minutes to chat through some news as he does every Friday.Thanks Benzinga for giving us the platform to do this. We bring you news and insights every day. A lot of stuff happening, man, on Aaron. I don't know why they don't spread some of this news out away from earnings a little bit, but maybe it's to cover up some of the earnings who knows, but tons of stuff to talk about today.Obviously we got lots of opinions and hope this gives you a direction to look at for your day. So let's get. Tilt holdings having those a week. Y'all T L L T F or suitable for adult use at another Massachusetts dispensary, the second one in a week in that state pending final inspection. So I think final maybe Is is coming, but pretty much, they're still props to Gary.Mann's leaving that company as good as he else in this, in this industry, flora grow their side of life. FLDC announced pricing of unblock offering of 10 million units at three bucks per current. Well, when I looked earlier was around 360 9 three 69 cents. Of course. I believe that is down 30% since they announced that news.I still a fan of flora growth. I think they have one of the more. Product lines and footprints in the base, obviously Latin American base. So you have to believe in that part of the world's cannabis operations, but I think for growth is a strong company, but the market, not a fan of this news. So they will continue to be listed through this. And we'll see how this turns out. Company village farms would BFF cannabis and produce operations, not affected severe weather. Just in case you are wondering, I personally was not aware of whether in British Columbia, but it's good to hear that are continuing on as normal unity road item labs of basically they're their franchise.Well, the dispensary model is unity road joins the international franchise association item nine labs listed on the OTC for I and L B first cannabis dispensary franchise to become members. Cool update. I think, you know, moving. Forward into this skin being the leading franchisor in cannabis. And this remains the fact, you know, once of course everything's federally or somebody else jumps into the franchise model, who knows in the feud and nine labs is working really hard to lead this part of the sector.Great. It's a California based company, their OTC GPF T has to release a Presley's defy their sale of stock by executives execs, take salary and do favor equity compensation. Their sales of their stocks are all executed by perforators told to minimize the price volatility, not sure successful those traders were considering they had to release a PR clarify.But I like the. Form of compensation for the executives, but obviously they paste this out a little differently in the future admin, M M in FF trial, coming to a congestion, former CFO Parker resigned, but felt full claims. He is owed just under 25. Millions has higher and so will go to jurors as early as next.MI w you know, obviously I, I'm not familiar with this case, med men, of course, several lawsuits in the, this seems to lean toward med men, everything that I've read this morning. Scott Cooper, as it, and CEO of Hexo has also been appointed to their bub directors props to him. He has experienced with trusts horrors, and obviously texts. For Sebastian St. Claire after harsher last but not least. Nope. Nope. Two more news. I hide your face. I'm sorry. A Conda court testing the waters of in the U S this is pretty big, in my opinion, a national company to listen to the U S probably since. Which isn't that long ago, but you know, nobody really S in my opinion to them and, and for growth, but this is an international medical cannabis company with assets, such as a cultivation and processing campus in South Africa as tan Mart in the UK.So in my opinion is going to be. Super interesting to watch. I think we'll probably be along the same lines as insecure that not necessarily to till raise level at yet, you know, probably not to the excitement of flora growth court, but you know, I, this is Intercare could be a good comparison for how a conduct could be would once it lists in the U S.Last, but not least give a shout out to my main man, Michael Mills body in my other stellar news release for their rec year end financial results. Year over year revenue increased 332% from the end of 20 at the end of 2021 Q4 revenue. 40% sequentially profitable Q4. They are going to have a call at 11:00 AM Eastern.We'd like to tune in today. But I'm very excited for them has worked incredibly hard. He's taken all of his debt off of his sheep. He is of course always open to adding more debt than anybody else in the space. And also, you know, shout out to cannabis. I'm pretty major debt financer in the space cannabis hour, chatting about what debt has done for cannabis.So please tune into us know any thoughts you have there, but I, in my opinion, I'm super body and mind that's B M M J on the OTC. I think Mike Mills, Gary Santo, two of the most underestimated executives in this industry. I think they're both incredible. So big fans of tilt, big fans of body of mind. And make them on your watch list at the very least, if you can invest in us plant touching companies. So with that being said, Elliot's ramble for the day is done. And Aaron Thomas has Ram day begins. What's up big 80. What's up big Elliot. How's it going? I'm actually kind of a big dude. So watch