Podcasts about digital assistants

In this episode, Merete, Joanna, and Sirte Pihlaja discuss the evolving landscape of customer experience (CX) and the significant role of artificial intelligence (AI) in shaping it. Sirte, known as the 'AI whisperer', shares insights on how AI can enhance customer and employee experiences, emphasizing the need for a human-centric approach. The conversation explores the concept of 'machine customers' and their implications for businesses, highlighting the necessity for companies to adapt their strategies to accommodate these digital entities. The episode also touches on the importance of creativity in CX and the ongoing efforts to grow the Customer Experience Professionals Association (CXPA) in Finland. In this conversation, Sirte Pihlaja discusses the transformative impact of AI on customer service, emphasizing the need for businesses to adapt to AI-driven customer interactions. She highlights the importance of creating effective digital assistants and leveraging AI for customer insights, while also addressing the role of AI in promoting inclusivity and accessibility. The discussion culminates in reflections on achievements in customer experience and the collaborative efforts to enhance human connections through technology.Read more about Sirte and her work on the following links: Website:www.shirute.fi/enYou can follow Sirte on social media:LinkedIn: https://www.linkedin.com/in/sirte I Follow me on LinkedInInstagram: https://www.instagram.com/sirteaceFacebook: https://www.facebook.com/shiruteInterested in AI, Agentic AI, Machine Customers, Digital Assistants and AI Twins?:www.machinecustomers.fi I www.koneasiakkaat.fi (Digital Assistants Experience Report)www.aiexperience.fi (The AI Experience Podcast)Talk with my AI Twin (Sirte AI)bit.ly/cx5book (The CX5 Book)CX and CEM Benchmark:www.shirute.fi/en/cemwww.cxmasterclass.fibit.ly/cx3book (The CX3 Book)LEGO Serious Play & Creativity:www.cxplay.fi I www.tosileikki.fibit.ly/cx2book (The CX2 Book)

Discover how Oracle APEX leverages OCI AI services to build smarter, more efficient applications. Hosts Lois Houston and Nikita Abraham interview APEX experts Chaitanya Koratamaddi, Apoorva Srinivas, and Toufiq Mohammed about how key services like OCI Vision, Oracle Digital Assistant, and Document Understanding integrate with Oracle APEX.   Packed with real-world examples, this episode highlights all the ways you can enhance your APEX apps.   Oracle APEX: Empowering Low Code Apps with AI: https://mylearn.oracle.com/ou/course/oracle-apex-empowering-low-code-apps-with-ai/146047/ Oracle University Learning Community: https://education.oracle.com/ou-community LinkedIn: https://www.linkedin.com/showcase/oracle-university/ X: https://x.com/Oracle_Edu   Special thanks to Arijit Ghosh, David Wright, Kris-Ann Nansen, Radhika Banka, 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! 00:25 Lois: Hello and welcome to the Oracle University Podcast. I'm Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services. Nikita: Hi everyone! Last week, we looked at how generative AI powers Oracle APEX and in today's episode, we're going to focus on integrating APEX with OCI AI Services. Lois: That's right, Niki. We're going to look at how you can use Oracle AI services like OCI Vision, Oracle Digital Assistant, Document Understanding, OCI Generative AI, and more to enhance your APEX apps. 01:03 Nikita: And to help us with it all, we've got three amazing experts with us, Chaitanya Koratamaddi, Director of Product Management at Oracle, and senior product managers, Apoorva Srinivas and Toufiq Mohammed. In today's episode, we'll go through each Oracle AI service and look at how it interacts with APEX. Apoorva, let's start with you. Can you explain what the OCI Vision service is? Apoorva: Oracle Cloud Infrastructure Vision is a serverless multi-tenant service accessible using the console or REST APIs. You can upload images to detect and classify objects in them. With prebuilt models available, developers can quickly build image recognition into their applications without machine learning expertise. OCI Vision service provides a fully managed model infrastructure. With complete integration with OCI Data Labeling, you can build custom models easily. OCI Vision service provides pretrained models-- Image Classification, Object Detection, Face Detection, and Text Recognition. You can build custom models for Image Classification and Object Detection. 02:24 Lois: Ok. What about its use cases? How can OCI Vision make APEX apps more powerful? Apoorva: Using OCI Vision, you can make images and videos discoverable and searchable in your APEX app.  You can use OCI Vision to detect and classify objects in the images. OCI Vision also highlights the objects using a red rectangular box. This comes in handy in use cases such as detecting vehicles that have violated the rules in traffic images. You can use OCI Vision to identify visual anomalies in your data. This is a very popular use case where you can detect anomalies in cancer X-ray images to detect cancer. These are some of the most popular use cases of using OCI Vision with your APEX app. But the possibilities are endless and you can use OCI Vision for any of your image analysis. 03:29 Nikita: Let's shift gears to Oracle Digital Assistant. Chaitanya, can you tell us what it's all about? Chaitanya: Oracle Digital Assistant is a low-code conversational AI platform that allows businesses to build and deploy AI assistants. It provides natural language understanding, automatic speech recognition, and text-to-speech capabilities to enable human-like interactions with customers and employees. Oracle Digital Assistant comes with prebuilt templates for you to get started.  04:00 Lois: What are its key features and benefits, Chaitanya? How does it enhance the user experience? Chaitanya: Oracle Digital Assistant provides conversational AI capabilities that include generative AI features, natural language understanding and ML, AI-powered voice, and analytics and insights. Integration with enterprise applications become easier with unified conversational experience, prebuilt chatbots for Oracle Cloud applications, and chatbot architecture frameworks. Oracle Digital Assistant provides advanced conversational design tools, conversational designer, dialogue and domain trainer, and native multilingual support. Oracle Digital Assistant is open, scalable, and secure. It provides multi-channel support, automated bot-to-agent transfer, and integrated authentication profile. 04:56 Nikita: And what about the architecture? What happens at the back end? Chaitanya: Developers assemble digital assistants from one or more skills. Skills can be based on prebuilt skills provided by Oracle or third parties, custom developed, or based on one of the many skill templates available. 05:16 Lois: Chaitanya, what exactly are “skills” within the Oracle Digital Assistant framework?  Chaitanya: Skills are individual chatbots that are designed to interact with users and fulfill specific type of tasks. Each skill helps a user complete a task through a combination of text messages and simple UI elements like select list. When a user request is submitted through a channel, the Digital Assistant routes the user's request to the most appropriate skill to satisfy the user's request. Skills can combine multilingual NLP deep learning engine, a powerful dialogflow engine, and integration components to connect to back-end systems.  Skills provide a modular way to build your chatbot functionality. Now users connect with a chatbot through channels such as Facebook, Microsoft Teams, or in our case, Oracle APEX chatbot, which is embedded into an APEX application. 06:21 Nikita: That's fascinating. So, what are some use cases of Oracle Digital Assistant in APEX apps? Chaitanya: Digital assistants streamline approval processes by collecting information, routing requests, and providing status updates. Digital assistants offer instant access to information and documentation, answering common questions and guiding users. Digital assistants assist sales teams by automating tasks, responding to inquiries, and guiding prospects through the sales funnel. Digital assistants facilitate procurement by managing orders, tracking deliveries, and handling supplier communication. Digital assistants simplify expense approvals by collecting reports, validating receipts, and routing them for managerial approval. Digital assistants manage inventory by tracking stock levels, reordering supplies, and providing real-time inventory updates. Digital assistants have become a common UX feature in any enterprise application. 07:28 Want to learn how to design stunning, responsive enterprise applications directly from your browser with minimal coding? The new Oracle APEX Developer Professional learning path and certification enables you to leverage AI-assisted development, including generative AI and Database 23ai, to build secure, scalable web and mobile applications with advanced AI-powered features. From now through May 15, 2025, we're waiving the certification exam fee (valued at $245). So, what are you waiting for? Visit mylearn.oracle.com to get started today. 08:09 Nikita: Welcome back! Thanks for that, Chaitanya. Toufiq, let's talk about the OCI Document Understanding service. What is it? Toufiq: Using this service, you can upload documents to extract text, tables, and other key data. This means the service can automatically identify and extract relevant information from various types of documents, such as invoices, receipts, contracts, etc. The service is serverless and multitenant, which means you don't need to manage any servers or infrastructure. You can access this service using the console, REST APIs, SDK, or CLI, giving you multiple ways to integrate. 08:55 Nikita: What do we use for APEX apps?  Toufiq: For APEX applications, we will be using REST APIs to integrate the service. Additionally, you can process individual files or batches of documents using the ProcessorJob API endpoint. This flexibility allows you to handle different volumes of documents efficiently, whether you need to process a single document or thousands at once. With these capabilities, the OCI Document Understanding service can significantly streamline your document processing tasks, saving time and reducing the potential for manual errors. 09:36 Lois: Ok.  What are the different types of models available? How do they cater to various business needs? Toufiq: Let us start with pre-trained models. These are ready-to-use models that come right out of the box, offering a range of functionalities. The available models are Optical Character Recognition (OCR) enables the service to extract text from documents, allowing you to digitize, scan the documents effortlessly. You can precisely extract text content from documents. Key-value extraction, useful in streamlining tasks like invoice processing. Table extraction can intelligently extract tabular data from documents. Document classification automatically categorizes documents based on their content. OCR PDF enables seamless extraction of text from PDF files. Now, what if your business needs go beyond these pre-trained models. That's where custom models come into play. You have the flexibility to train and build your own models on top of these foundational pre-trained models. Models available for training are key value extraction and document classification. 10:50 Nikita: What does the architecture look like for OCI Document Understanding? Toufiq: You can ingest or supply the input file in two different ways. You can upload the file to an OCI Object Storage location. And in your request, you can point the Document Understanding service to pick the file from this Object Storage location.  Alternatively, you can upload a file directly from your computer. Once the file is uploaded, the Document Understanding service can process the file and extract key information using the pre-trained models. You can also customize models to tailor the extraction to your data or use case. After processing the file, the Document Understanding service stores the results in JSON format in the Object Storage output bucket. Your Oracle APEX application can then read the JSON file from the Object Storage output location, parse the JSON, and store useful information at local table or display it on the screen to the end user. 11:52 Lois: And what about use cases? How are various industries using this service? Toufiq: In financial services, you can utilize Document Understanding to extract data from financial statements, classify and categorize transactions, identify and extract payment details, streamline tax document management. Under manufacturing, you can perform text extraction from shipping labels and bill of lading documents, extract data from production reports, identify and extract vendor details. In the healthcare industry, you can automatically process medical claims, extract patient information from forms, classify and categorize medical records, identify and extract diagnostic codes. This is not an exhaustive list, but provides insights into some industry-specific use cases for Document Understanding. 12:50 Nikita: Toufiq, let's switch to the big topic everyone's excited about—the OCI Generative AI Service. What exactly is it? Toufiq: OCI Generative AI is a fully managed service that provides a set of state of the art, customizable large language models that cover a wide range of use cases. It provides enterprise grade generative AI with data governance and security, which means only you have access to your data and custom-trained models. OCI Generative AI provides pre-trained out-of-the-box LLMs for text generation, summarization, and text embedding. OCI Generative AI also provides necessary tools and infrastructure to define models with your own business knowledge. 13:37 Lois: Generally speaking, how is OCI Generative AI useful?  Toufiq: It supports various large language models. New models available from Meta and Cohere include Llama2 developed by Meta, and Cohere's Command model, their flagship text generation model. Additionally, Cohere offers the Summarize model, which provides high-quality summaries, accurately capturing essential information from documents, and the Embed model, converting text to vector embeddings representation. OCI Generative AI also offers dedicated AI clusters, enabling you to host foundational models on private GPUs. It integrates LangChain and open-source framework for developing new interfaces for generative AI applications powered by language models. Moreover, OCI Generative AI facilitates generative AI operations, providing content moderation controls, zero downtime endpoint model swaps, and endpoint deactivation and activation capabilities. For each model endpoint, OCI Generative AI captures a series of analytics, including call statistics, tokens processed, and error counts. 14:58 Nikita: What about the architecture? How does it handle user input? Toufiq: Users can input natural language, input/output examples, and instructions. The LLM analyzes the text and can generate, summarize, transform, extract information, or classify text according to the user's request. The response is sent back to the user in the specified format, which can include raw text or formatting like bullets and numbering, etc. 15:30 Lois: Can you share some practical use cases for generative AI in APEX apps?  Toufiq: Some of the OCI generative AI use cases for your Oracle APEX apps include text summarization. Generative AI can quickly summarize lengthy documents such as articles, transcripts, doctor's notes, and internal documents. Businesses can utilize generative AI to draft marketing copy, emails, blog posts, and product descriptions efficiently. Generative AI-powered chatbots are capable of brainstorming, problem solving, and answering questions. With generative AI, content can be rewritten in different styles or languages. This is particularly useful for localization efforts and catering to diverse audience. Generative AI can classify intent in customer chat logs, support tickets, and more. This helps businesses understand customer needs better and provide tailored responses and solutions. By searching call transcripts, internal knowledge sources, Generative AI enables businesses to efficiently answer user queries. This enhances information retrieval and decision-making processes. 16:47 Lois: Before we let you go, can you explain what Select AI is? How is it different from the other AI services? Toufiq: Select AI is a feature of Autonomous Database. This is where Select AI differs from the other AI services. Be it OCI Vision, Document Understanding, or OCI Generative AI, these are all freely managed standalone services on Oracle Cloud, accessible via REST APIs. Whereas Select AI is a feature available in Autonomous Database. That means to use Select AI, you need Autonomous Database.  17:26 Nikita: And what can developers do with Select AI? Toufiq: Traditionally, SQL is the language used to query the data in the database. With Select AI, you can talk to the database and get insights from the data in the database using human language. At the very basic, what Select AI does is it generates SQL queries using natural language, like an NL2SQL capability.  17:52 Nikita: How does it actually do that? Toufiq: When a user asks a question, the first step Select AI does is look into the AI profile, which you, as a developer, define. The AI profile holds crucial information, such as table names, the LLM provider, and the credentials needed to authenticate with the LLM service. Next, Select AI constructs a prompt. This prompt includes information from the AI profile and the user's question.  Essentially, it's a packet of information containing everything the LLM service needs to generate SQL. The next step is generating SQL using LLM. The prompt prepared by Select AI is sent to the available LLM services via REST. Which LLM to use is configured in the AI profile. The supported providers are OpenAI, Cohere, Azure OpenAI, and OCI Generative AI. Once the SQL is generated by the LLM service, it is returned to the application. The app can then handle the SQL query in various ways, such as displaying the SQL results in a report format or as charts, etc.  19:05 Lois: This has been an incredible discussion! Thank you, Chaitanya, Apoorva, and Toufiq, for walking us through all of these amazing AI tools. If you're ready to dive deeper, visit mylearn.oracle.com and search for the Oracle APEX: Empowering Low Code Apps with AI course. You'll find step-by-step guides and demos for everything we covered today.  Nikita: Until next week, this is Nikita Abraham… Lois: And Lois Houston signing off! 19:31 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.  