your face.Oh, I'm good, man. Happy Friday. Good things. This is a podcast. I know what I'm trying, man. I'm trying to lose that way. What are you going to hear drinking? Half a cup of creamer in my coffee, but we're still in zinger nation. Don't worry. Elliot is a great looking dude. So my man trying to woo me over. Once you got for us today, let's get right into it. So you touched on it yesterday, but let's start it off with this New York subways ban ads for cannabis or mushrooms. So ads about psychedelics is cannabis and other things that promote unsafe behavior are now banned by new York's MTA. So since you brought it up, Aaron, you know, I did mention this yesterday.You've been on the subways in New York recently, recently. It's, this is hysterical to me. Like, I mean, it's the same thing with Gavin Newsom in California, banning the billboard, same thing, I think in like South Dakota and some of these in Michigan and some of the states where they have like advertising bans on case, which is actually not too far away from other sins, like alcohol and tobacco.But what's funny to me is the ads for like OkCupid and some of these other types of companies are so sexual. Yeah. And the subways, and they're worried about like, And I'm just like, have you guys seen the orgy ads you've put in the subways recently? I'm not sure if you have or not, but it sounds like, yeah, I actually saw that when I was there.I thought it was hilarious. And then on another note, so even if you're downtown in New York and you just walk around and you're just going to get the message of marital. Everywhere you go, every corner you turn, someone has marijuana, there are stores where you can buy marijuana and smoke it right outside the store in New York city.So, I mean, we'll see how this goes. And this is just so silly, but I mean, I get why it's on the same level as the others, these other SIM products, but something definitely not equal this picture. Anyways. What's next brother. All right. So we touched on New York where you live, let's touch on Michigan, where I live.So Michigan works to limit the amount of cannabis that caregivers can grow. This is not a positive move forward that I think at least Michigan wants to limit caregivers, grow amounts of move that is always contentious in the medical cannabis community. So let's see. So here's, I I'm torn if I'm going to be honest.Y I, what do you, I mean, if you have the exact limits, let us know, but you know, you can't run a medical cannabis business out of your basement, right? So like, you know, if it's limiting to like maybe six plants or something like that, I don't know. I don't know what a medical cannabis patient needs, because I am not one. But you know, I, I would hope that research has been included in this decision, but I will admit, like you have to allow people to grow their own cancer. It has to be seen that, like, I can make my own beer whenever. You know, so that doesn't take that. Doesn't stop me from going to the store and buying white claws or craft beer whenever I want to. But you know, in terms of cannabis, like you can't just have a whole damn field in your basement. Excuse my language. Yes. So. The upshot of all the bills is that they would significantly limit the amount of marijuana. The caregiver can grow, reducing the number of cannabis plants from 72 to 24. So definitely a 66% cut there. And then, so two thirds of the market right now of cannabis in Michigan is unregulated. And so what that means is the majority of that product can be untested as quoted by. A local television station. What TV? So cancer for patients. Those with immunocompromised situations, getting access to safe product is really important.Some of this untested product has been found to contain mold, pesticides, Cola, salmonella. So if this is what the studies are showing and you know, obviously this is for the medical market Definitely you want a better product there so that, you know, the end user and customers have a better experience, aren't getting a bad product that in turn hurts their health and not helping their health.Yeah. Yeah. So I think, I mean, honestly, like I'm, I'm not overly bothered by it, but again, like I also don't claim to know what a medical cannabis patient needs. And so I hope that research has been taken into account. Good stuff, man. Aye, what else? You got some more, right? Yep. I got two more things. We're going all over the place today.So let's move on to some more federalisation news. So Schumer, Chuck Schumer wants to keep the big boys out of marrow out of the marijuana industry and says legalization. Bill is past. So Senate majority leader, Chuck Schumer wants to keep the big boys out of the marijuana industry in favor of creating opportunities for smaller operators.When canvas is federally legalized and he says his upcoming bill would accomplish just that. To me, I have, in my opinion, like it really is just a cop out. And, you know, the, the investment opportunity in this space drives a lot of these types of opinions. And I get that and it, it does obviously make a part of my opinion, but at the end of the day, it, it it's, in my opinion, it's, it's his job and the job of Republicans and Democrats to figure out how to create social equity opportunities, opportunities for small businesses, while also allowing companies that are in the space and have