What does the future hold for businesses striving for success? This episode explores the convergence of Cloud ERP, Artificial Intelligence, and sustainability, and how these elements are reshaping the business landscape. Peter Pluim discusses how businesses can harness data for sustainability insights, AI-driven automation, and process optimization. Discover how a connected enterprise can make informed choices within its supply chain, balancing price, delivery speed, and environmental impact. Learn how AI is transforming the user experience and driving the need for integrated suites that break down traditional application silos. Gain insights on navigating complex trade-offs, making better decisions through enhanced visibility, and empowering stakeholders with informed choices.

Banking digital assistants may be common now, but in 2017, Bank of America was one of the first to be thinking about how they make the firm's customer experience more powerful. The answer was an in-house build of a digital assistant that required the firm to hire PhDs in linguistics and build a collaboration structure that could facilitate teams from different departments. In 2024, BofA clients interacted with Erica 676 million times bringing its total interactions since its launch in 2018 to 2.5 billion. On the show today, Hari Gopalkrishnan, who leads Bank of America's Consumer, Business & Wealth Management Technology team, joins us to tell the tale of how the firm built its industry-leading digital assistant, Erica. Hari shares how the firm has gradually expanded Erica's remit beyond consumer banking to also include multiple lines of business and individual and corporate clients across the firm's global footprint. It's a dive into what it takes to push the boundaries in this industry, how the firm thought about development, testing, expansion, and how Erica's capabilities can be expanded with the recent innovations of Gen AI.