worked hard to be in this space right now. You know, so I think just limiting and saying you're, you're here to, to stop this from becoming too corporate. The only people in this industry that, that excites are the small businesses in California that haven't been able to compete. And I, I mean, to me, that's not good enough, but at the end of the day, I mean, I'm not a politician.I don't claim to have all the ins and sources there, but I don't know, man, I. I feel like you should not limit an industry that could be so beneficial to so many states. Absolutely. And I agree with you there, but I think if this bill does pass in the right way, definitely could be more inclusive or it makes the industry more inclusive.Right? So we have these smaller, smaller operators who are being noticed who are getting their fair share and. As well as these big operators who are coming into the space and now that it's federally illegal taking it advantage of all their initiatives and all of their you know, big, big practices that they've put into place over the years and finally grabbed the fruits of that.Yeah. Yeah. I mean, honestly, like I think you have, you have to do this for small businesses too, and I'm not saying due to. Not work for them. Obviously. I think you have to create a path for people to start their own businesses and you can't just let Ms. Sows be the only cannabis businesses out there that is not a sustainable industry, but you know, you can't limit the MSOC either.So, I mean, I think ultimately like it's, it's an extreme statement. But ideally there's more behind the bill, you know, like you're saying you know, and we'll all see how it comes out in the wash. And if Nancy Mesa get through gets there, even if Mitch McConnell lets Nancy Macy's get through. But we'll see, you will see.I I'm hoping for the best. I think we all know. Yeah, hope. Hope is the key word here. No legislation this year. All right. Let's end it on a nice light notes. W we're going to take it overseas to end, ended up or ended off, I know what you're going to say. Yes. Germany set to legalize marijuana nationwide.After major parties, reach agreement, party leaders in Germany. Germany's incoming government coalition have reached an agreement to legalize marijuana nationwide. The legalization legislation is expected to be introduced. Introduced during the upcoming legislative session, it will also provide broader drug harm reduction services and restrict advertising of tobacco and alcohol.Along with cannabis, as it stands, personal, personal possession of marijuana is decriminalized in Germany and there's a medical cannabis program in place, but this forthcoming proposal would seek to establish a regulated market for adult use. Nice. So far today Tilray up almost 3% to 2.7, 5%. And if this news doesn't spark some move until red be shocked surprised that this move didn't spark, or if this news didn't spark a lot of other moves, you know?Yeah. For me, the two big ones that I would look at are artillery. And cure leaf. So those two specifically public stock wise are I think the ones, it looks like what's like clearly is up this morning a little bit. So. Yeah, I mean, honestly, like those are the two stocks they're both up. Not as much as I would have assumed on this news, but I mean, I don't think anybody is directly in, but you can also look at other companies like flower Corp like perhaps heck so has some international, I think village farms is expanding into Northern Europe.So I mean, there's a lot of companies that are investible that can take part of the. No worries, Aaron. That was fun, bro. That's some good, you know, I hope we didn't get too political on you all today. Obviously we want the best for the industry and we want it to keep growing so we can all make that money on it.Y'all Yes. Fun always intended. Aaron, appreciate your brother. Happy Friday. Feel good Friday. Man we are long-winded. These are these Friday episodes, 20 minutes, but it feels so short and quick have fun on these. I have a lot of fun on these. So the time flies. Yeah. Thanks everybody for tuning in cannabis, our benzinga.com.If you have any suggestions, please rate and review us on your podcasting. Platform of choice. It helps us know what you all want to hear about. We do check those. We do read those. So please let us know. Outside of that, have a fantastic weekend. We will do this for the first three days of the week, next week. And then we will be off next Thursday and Friday. But we will see you again on Monday. There's Hey investors. Thanks so much for tuning in to Benzing. As cannabis daily stock picks and news podcast everyday pre-market. Once again, this is not financial advice. Please do your own research. We hope we bring you the best and most efficient news for your investing.Continue to find us on benzinga.com/cannabis, spending a.com/podcasts or on YouTube on Benzinga channel.Support this podcast at — https://redcircle.com/cannabis-daily/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Wherein we talk with Wolf Vollprecht about his work on Conda Forge and Mamba and the upcoming Packaging-Con (https://packaging-con.org/) event that he's organizing. The Packaging Con 2021: Call for Presentations is open until 1st September 2021,14:00 (UTC) if you'd like to speak: https://pretalx.com/packagingcon-2021/cfp Special Guest: Wolf Vollprecht.