Stewart Alsop sat down with Nick Ludwig, the creator of Kibitz and lead developer at Hyperware, to talk about the evolution of AI-powered coding, the rise of agentic software development, and the security challenges that come with giving AI more autonomy. They explored the power of Claude MCP servers, the potential for AI to manage entire development workflows, and what it means to have swarms of digital agents handling tasks across business and personal life. If you're curious to dive deeper, check out Nick's work on Kibitz and Hyperware, and follow him on Twitter at @Nick1udwig (with a ‘1' instead of an ‘L').Check out this GPT we trained on the conversation!Timestamps00:00 Introduction to the Crazy Wisdom Podcast00:52 Nick Ludwig's Journey with Cloud MCP Servers04:17 The Evolution of Coding with AI07:23 Challenges and Solutions in AI-Assisted Coding17:53 Security Implications of AI Agents27:34 Containerization for Safe Agent Operations29:07 Cold Wallets and Agent Security29:55 Agents and Financial Transactions33:29 Integrating APIs with Agents36:43 Discovering and Using Libraries43:19 Understanding MCP Servers47:41 Future of Agents in Business and Personal Life54:29 Educational and Medical Revolutions with AI56:36 Conclusion and Contact InformationKey InsightsAI is shifting software development from writing code to managing intelligent agents. Nick Ludwig emphasized how modern AI tools, particularly MCP servers, are enabling developers to transition from manually coding to overseeing AI-driven development. The ultimate goal is for AI to handle the bulk of programming while developers focus on high-level problem-solving and system design.Agentic software is the next frontier of automation. The discussion highlighted how AI agents, especially those using MCP servers, are moving beyond simple chatbots to autonomous digital workers capable of executing complex, multi-step tasks. These agents will soon be able to operate independently for extended periods, executing high-level commands rather than requiring constant human oversight.Security remains a major challenge with AI-driven tools. One of the biggest risks with AI-powered automation is security, particularly regarding prompt injection attacks and unintended system modifications. Ludwig pointed out that giving AI access to command-line functions, file systems, and financial accounts requires careful sandboxing and permissions to prevent catastrophic errors or exploitation.Containerization will be critical for safe AI execution. Ludwig proposed that solutions like Docker and other containerization technologies can provide a secure environment where AI agents can operate freely without endangering core systems. By restricting AI's ability to modify critical files and limiting its spending permissions, businesses can safely integrate autonomous agents into their workflows.The future of AI is deeply tied to education. AI has the potential to revolutionize learning by providing real-time, personalized tutoring. Ludwig noted that LLMs have already changed how people learn to code, making complex programming more accessible to beginners. This concept can be extended to broader education, where AI-powered tutors could replace traditional classroom models with highly adaptive learning experiences.AI-driven businesses will operate at unprecedented efficiency. The conversation explored how companies will soon leverage AI agents to handle research, automate customer service, generate content, and even manage finances. Businesses that successfully integrate AI-powered workflows will have a significant competitive edge in speed, cost reduction, and adaptability.We are on the verge of an "intelligence explosion" in both AI and human capabilities. While some fear AI advancements will outpace human control, Ludwig argued that AI will also dramatically enhance human intelligence. By offloading cognitive burdens, AI will allow people to focus on creativity, strategy, and high-level decision-making, potentially leading to an era of rapid innovation and problem-solving across all industries.

An exploration into the intersection of artificial intelligence and manufacturing, where complex challenges meet innovative solutions. Expect insights that go beyond buzzwords to the heart of what drives efficiency and transformation in the manufacturing sector.

Roman Cyganov is the Founder and CEO of Antix, a company pushing the boundaries of Web3, AI, and gaming technologies. At the heart of Antix is Avagen, a proprietary technology that builds hyper-realistic AI-powered humans. Why you should listen Antix has a growing global client base, working with industry giants such as Warner Brothers, Porsche, Tencent, and HBO Entertainment. With over 20 clients, 20 completed projects, and 70+ cinematic experiences created, they have a proven ability to deliver innovative, scalable solutions. At the heart of Antix is Avagen, a proprietary technology that builds hyper-realistic AI-powered humans, fundamentally changing client engagement in the digital space. Antix's mission is to bridge the gap between real and virtual worlds through hyper-realistic digital humans.  Digital Assistants, Digital Influencers and Digital Twins are here. There are many implications for this. Antix is working to build a token economy and blockchain-proven ownership of a digital ID, this is the type of protection users need for this innovation to be a positive technology for all. Supporting links Stabull Finance Antix Andy on Twitter  Brave New Coin on Twitter Brave New Coin If you enjoyed the show please subscribe to the Crypto Conversation and give us a 5-star rating and a positive review in whatever podcast app you are using.

Make a Logo on Fiverr Last Updated on January 13, 2025 11:41 am by Jeffrey Powers Digital Assistants are starting to get a face, as I saw at CES 2025. Character Livehouse is a next-gen digital assistant doesn't just talk or display information—it entertains, dances, and engages with users through a customizable holographic interface. A […] The post Character Livehouse Brings Digital Assistants to Life from Code27 appeared first on Geekazine.

Pop quiz: What is an AI factory?

In this episode of SAP BTP Talk, December 2024, we will talk about how Joule – the AI copilot from SAP – truly understands your business. And when this intelligence is infused in SAP BTP Cockpit, how it transforms productivity and the way your teams work. Host Gaurav Dey interviews Kishore Vivekanandan, a product lead at SAP BTP, discussing Joule's role in making BTP administration more efficient and user-friendly. Our conversation delves into the advancements in AI, particularly interactive AI in business applications, with a focus on the new features of SAP BTP and Joule's integration. We also touch upon the learnings that the development team had from the beta program and how those insights have shaped the product roadmap.

Why You Can't-Miss This EpisodeDive into the fascinating future of customer interactions as Sirte Pihlaja discusses the rise of machine customers and digital assistants. Discover how this emerging technology will revolutionize customer experiences, reshape industries, and create a new era of business opportunities. This episode is your guide if you want to stay ahead in CX.About the GuestSirte Pihlaja is the CEO and Customer Experience Optimiser of Shirute, the first customer experience agency in Finland. She is also heading the activities of the Customer Experience Professionals Association (CXPA) in Finland. Sirte is an internationally known expert in her field, a trainer, designer, and strategist with over 25 years of experience in advising large domestic and international corporations and brands in different industries (e.g., Elisa, Arabia, Fiskars, Hackman, Iittala, Marimekko, Nokia, Nordea, Rovio, S-Group, TeliaSonera, Veikkaus, VR and Finnish Broadcasting Company).Sirte delivers creative solutions in customer experience research and experience design, customer experience management, data-driven business, the voice of customer and reputation management, and concretizing solutions through multi-channel service design.Relevant Linkshttps://linkedin.com/in/sirte https://www.shirute.fi/en https://www.machinecustomers.fi The Top 3 Key LearningsMachine Customers Are the Future: Autonomous digital assistants are evolving rapidly, offering businesses a unique opportunity to innovate and engage with a growing market segment.Empathy Meets Automation: While human connections remain essential, companies must also adapt to machine interactions that prioritize efficiency and convenience.Prepare for Hyper-Personalization: The rise of machine customers will demand tailored customer journeys and proactive, AI-driven solutions.Chapters00:00 Introduction and Guest Presentation 04:18 Exploring the Concept of Machine Customers 06:24 Practical Examples and Uses of Digital Assistants 09:12 Creating and Utilizing Digital Assistants 13:12 Challenges and Opportunities for Companies 23:26 Future of Machine Customers and AI 27:38 Conclusion and Contact InformationKeywordsmachine customers, digital assistants, customer experience, CX innovation, autonomous systems, generative AI, hyper-personalization, customer journeys, CX strategy, future of CX, AI in CX, empathy in CX, AI tools, proactive solutions, digital transformationFinal NoteThank you for tuning into the CX Goalkeeper Podcast! If you enjoyed this episode, make sure to subscribe, share, and leave a review. Stay connected for more insightful discussions:Podcast PageApple PodcastSpotifyYouTubeFeedback is always welcome—don't hesitate to reach out and share your thoughts!

Do you own a smart speaker, but the only thing you really use it for is to find out tomorrow's weather forecast? If so, today we're sharing three surprising ways your voice-activated digital assistant can be a wonderful help throughout your day.  To support more content like this, become an AARP member at aarp.org. And don't forget to subscribe for more tips and tricks to help make your life a little easier — and happier!

Welcome back to another episode of Multifamily Collective! Still here in San Diego at the Blueprint Conference, and wow—this event has been nothing short of world-class. From start to finish, every detail was meticulously crafted, leaving me inspired and proud to both speak and participate. Today, I'm discussing something that's truly shaking up our industry: AI-driven workflow automation and how it's shifting the landscape of property management. In this episode, I break down the exciting evolution we're seeing across PropTech platforms, especially as Generative AI (GAI) becomes a core part of operations. Imagine taking routine tasks off your plate entirely—not just automating them, but building workflows that handle data entry, compliance, and repetitive tasks for you. The tech is now sophisticated enough to prompt systems to “run recipes” that streamline everyday tasks, freeing up your team to focus on what really matters. And what's that, exactly? Relationships. It's time to shift from task completion to human connection. By letting technology take over the mundane, your team has more time to look people in the eye and build genuine connections—whether with residents, colleagues, or partners. This is more than a tech trend; it's about moving from transactional work to relational work—putting loyalty and community first. If you're excited about the future of multifamily and ready to leverage tech to give your team more time for the human side of work, hit that like button, subscribe, and let's keep building this community together. To find out more, please visit https://www.multifamilycollective.com --- Support this podcast: https://podcasters.spotify.com/pod/show/mike-brewer/support

This episode, "How My Projects Fit Together," is a follow-up to a previous post called "What I Am Doing & How It's Going". Here, Daniel Miessler addresses the most commonly asked questions: "I see all your projects, but what are they? How are they related?" He takes an individual look at his various projects (Substrate, Fabric, Telos, Daemon, and Human 3.0) and then how they work together to tackle big issues such as the lack of purpose and meaning in people's lives, preparing people for the impact of AI in society, and the need for holistic human development. For all the projects' links,visit: https://danielmiessler.com/p/how-my-projects-fit-together - Intro (00:00:00)- Identifying Major Problems (00:00:47)- Lack of Purpose and Meaning (00:01:50)- Impact of AI on Society (00:01:50)- Training for Full-Spectrum Individuals (00:03:02)- Security as a Core Focus (00:03:02)- Helios: Attack Surface Monitoring (00:04:11)- Daemon: Security Program Management (00:05:16)- Substrate: Enhancing Human Understanding (00:06:21)- Argument Components in Substrate (00:07:35)- AI and Argument Detection (00:10:59)- Fabric: Augmenting Humans with AI (00:15:26)- Fabric Patterns for Problem Solving (00:16:31)- Fabric Overview (00:19:36)- Telos Introduction (00:20:50)- Articulating the Mission (00:21:50)- Telos File Example (00:22:53)- Managing Personal Life with Telos (00:23:57)- AI and Purpose (00:26:10)- Daemon Introduction (00:28:21)- API Concept in Daily Life (00:29:28)- Digital Assistants and APIs (00:31:40)- Human Connection through Sharing (00:37:52)- Daemon Personal API Broadcast (00:39:53)- Human 30 Introduction (00:43:07)- Human 30 Philosophy (00:45:22)- Impact of AI on Work (00:48:47)- Human 30 Platform Overview (00:51:00)- Summary of Projects (00:54:03)- Vision of Future AI Integration (00:56:21)- Encouragement for Clarity and Purpose (00:57:39)- Encouragement for Purpose (00:59:47)- Articulating Your Work (01:00:46)Become a Member: https://danielmiessler.com/upgradeSee omnystudio.com/listener for privacy information.

On this episode of Crazy Wisdom, I, Stewart Alsop, sit down with Ben Ford and Michael Greenberg for a dynamic conversation. Ben is the founder of Mission Control Dev, and Michael is the founder of Third Brain, a company focused on automating business operations. We explore a variety of topics, including the real meaning of "artificial intelligence," how AI is impacting various industries, and whether we truly have AI today. Michael introduces his concept of "Third Brain," a digital layer of operations, while Ben reflects on his military background and how it shapes his current work. Both offer unique perspectives on where technology is headed, especially around the future of knowledge work, digital transformation, and the human element in an increasingly automated world. Check out the links to learn more about Ben's Mission Control Dev and Michael's Third Brain.Check out this GPT we trained on the conversation!Timestamps00:00 Introduction to the Crazy Wisdom Podcast00:15 Meet the Guests: Ben Ford and Michael Greenberg01:04 Exploring Third Brain and Mission Control03:05 Debating Artificial Intelligence05:24 The Role of AI in Business Operations08:54 Challenges in Digital Transformation16:59 Implementing AI and Digital Operations29:12 Exploring Puzzle App: A New Tool for Documentation30:14 The Power of Graphs in Computer Science32:14 Infinite Dimensions and String Theory32:57 AI Systems and Social Media Content33:31 Wardley Mapping and Business Processes35:26 The Future of AI and Job Security35:49 AI Whisperers Meetup and Conference43:35 The Role of Subject Matter Experts in AI44:13 The Impact of AI on Learning and Careers55:09 Challenges in Implementing AI Chatbots57:10 Closing Thoughts and Contact InformationKey InsightsThe distinction between AI and true intelligence: Ben and Michael both agree that current AI, particularly large language models (LLMs), lacks true intelligence. While these systems are highly capable of pattern recognition and can execute specific workflows efficiently, they fall short of human-like intelligence due to their inability to form cognitive loops, embody real-world understanding, or have agency. AI today excels at capacity but not in truly autonomous thinking.Digital transformation is continuous, not a one-time event: The idea that digital transformation has failed was discussed, with Ben and Michael pointing out that the problem lies in the perception that digital transformation has a start and end point. In reality, businesses are constantly transforming, and the process is more about ongoing adaptation than achieving a static, “transformed” state. Success in this realm requires persistent updates and improvements, especially in operational structure.AI as an enabler, not a replacement: Both guests emphasized that AI should be seen as a tool that augments human capability rather than replaces it. AI can significantly enhance the capacity of knowledge workers, enabling them to focus on more creative or strategic tasks by automating routine processes. However, human oversight and strategic input are still essential, especially when it comes to structuring data and providing context for AI systems to function effectively.The future of work involves "AI whisperers": Stewart introduces the idea of "AI whisperers" — people skilled in communicating with and directing AI systems to achieve specific outcomes. This requires a high level of linguistic and operational understanding, suggesting that those who can finesse AI's capabilities with precision will be in high demand in the future workforce. This shift may see creative, word-focused individuals becoming increasingly critical players in business operations.Structured data is crucial for effective AI deployment: A major challenge in deploying AI for businesses is the lack of well-structured data. Many organizations lack the documentation or system integration needed to effectively implement AI, meaning much of the initial work revolves around organizing data. Without this foundational step, attempts at AI deployment—such as customer service chatbots—are prone to failure, as the AI systems are only as good as the data they're fed.Graphs as the framework for business processes: Ben and Michael both highlight the importance of graphs in modern operations. Graphs, as a way to map out relationships between different elements of a system, are key to understanding and implementing digital operations. This concept allows for the visualization and optimization of workflows, helping businesses better navigate the complexities of modern digital ecosystems.AI is accelerating, and businesses need to keep up: One of the key takeaways from the episode is the rapid pace of AI advancement and its effect on businesses. Companies that fail to incorporate AI tools into their operations risk being left behind. Ben points out that the train has already left the station, and businesses need to quickly adapt by leveraging AI to streamline their processes and maintain competitiveness in an increasingly automated world.

Nick Allgaier is the Product Manager for Digital Assistants and Conversational AI at Lufthansa Group, and has taken the Lufthansa AI program from zero to 10 million interactions per year over chat, with more than 1 million interactions per year on voice. Nick joins me to share his learnings on scaling an AI practice to extraordinary heights. We cover Lufthansa's journey and where it all began, right through to how it's operating at scale today. You'll learn how Lufthansa is utilising generative AI and the specific use cases it's working well for, with some of the numbers to back it up. You hear about Nick's Golden Triangle for conversational AI use case selection and how missing any one of those crucial ingredients leaves you destined to fail. You'll also learn Nick's 5-step process that ensures customer experience excellence and the crucial role AI plays in that (and it's not what you think). Finally, you'll learn how to operate an AI service that spans multiple brands and languages.Lufthansa is Europe's biggest airline from a revenue generation perspective, second biggest in terms of numbers of passengers carried, and 4th in the world in terms of revenue. It houses Lufthansa, SWISS, Discover, Eurowings, Austrian, Brussels airlines and has over 60,000 staff. Getting an AI programme off the ground in an organisation of this size requires a skill and a solid approach. We'll cover all of that and more in this episode of VUX World.This episode is sponsored by Intel® Core Ultra processors and the Intel vPro® platform. Elevate your business with AI-powered PCs from Intel full of enhanced features like improved productivity, enhanced battery life, and integrated Arc graphics.​Supercharge your company today. Discover more: https://intel.ly/3A3Ziwq ​ Hosted on Acast. See acast.com/privacy for more information.

Send us a textAI Revolutionizing Customer Education: Insights from Kristine KukichIn this enlightening episode of the Customer Success Playbook podcast, hosts Roman Trebon and Kevin Metzger dive deep into the transformative impact of AI on customer education with guest expert Kristine Kukich, principal owner of The Training Sherpa.Kristine shares her extensive experience in implementing effective training programs and reveals how AI is making customer education more efficient, scalable, and personalized than ever before. The discussion covers five key areas where AI is making significant strides:Personalization of learning experiencesGamification for enhanced engagementStreamlined content developmentImproved assessment and certification processesAdvanced data analytics for actionable insightsListeners will gain valuable insights into:How AI is democratizing data analysis and content creationThe future of customer education, including the role of digital assistants and avatarsPractical AI tools for enhancing customer education initiativesThe balance between automated learning and premium, in-person training experiencesWhether you're a customer success professional, a training specialist, or a business leader interested in leveraging AI for educational purposes, this episode offers a wealth of knowledge and forward-thinking strategies.Please Like, Comment, Share and Subscribe. You can also find the CS Playbook Podcast:YouTube - @CustomerSuccessPlaybookPodcastTwitter - @CS_PlaybookYou can find Kevin at:Metzgerbusiness.com - Kevin's person web siteKevin Metzger on Linked In.You can find Roman at:Roman Trebon on Linked In.

This week's update discusses key trends in the mortgage industry, focusing on the importance of cybersecurity, the effectiveness of digital assistants, and the need for proactive customer service strategies.-----------------------------------------------------Allen Pollack, Tech ConsultantAllen Pollack, a Mortgage & Financial Services Technology Advisor, is a subject matter expert in the mortgage origination process along with software product management and software development.In today's financial services push to all things Digital, Allen has been helping lenders and financial services solution providers align their digital transformation and technology strategies by removing the human element of risk, and automating processes that drive efficiencies and margins into profits.Over the course of his career, Allen has co-created and developed technology business models that have birthed highly successful, innovative solutions and companies.Allen co-founded and served as CTO of New York Loan Exchange (NYLX), a loan product eligibility and pricing engine (PPE) that made an immediate impact on the industry, scaling the company quickly and forming partnerships with multiple mortgage and financial lending companies. In 2012, Allen was a co-founder of a merger between NYLX and Aklero Risk Analytics that created LoanLogics, A Mortgage Loan Quality and Performance Analytics company. Allen served as CTO where he continued to bring new and innovative product solutions to the market that made a significant impact to mortgage lenders that reduced risk, scaled business channels, and grew profits in a very competitive and highly regulated market.Allen is also is mortgage and finance technology contributor on a weekly live industry podcast, Lykken on Lending, and is launching a new podcast soon to be released, TechStack Radio, dedicated to technology and innovation in Financial Services.