HAPPY MARDI GRAS LOVERS! I sat down with the queen of my absolute dreams this week to discuss all things drag!! We look at the career highs and lows of Hannah Conda as she explains her relationship with this ever so fabulous sector of our entertainment industry! We discuss her plans and celebrations in the lead up to Sydney Mardi Gras 2021 and her partnership with Koala. STRAP IN KIDS! This ones a wild ride! ENJOY!! Instagram: @hannahcondaofficial

Howdy friends! Today I chat with the wonderful Hannah Conda about her upbringing, how she entered the world of drag and how she has grown as a person throughout her experiences! It was such a fun chat and I learnt a lot so I am excited to share it with you all today. Thanks for listening, Leila x FOLLOW: @hannahcondaofficial @allthingslifepodcast

如果喜欢我们的节目，欢迎通过爱发电打赏支持：https://afdian.net/@pythonhunter 本期嘉宾 立党 本期主播 laike9m laixintao 小白 时间轴 00:00:28 嘉宾介绍 00:01:26 立党开场快板 00:02:02 hedgehog-lab 介绍 00:03:43 创建 hedgehog-lab 的初衷 00:06:35 MATLAB 和 Python 在科学计算领域如何走向成功的 00:10:02 Python 和 NumPy 是谁成就了谁 00:10:53 NumPy 和 MATLAB 的简单对比以及 MATLAB 生态的相关讨论 00:13:31 主播们使用 MATLAB 的一些经历 00:16:15 为什么 Python 不是最适合初学者学习的编程语言 00:29:18 hedgehog-lab 的起源 00:30:58 聊一聊实现矩阵运算的原理 00:34:27 什么是符号计算 00:36:01 hedgehog-lab 中使用到的一些库和工具 00:39:50 hedgehog-lab 未来的规划 00:45:41 hedgehog-lab 的计算速度是和什么相关的 00:48:17 关于 hedgehog-lab 使用场景和部署方式的讨论 00:55:14 开源社区治理相关讨论 01:05:50 hedgehog-lab 未来形态的讨论 01:09:59 推荐环节 相关资料 00:01:48 hedgehog-lab 00:21:29 IBM SPSS software 00:21:29 Stata 00:21:29 SAS 00:27:53 Conda 00:29:52 Babel 00:30:17 operator overloading 百度百科 | 维基百科 00:33:23 Nerdamer 00:34:56 MATHEMATICA 00:35:08 simpy 00:36:08 plotly.js 00:37:00 CUDA 百度百科 | 维基百科 00:37:05 GPU.JS 00:38:24 TensorFlow.js 00:38:25 onnx.js 00:41:10 Reply 1988 00:50:34 Electron 00:52:05 PWA 01:10:24 AutoKeras 01:10:45 Nerdamer 01:11:13 请回答 1988 01:12:17 草东没有派对 01:12:53 shortuuid 01:14:12 typing-extensions 01:17:35 魁拔之十万火急 | 魁拔之大战元泱界 | 魁拔之战神崛起 01:17:35 镜心之歌

本期节目较长且信息量巨大，大家可以酌情分多次来听。 本期结尾有彩蛋，会是什么呢？大家敬请期待吧

In this episode of the Data Exchange I speak with David Talby, co-creator of Spark NLP, an open source, highly scalable, production grade natural language processing (NLP) library. Spark NLP has become one of the more popular NLP libraries and is available on PyPI, Conda, Maven, and Spark Packages. With recent advances in research in large-scale natural language models, there is strong interest in domain specific natural language applications. Besides their work on Spark NLP, David and his collaborators are building natural language models tuned specifically for healthcare applications.Our conversation spanned many topics, including:Spark NLP: its current status and some common and surprising use cases.Recent developments in NLP research and their implications for companies.Spark NLP for HealthcareDetailed show notes can be found on The Data Exchange web site.

Special thanks to Brownie, Joe, Micah, and Randy for their support and being awesome gamers.  We had a blast. In our first ever Patreon backer game, the poor fools willing to give us money return to the RPX Red Markets setting, the Conda. Johnny Mop and the Buckets have been tasked with rustling cattle from … Continue reading "Actual Play – Red Markets -Where's The Beef – Patreon Game 1" The post Actual Play – Red Markets -Where's The Beef – Patreon Game 1 appeared first on The Roleplaying Exchange.