August 12, 2024: George Pappas, CEO of Intraprise Health joins Drex for the news. They explore Paul Connelly's advice on connecting with boards, emphasizing the importance of clear communication and understanding the business perspective. How do CISOs balance technical details with business language to effectively convey cybersecurity needs to the board? The conversation transitions to the implications of recent cybersecurity insurance challenges, especially in the wake of incidents like the CrowdStrike update issue. How can organizations prepare for the unexpected disruptions caused by both malicious and non-malicious events? Finally, they touch on the transformative potential of AI in cybersecurity, pondering the future role of AI assistants in reducing manual effort and enhancing risk assessment. Can AI truly alleviate the burden on cybersecurity professionals while maintaining accuracy and reliability?Key Points:01:18 Connecting with Your Board of Directors09:34 Cyber Insurance and Risk Management19:33 AI and Digital Assistants in Cybersecurity23:45 Conclusion and Final ThoughtsNews articles:CrowdStrike losses may be biggest test yet of cybersecurity insurance risk warning from Warren BuffettWhy agents are the next frontier of generative AITrigger Warning: Cyber Policy Wordings to Impact Coverage for Tech OutageConnecting with your board of directorsThis Week Health SubscribeThis Week Health TwitterThis Week Health LinkedinAlex's Lemonade Stand: Foundation for Childhood Cancer Donate

Hello Brave Friends! Welcome to today's practical episode, #184. Our guest today is a dad!  Ryan Sheedy is a dad, a rare disease caregiver and a founder. He lives in Bentonville, Arkansas with his wife and three sons. In 2018, after 15 plus years in business development and fundraising, he paused his career to become a stay-at-home dad caregiver for his twin sons. One of his sons, Reynolds, was diagnosed with Costello syndrome in 2018. Since birth, Ryan has been Reynolds' primary caregiver. 100 plus days in the NICU, countless surgeries, and managing a 25 plus person care team. He and his son's rare journey and the countless families they have met along the way inspired him to create Mejo. As a caregiver, he knows, first hand, that being a caregiver is an everyday job, there's no days off. And Mejo is a web app built for caregivers to help save you time so that you can have more joy with those that you love and care for. I can't wait for you to meet Ryan. He is a great guy, great dad, entrepreneur, and he created something that all of us need! So please, run to your computers and look this up because it's going to save you a lot of time. Thanks for listening to my conversation with Ryan Sheedy. Find the my mejo website here.Contact Ryan Sheedy about my mejo here.Find our first book from We Are Brave Together here.Find our Becoming Brave Together book trailer here.Donate to our Mother's Day Fundraiser here.Find WABT 5K Fundraiser here. Brave Together is the podcast for We are Brave Together, a not-for-profit organization based in the USA. The heart of We Are Brave Together is to strengthen, encourage, inspire and validate all moms of children with disabilities and other needs in their unique journeys. JOIN the international community of We Are Brave Together here.Donate to our Retreats and Respite Scholarships here.Donate to keep this podcast going here.Can't get enough of the Brave Together Podcast?Follow our Instagram Page @wearebravetogether or on Facebook.Feel free to contact Jessica Patay via email: jpatay@wearebravetogether.orgIf you have any topic requests or if you would like to share a story, leave us a message here.Please leave a review and rating today! We thank you in advance!Disclaimer

OpenAI is in the hot seat. Scarlet Johansson thinks OpenAI might have used her voice without her permission. Former employees are compelled to sign non disparagement agreements or face losing their equity in the company. And much more! Plus, non AI stories too!See omnystudio.com/listener for privacy information.

In this episode, Tudor and the team discuss two main topics: the renaming of offenders to justice impacted individuals in Illinois and the budget cuts in Ann Arbor Public Schools in Michigan. They explore the implications of these decisions and the lack of accountability in the education system. The conversation touches on the importance of holding schools accountable, the role of unions, and the need for parents to be involved in their children's education. They also highlight the threat to democracy posed by the government education system and the lack of emphasis on teaching basic skills and critical thinking. The Tudor Dixon Podcast is part of the Clay Travis & Buck Sexton Podcast Network.  For more visit TudorDixonPodcast.comSee omnystudio.com/listener for privacy information.

In this episode, Tudor and the team discuss two main topics: the renaming of offenders to justice impacted individuals in Illinois and the budget cuts in Ann Arbor Public Schools in Michigan. They explore the implications of these decisions and the lack of accountability in the education system. The conversation touches on the importance of holding schools accountable, the role of unions, and the need for parents to be involved in their children's education. They also highlight the threat to democracy posed by the government education system and the lack of emphasis on teaching basic skills and critical thinking. The Tudor Dixon Podcast is part of the Clay Travis & Buck Sexton Podcast Network.  For more visit TudorDixonPodcast.comSee 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 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.

According to Adeel Sarwar, Chief Technology Officer at CareCloud, doctors spend at least 20% of their clinical work time on administration. In this video interview, Sarwar and A. Hadi Chaudhry, Chief Executive Officer and President at CareCloud, talk about their use of AI, and now generative AI, to relieve doctors of this burden and achieve more face-to-face time with patients. Learn more about CareCloud: https://www.carecloud.com/ Health IT Community: https://www.healthcareittoday.com/

Take a deep dive into the creation of an advanced digital assistant with Jeff McMillan and David Wu of Morgan Stanley. As the Head of AD&I, Morgan Stanley Wealth Management and the Head of Knowledge Management & Generative AI respectively, Jeff and David led the creation of an AI assistant for the global investment firm's advisors. Robb and Josh invite them in for a conversation about the technical work and strategic initiatives that enabled Morgan Stanley to create a knowledge base that's given them a massive leap forward with conversational AI.

This is our Wednesday episode, in which we dig into critical startup news to stay abreast of what founders and venture capitalists are working on.Today on the podcast, we got through the following:New data from Carta digging into startup compensation, and how it is changing;How one startup is profiting off death, but in a way that is actually great;Bear Robotics, and its killer new round for cute serving robots;New stuff from BlueSky (all about moderation and choosing one's own adventure) and Brave (getting a boost from the EU's DMA);And finally, some venture capital news that was a legit surprise.For episode transcripts and more, head to Equity's Simplecast website.Equity drops at 7 a.m. PT every Monday, Wednesday and Friday, so subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. TechCrunch also has a great show on crypto, a show that interviews founders and more! Credits: Equity is hosted by TechCrunch's Alex Wilhelm and Mary Ann Azevedo. We are produced by Theresa Loconsolo with editing by Kell. Bryce Durbin is our Illustrator. We'd also like to thank the audience development team and Henry Pickavet, who manages TechCrunch audio products.

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.

Summary:The main points of this episode are:Celebrating the 100th episode of cybercrimeology and reflecting on the podcast's journey over the past three years.Discussing the use of new technologies, such as AI, for analyzing and understanding the podcast's content.Analyzing the podcast's content using natural language processing and summarization techniques to identify recurring themes and research topics.Identifying common themes in the podcast, including abuse in relationships, privacy invasion, law enforcement in cybercrime, social engineering, and age-related factors in cybercrime.Discussing various research methodologies covered in the podcast, such as technographs, online experiments, and survey research.Highlighting the dedication of guests who share their time and research without any financial incentives.Answering questions about the process of creating each episode, including research, interviews, editing, and production.Discussing the volume of work represented by 99 episodes totaling over 5 hours of content and involving 96 guests.Reflecting on the impact of the podcast and its growth over the past three years, including achieving 100,000 downloads.Looking forward to the future of the podcast and the potential for new technologies to enhance its content and reach.About our guests:Alloy:https://platform.openai.com/docs/guides/text-to-speechvoicing generations fromChatGPThttps://openai.com/blog/chatgptPapers or resources mentioned in this episode:The BART model:https://huggingface.co/docs/transformers/model_doc/bartThe DistilBERT model:https://huggingface.co/docs/transformers/model_doc/distilbert Results:Which terms were spoken about the most and what was the sentiment around those ? NounOccurrencesFilesOccurredInSentimentScoreSumpeople25299492.60830581188202time11338379.5210649research13968079.49750900268553way10057473.79837167263031things12387372.45885318517685lot11177170.87118428945543data9034644.24124717712402kind6674443.9891608crime8854342.725725710392005cyber8054139.68457114696503cybercrime4813836.90566980838775thing3933635.59294366836548security5273130.89444762468338information4672928.87013864517212 Was there a change in the sentiment of the podcast after the end of  pandemic conditions, assuming that the pandemic ended at the end of Q3 2021? The model is given by:yi∼Normal(μi,σ)yi​∼Normal(μi​,σ)whereμi=β0+βafter_event⋅xiμi​=β0​+βafter_event​⋅xi​Here, the parameters are defined as follows:β0β0​: Intercept, with a Student's t-distribution prior with 3 degrees of freedom, a location parameter of 0.8, and a scale parameter of 2.5.βafter_eventβafter_event​: Coefficient for the predictor variable (after_event), with a flat prior.σσ: Standard deviation of the response variable, with a Student's t-distribution prior with 3 degrees of freedom, a location parameter of 0, and a scale parameter of 2.5.This provided the results as follows: Population-Level Effects:           Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESSIntercept       0.37      0.06     0.26     0.48 1.00     3884     2917after_event     0.39      0.08     0.23     0.54 1.00     3561     2976 Family Specific Parameters:     Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESSsigma     0.38      0.03     0.33     0.44 1.00     3608     2817Other:The model overlooked Mike Levi's contribution to the History series.  That is a bit unfair.  Where there were multiple guests, I did not include them all in the database, hence "no specific guest listed"  

What an exciting time to be alive. Using artificial intelligence for business has ushered us into a truly fascinating era of unprecedented productivity and efficiencies. Today, AI expert Kevin Surace of Appvance.ai joins A.J. to share his game-changing insights into AI capacities. He gives practical lessons about using automation to improve performance, choosing the right AI tools for your needs, and harnessing the power of AI to revolutionize your business.About Kevin Surace:Kevin Surace is a Chairman and CTO at Appvance, an AI expert, keynote speaker, and an award-winning CEO, CTO, and Innovator. He has been working in the Artificial Intelligence space since the 1990s and has much to say about AI's state, GPT models, and the impacts on your job and your life. He has been awarded almost 100 worldwide patents, including the core technology that would become Siri and other virtual assistants.  Futurist and Disruptive Innovation Keynote Speaker, Creator of the First Smartphone and Digital Assistant, and Innovator of the Decade. Kevin is a top innovation keynote speaker, CEO, and inventor of one of the world's first smartphones. Kevin has been named Inc. Magazine's Entrepreneur of the Year, CNBC's Innovator of the Decade, and inducted into RIT's Innovation Hall of Fame. While he has a deep technical background, he has been featured in over 15 TED and TEDx talks and is a high-energy, dynamic speaker and true entertainer who has energized hundreds of audiences to action.Key Insights: Automate your business for faster delivery. You can use large language models to automate various tasks in your business, such as emails, presentations, social media scheduling, etc., to save time and money. This ensures faster and more accurate delivery, improving operational efficiency and leaving more time for strategic tasks. Improve communication with AI. AI can simplify complex information and help you achieve more clarity by condensing lengthy reports or turning articles into briefs. You can use it to streamline communication and reduce misunderstandings, ultimately improving work productivity and professional relationships.   Double your productivity with AI. Using artificial intelligence for business is the ultimate productivity hack. Kevin says AI makes us 10 to 100 times more productive with everyday tasks. So, use it to boost your team's performance and ultimately achieve more with less time. Choose the right AI tools. Take the time to find what works for you, what brings value to your business, and what improves your team's productivity. This will ensure you get maximum value from the tools you use and not get distracted by every new one on the market. Futureproof your business. AI is transforming almost every industry. There's no hiding from it or denying its potential. Artificial intelligence is no longer a fun thing to have for businesses that want to thrive - it's what sets them apart from the competition. You either embrace it or risk extinction.  Kevin's best advice for entrepreneurs:“I think as an entrepreneur, the only thing we don't have is time because time is money. [...] Start using these accessible models that are now in English, and you might find five hours of your day come back to you.”Connect with Kevin:  LinkedIn Personal Website Resources Mentioned: Kevin's Ted Talk Crystal Knows ChatGPT Bard Follow Beyond 8 Figures: Linkedin Twitter Website

Time to unlock your finance team's digital potential! Join Lois Houston and Nikita Abraham, along with Sr. Principal ERP Learning Strategist David Barnacle, as they discuss the Procure to Pay process flow, an integral financial process that integrates purchasing with accounts payable activities.   They also talk about the Asset Acquisition to Retirement process flow, which includes all the main activities that occur during the life of an asset, right from acquiring it all the way to disposing it at the end of its life.   Oracle MyLearn: https://mylearn.oracle.com/ 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, Radhika Banka, Parvathy Narayan, 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: Hello and 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: Hi everyone. In our last episode, we looked at Invoice to Cash, which is the first business process within the Oracle Cloud Financials Business Process Model. Invoice to Cash refers to everything from the moment a receivable invoice is created until the customer's receipt is settled and reconciled with the bank statement. If you missed that episode, do go back and give it a listen. 01:01 Lois: Today,  David “Barney” Barnacle, our Sr. Principal ERP Learning Strategist is back on the podcast to tell us about the next two business processes, Procure to Pay and Asset Acquisition to Retirement. Nikita: Hi Barney! Thanks for being back with us. So, what is the Procure to Pay process? 01:20 Barney: Hi Niki. Hi Lois. Good to be here. Let's focus on Procure to Pay or P2P for short, which is an integral financial process within any organization. It integrates purchasing with accounts payables activities and involves a series of tasks. These could include placing a purchase requisition or a purchase order, receiving and inspecting the delivered goods or services, capturing the supplier invoices, which is the company's liability to the supplier, matching the unit quantity and price to the original PO, calculating the relevant taxes or withholding taxes, approving the charges for final payment by the company, and finally, recording the bank statement lines with all payments made to suppliers or employees. 02:04 Barney: Oracle Fusion Cloud: ERP's capacity to use cutting-edge technologies for effective operations is what distinguishes it from the competition. The true value is in the automation, which helps enterprises improve processes, increase efficiency, and get the latest insights and alerts.  Let me give you some examples within P2P. We have something called Intelligent Document Recognition or IDR for short, which is a fully integrated invoice recognition solution. As you know, many suppliers send payables invoices electronically via email. With Oracle's cloud solution, IDR extracts invoice information from the emailed documents to create invoices and then imports them directly into Payables. Another interesting feature is the ability to calculate the trip distance in mileage expense entry by using the Oracle Maps Cloud service. For mileage expense types, on the Oracle Maps page, you can enter the start location, subsequent stops, and the end location. It's that easy. 03:09 Lois: Oh wow, that's pretty cool. I remember having to track my miles manually many years ago. What a nice feature. So, is creating an invoice the beginning of the P2P process?  Barney: No, Lois. Invoicing is not the beginning but just one part of the larger parent P2P process. The P2P process can be broken into three key phases. These phases are set in a repeating loop and fine-tuned and improved with every cycle. The three phases are the Purchasing process, the Receiving process, and finally, the Payment process. 03:46 Barney: During the Purchasing process, purchase requisitions for goods and services are created and approved. Suppliers are evaluated and selected. And then, purchase orders are issued for the required goods and/or services. Next is the Receiving process, where goods and services are received. Receiving documents are then reviewed and logged for the goods. In the final Payment process, which includes the Invoice, Payment, and Reconciliation sub-processes, invoices are received and invoice processing is completed, recording the supplier's liability. Invoices are reconciled and cross-checked with the original purchase orders and goods receipts or receiving documents. This is called purchase order or receipt matching, and it ensures that the enterprises only pay for goods and services it has ordered and received. Errors are recorded and corrected, and approved invoices are paid, reducing the supplier's liability. Payments are then reconciled with bank statement lines. 04:47 Nikita: OK. So, there are multiple activities, like purchasing, receiving, and invoicing, which are part of the P2P process. But how do these activities flow with regard to the Oracle Fusion Cloud: ERP application?  Barney: The Procure to Pay process spans multiple departments within an organization. And in the Oracle application, it covers different modules like purchasing, payables, cash management, and general ledger. Demand generation for goods or services can originate in the Manufacturing departments based on planned or actual orders, or by internal employee orders for goods or services that the business requires.  05:23 Barney: This demand gets converted into requisitions within the Purchasing department. Everything from the creation all the way to the authorization of these requisitions is performed within the Purchasing department. Once the requests have been authorized, the buyers or procurement agents consolidate the requests and convert them into a purchasing document, like a purchase order. Next, the process of receiving goods or services against the purchasing document is typically carried out by the employees requesting those goods or services or by the staff at the receiving location. 05:54 Nikita: And a receiving location could be a warehouse, for example, right? So there is a purchasing department processing purchased orders and another receiving department recording the receipt of goods. Barney: Exactly, Niki. And once the goods are received and recorded, the transaction flows into the Payables department within the finance business function. Supplier Invoice to Payment, which comes within the finance business function, touches internal as well as external parties involved with an organization.  06:23 Barney: For example, when talking about the process of expense reimbursement, employees are considered internal parties. In this process, employees record and submit expenses incurred on behalf of the organization and are reimbursed for the authorized items. For an external party, the process of recording invoices against goods or services used by the organization and the subsequent process of making payment to clear these invoices is also a key part of the Procure to Pay process.  For example, organizations purchase assets like printers or furniture, which are recorded as part of the purchasing process. Oracle Assets is a fully integrated solution to track internal products and assets at internal or external sites, while providing the ability to capture financial transactions with back-office automation. 07:10 Barney: And then there is the Treasury department that some companies may call the Cash department, which, at periodic intervals, receives bank statements and reconciles the statement lines with payments made to suppliers. The key focus of the Treasury department is to determine the cash position and to assist in managing the cash forecasting process. These are just some activities of the Procure to Pay process that touch multiple departments within the business. 07:35 Lois: You mentioned expense reimbursement and making payments to external suppliers for goods received. How does this fit into the Oracle Financials Business Process Model?  Barney: As we discussed, P2P involves multiple processes spanning procurement to cash, specifically payables invoice to cash. Let me list out the processes that are aligned with Oracle Financials business processes as part of the P2P process. First, we have the Expense Report to Reimbursement process that deals with getting business expenses reimbursed for employees and contract workers, also known as contingency workers. 08:13 Barney: The Supplier Invoice to Payment process deals with recording liability for purchases made by the organization directly from external parties and paying for those purchases. The Capture Tax process deals with applying transactional tax or withholding taxes based on the information entered in an invoice and invoice line level, and legislative requirements. The Bank Transaction to Cash Position process deals with matching bank statement lines to payments made to suppliers. Accountants working in the Treasury department can prepare the expected cash position based on the expected receipts and payments within that specific period.  08:51 Lois: Each of the Oracle business processes you mentioned seem to be aligned with the general flow of activities in a typical organization. What are the advantages of having such a streamlined P2P process? Barney: A streamlined and automated Procure to Pay process helps organizations remain compliant with supplier-related contractual terms and legislative tax requirements. It also helps them reduce the risk of fraud with risk migration controls in place and automation within the process.  09:18 Barney: It results in better supplier management in terms of sourcing and evaluating suppliers, and monitoring and controlling supplier invoice aging, resulting in timely payments being made to suppliers. The ability to capture supplier invoices from multiple channels, including scanning and online submission by suppliers to enable batch processing of payments, results in cost reduction for an organization and saves hours that would have been spent manually processing invoices and payments. Most importantly, a streamlined Procure to Pay process provides the ability to capture data at each stage, which helps with future decision-making. 09:56 Nikita: What are the job roles associated with the Procure to Pay business process? Barney: There are a few key job roles in the P2P business process. There's the employee job role, which identifies the person as an employee who can create a requisition and an expense report. The Procurement Agent job role is responsible for transactional aspects of procurement processing. The Expense Audit job role reviews and audits expense reports daily to ensure compliance with the company's reimbursement policy. The Accounts Payable Specialist job role enters invoices, ensuring accuracy, uniqueness, and completeness, and matches invoices to the correct purchase orders or receipts, all while making sure that the invoices comply with company policy. The Accounts Payables Supervisor job role oversees the activities of Accounts Payable Specialists, initiates and manages payment runs, and resolves non-data entry holds. And finally, the Cash Manager job role protects and develops the company's liquid assets, maximizing their use and return to the organization. 10:58 Lois: For an organization to have an optimized Procure to Pay process, I'm sure they need to track certain key performance indicators, right?  Barney: Yes, and they do. Some of the KPIs that are tracked for the P2P process are Expenses vs. Budget, Invoice Payment Days, % Discount Taken, Time to Settlement, Time to Reconcile, and Payables Overdue Invoices. 11:20 Lois: Barney, earlier you spoke about how easy it is to raise expenses and use the Maps functionality. Are there other emerging technologies used by the ERP application in the Procure to Pay process? Barney: Yes Lois, Oracle Fusion Cloud: ERP uses the latest emerging technologies like artificial intelligence, digital assistants, and image scanning in different areas of the Procure to Pay process. Adaptive Intelligence models are used in the Payables module to calculate and recommend discounts for single payments. Intelligent Document Recognition is used to scan and automate the invoice creation process in Payables, incorporating the required reviews and approvals. Within the Expenses module, Digital Assistants are used to punch in expenses and submit them automatically. You can also click photos of receipts and process them to input the required expenses.  12:16 Working towards an Oracle Certification this year? Grab all the help you can get. Attend a cert prep live event in the Oracle University Learning Community. And once certified, don't forget to join our exclusive forum for Oracle certified users.  If you're already an Oracle MyLearn user, go to MyLearn to join the community. You will need to log in first. If you've not yet accessed Oracle MyLearn, visit mylearn.oracle.com and create an account to get started.  12:47 Nikita: Welcome back. Barney, you mentioned that Payables is one of the starting points to capture or track assets in the application. Can you help us understand how this is built in to Oracle Fusion Cloud? Barney: In the Oracle Financials Business Process Model, Asset Acquisition to Retirement is a key process that covers all the main activities that occur during the life of an asset, anything from acquiring it to disposing it at the end of its useful life. There are many things a business will need to do with assets. Capture asset acquisition, record financial transactions, track asset movement for reporting and regulatory purposes, and so on. We can manage these assets and simplify fixed asset accounting tasks with the help of Oracle Fusion Assets. It has the ability to record leased assets in line with the requirements of the two new accounting standards. 13:37 Barney: Oracle Assets integrates with other modules like Payables, Subledger Accounting, and Projects. You can add assets and cost adjustments directly into Assets from invoice information in Payables. The Create Mass Additions for Assets process sends valid invoice line distributions and associated discounts from Payables to the Mass Additions interface table in Assets. You can then review the mass addition lines in Assets and determine whether to create assets from them. 14:03 Nikita: So, what are the different stages in the Asset Acquisition to Retirement life cycle? I'm sure the first one has to be acquiring the asset. Barney: You're absolutely right there, Niki. The Asset Acquisition to Retirement life cycle starts with the Asset Acquisition stage. A business can acquire an asset through the Procure to Pay life cycle and record the asset in the asset register. An asset can be acquired by purchasing it, leasing it, constructing/developing it (i.e. by the use of Oracle Fusion Projects), or by mergers or acquisitions. And by acquiring assets, we mean capturing and recording the purchase of assets from all business locations. 14:42 Barney: The next stage is Monitoring and Tracking. Once an asset has been created and added to the asset register, you can perform various activities during the asset's life cycle. These activities could be changing its category or financial details, transferring assets, i.e. from locations, or running or changing depreciation. Any finally, we have Retirement. When you sell an asset, or an asset is lost, or the asset reaches the end of its useful life, you must remove it from the asset register. 15:14 Lois: And before we let you go for today, remind us – what job roles perform the functions related to this life cycle, Barney? Barney: There are two main job roles involved in this process. One is the Asset Accountant, the basic user who performs all functions in the asset management module. Then there's also the Asset Accounting Manager who has much of the same access as the asset accountant, along with extra access in terms of reporting and running accounting processes. 15:40 Nikita: I think we've discussed these two important Oracle business processes quite thoroughly. Thank you so much, Barney, for taking us through them.  Barney: Thanks for having me! Lois: Yes, thanks, Barney. This is a great introduction. Next week will be our final episode on the Oracle Financials Business Process Model, where we'll cover the Accounting Transformation and Budget to Report business processes. And don't forget to head over to mylearn.oracle.com to learn more about these processes and get certified. Until next time, this is Lois Houston… Nikita: And Nikita Abraham, signing off! 16:13 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.

Joe Rare likes to build businesses and help people find more time to spend with their family. How does he do it? Two words: Digital Assistants. In today's episode of the podcast, Matt and Joe talk about the passion project turned business Joe created and how people can outsource effectively for time and cost savings. Join the conversation to learn how to optimize your grind - Welcome back to the Get Better Everyday Podcast! Want to help the show? Sharing this episode with a friend or on social media is the number 1 way to help us grow. Leaving 5-star reviews on Spotify and Apple Podcasts are also great ways to give back. Visit mattgouge.com to learn more! --- Send in a voice message: https://podcasters.spotify.com/pod/show/matt-gouge/message

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Chris Were is the Co-Founder and CEO of Verida, a network of decentralized data storage, messaging, and single sign-on solutions that enable interoperable ownership of personal data for Web3. In this episode of Secure Talk, Chris talks about self-sovereign identities, zero-knowledge credentials, and crypto wallets, and explains how personal will unlock AI digital assistants. Verida https://www.verida.io/

From the WEDI Archives: Dr. Steve Waldren, Vice President and Chief Medical Informatics Officer of the American Academy of Family Physicians discusses how AAFP's Innovation Lab has embraced the power of artificial intelligence to aid their physicians with numerous functions and processes. 

In this episode:

Artificial intelligence (AI) has been an emerging hot topic over the last several months with the rise of Open AI's ChatGPT, Microsoft's integration of ChatGPT technology into its Bing search engine, and Google's announcement of its own chatbot, known as Bard. And while there are concerns about the more “general AI” technologies built to improve neural network capabilities so they are comparable to those of humans, health care systems are able to expand their services by leveraging the more familiar “narrow” or single-task AI tools, such as virtual chat assistance. Deploying this kind of AI technology can lead to an enhanced self-service experience for patients. We welcome Matt White, Director of Innovation at Contra Costa Health Services (CCHS), who shares how they've begun to thoughtfully integrate AI technology in order to better understand their patient engagement, with the ultimate aim to provide a consistent experience across all digital channels.Learn more about the people, places, and ideas in this episode: Matt White, Director of Innovation at Contra Costa County Health ServicesHyro.aiTechnology Hub, a CCI program that helps organizations vet, pilot, evaluate, and spread innovative digital health solutions targeting Medicaid markets and historically underinvested communities

You might read this title and think, what? What in the world are they talking about? What we are talking about are things that many of us will be using in our daily lives? Do you use Siri or Alexa? Do you have apps on your phone that are tailored to you and can help you out in a virtual way? If you use any of these things, you use virtual assistants. But what you might not have thought about is how they actually work and how they do (or do not) respond to more subjective things like feelings or an inability to quickly process questions being asked by the virtual assistant. Our next guest in our "What's New With" series studies all of these things and is making a significant impact on the way AI technologies are merging with user experiences. Dr. Miriam Sweeney is an associate professor in the School of Library and Information Studies, part of the College of Communication and Information Sciences. She is a renowned scholar in this area and is taking intentional steps to look beyond the service and better understand how user experiences can be improved. This is a fun one! Don't miss it!

In a unique technology demonstration, Lockheed Martin has partnered with Amazon and Cisco to bring the Alexa digital assistant and Webex video collaboration aboard Orion.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Peter Voss, Founder, CEO, and Chief Scientist at Aigo.ai, talks about making software intelligent. In a world of Siris and Alexas, most of us are familiar with the power and limitations of the first and second waves of AI. Now that we're in the third wave, chatbots have evolved beyond simple rule-based interactions and are now able to make judgments and learn, resulting in more human-like interactions. Today, Peter discusses chatbots revolutionizing enterprise digital assistants. Show NotesConnect With:Peter Voss: Website // LinkedInThe MarTech Podcast: Email // Newsletter // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

If you're in banking and you haven't been seriously considering your conversational AI strategy, then where have you been?Yes, it's early, but the banking industry is one of the stand-out industries where conversational AI can add immeasurable benefit to your business operations and customer experience. One person who's been through the end-to-end journey of formulating the strategy, building the team and deploying the solution is Bill Hawks. Bill is Digital Customer Experience Manager - Conversational AI & Virtual Client Service at Citizens Bank, where he's leading the CX digital strategy. Prior to that, Bill was Sr. Digital Product Manager at Truist Bank, where he led the conversational AI strategy, team and solutions. Bill joins us to share his lessons in how you can create an effective digital assistant for banking, as well as learnings that'll apply to any business leader considering their transformation strategy and how CAI can play a role.Join our next webinar, conversational commerce: how AI-powered digital workers can boost sales: Find out more: https://vux.world/conversational-commerce-how-ai-powered-digital-workers-can-boost-sales/ Hosted on Acast. See acast.com/privacy for more information.

AI-based digital assistants are great tools that provide opportunities to foster collaboration and enhance productivity in today's workplace. And this is where Oracle Digital Assistant (ODA) comes in. Join us on Cloud HCM Talk Radio to hear Sunil Kashyap, Oracle HCM Cloud Services Director, talk about empowering the Employee Experience using Oracle HCM Digital Assistant and discuss what's new with HCM skills and how they can help.

What do Siri, Alexa, and Google Assistant have in common? They're all girlies! This week Ione and Halima are exploring gender in the world of technology and artificial intelligence. Is the fact all of our 'virtual assistants' women sexist? Does it reinforce backdated gender roles? Or are we other thinking it? Ione and Halima break it down, looking at the research and history of female voices in the virtual world.Order Ione's book, Poor Little Sick Girls, here!Want to support the podcast? If you're a brand or organisation that could help us continue the show, Please fill in this form. Can't wait to hear from you!We'd love to know what you think about our podcast. Fill out this survey here to have your say

Most guests on How I Work will tell you to turn off your phone if you want to get work done. They'll probably tell you to leave it out of the bedroom when it's time to sleep, and to keep it out of reach when you're meant to be spending quality time with friends and family.  It's easy to forget sometimes just how useful that little super computer in your pocket can be - and that applies to life admin, too! Life Admin Hacks authors Mia Northrop and Dinah Rowe-Roberts put me onto the untapped power of Siri, and I've never looked back. And now they're teaching you how to use it, too.  If you've never used Siri for anything other than a Google search while your hands are full, you're missing out on an on-demand, high-powered digital assistant. From reminders to calendar updates, Mia and Dinah share how to use Siri to supercharge your life admin.  Connect with Mia and Dinah on their website and pick up a copy of Life Admin Hacks You can find the full interview here: Get professional about your personal life with Life Admin legends Mia Northrop and Dinah Rowe-Roberts *** Pre-order your copy of Time Wise at amantha.com Connect with me on the socials: Linkedin Twitter Instagram    If you're looking for more tips to improve the way you work, I write a fortnightly newsletter that contains three cool things I have discovered that help me work better, which range from interesting research findings through to gadgets I am loving. You can sign up for that at http://howiwork.co Visit https://www.amantha.com/podcast for full show notes from all episodes. Get in touch at amantha@inventium.com.au   CREDITS Produced by Inventium Host: Amantha Imber Sound Engineer: Martin Imber

Most guests on How I Work will tell you to turn off your phone if you want to get work done. They'll probably tell you to leave it out of the bedroom when it's time to sleep, and to keep it out of reach when you're meant to be spending quality time with friends and family. It's easy to forget sometimes just how useful that little super computer in your pocket can be - and that applies to life admin, too! Life Admin Hacks authors Mia Northrop and Dinah Rowe-Roberts put me onto the untapped power of Siri, and I've never looked back. And now they're teaching you how to use it, too. If you've never used Siri for anything other than a Google search while your hands are full, you're missing out on an on-demand, high-powered digital assistant. From reminders to calendar updates, Mia and Dinah share how to use Siri to supercharge your life admin. Connect with Mia and Dinah on their website and pick up a copy of Life Admin HacksYou can find the full interview here: Get professional about your personal life with Life Admin legends Mia Northrop and Dinah Rowe-Roberts***Pre-order your copy of Time Wise at amantha.comConnect with me on the socials:LinkedinTwitterInstagram  If you're looking for more tips to improve the way you work, I write a fortnightly newsletter that contains three cool things I have discovered that help me work better, which range from interesting research findings through to gadgets I am loving. You can sign up for that at http://howiwork.coVisit https://www.amantha.com/podcast for full show notes from all episodes.Get in touch at amantha@inventium.com.au CREDITSProduced by InventiumHost: Amantha ImberSound Engineer: Martin ImberSee omnystudio.com/listener for privacy information.

When humans interact, they don't just pass information from one to the other; there's always some relational element, with the participants responding to each other's emotional cues. Professor Cynthia Breazeal, MIT's new Dean of Digital Learning, believes it's possible to design this element into human-computer interactions as well. She foresees a day when AI won't merely perform practical tasks for us, but also will provide us with companionship, emotional comfort, and even mental health support. But a future of closer human-AI collaborative relationships doesn't only require technological development—it also requires us to learn what AI is capable of and how to interact with it in a more informed way. To further this goal, Professor Breazeal leads the Responsible AI for Social Empowerment and Education (RAISE) initiative at MIT, which runs an annual “Day of AI” program to promote better understanding of AI in the next generation of technology users and developers. In this episode, she describes those projects as well as her work developing the groundbreaking social robots Kismet and Jibo, prototypes of what she calls “warm tech”—AI-enabled devices designed to be engaging, expressive, and personal. Relevant Resources:Day of AIRAISE (Responsible AI for Social Empowerment and Education)MIT OpenCourseWareThe OCW Educator PortalShare your teaching insightsProfessor Breazeal's faculty pageProfessor Breazeal named Dean of Digital LearningProfessor Breazeal introduces Jibo (YouTube video)The Rise of Personal Robotics (TED talk by Professor Breazeal)Music in this episode by Blue Dot Sessions Connect with UsIf you have a suggestion for a new episode or have used OCW to change your life or those of others, tell us your story. We'd love to hear from you! Call us @ 617-715-2517On our siteOn FacebookOn TwitterOn Instagram Stay CurrentSubscribe to the free monthly "MIT OpenCourseWare Update" e-newsletter. Support OCWIf you like Chalk Radio and OpenCourseWare, donate to help keep these programs going! CreditsSarah Hansen, host and producer Brett Paci, producer  Dave Lishansky, producer Nidhi Shastri and Aubrey Calloway, scriptwriters Show notes by Peter Chipman

Today is the third episode of this five-part series being published every day this week on achieving ROI with early AI projects. We've heard from the Head of the AI Center of Excellence at Intel and the Head of Insure AI at Munich Re, and today, we speak with the VP of Engineering for Oracle's Digital Assistant, Raefer Gabriel. Raefer was a previous guest on the show, and he's also worked on Amazon, including their Alexa platform, and had a startup before then. In this episode, we speak from his perspective on how we can achieve that early AI ROI. He also details how you can diagnose the data assets required to meet a specific goal to determine if your data would be a good fit and start with more modest projects on the crawl, walk, run scale. Be sure to tune in to the rest of the series to gain valuable insights and advice from enterprise leaders on achieving ROI with early AI projects.