This monthly podcast tells the stories and testimonies of the broken children who arrive at the orphanage called "Casa de mi Padre" (My Father's House) in the mountains of Santa Cruz del Quiche. Join us and hear the great testimonies of the work God is doing every month here! And Join us in praising God for his faithfulness and all that He continues to do here! To give just go to: https://secure.myvanco.com/L-Z8EN/campaign/C-13DDC
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Welcome to DataFramed, a weekly podcast exploring how artificial intelligence and data are changing the world around us. On this show, we invite data & AI leaders at the forefront of the data revolution to share their insights and experiences into how they lead the charge in this era of AI. Whether you're a beginner looking to gain insights into a career in data & AI, a practitioner needing to stay up-to-date on the latest tools and trends, or a leader looking to transform how your organizat ...
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#242 Data Storytelling for Kids with Cole Nussbaumer Knaflic, Founder and CEO of Storytelling with Data
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We’ve all met someone with a limiting belief, someone who describes their relationship with data as: “I’m not a data person” or “I can’t tell a data story.” Oftentimes, this mindset starts in childhood. Data storytelling is an incredible vehicle to challenge and reshape these beliefs early on. Imagine if kids could develop the skills to ask the rig…
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#241 Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AI
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Lot’s of AI use-cases can start with big ideas and exciting possibilities, but turning those ideas into real results is where the challenge lies. How do you take a powerful model and make it work effectively in a specific business context? What steps are necessary to fine-tune and optimize your AI tools to deliver both performance and cost efficien…
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#240 Generative AI in the Enterprise with Steve Holden, Senior Vice President and Head of Single-Family Analytics at Fannie Mae
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The rapid rise of generative AI is changing how businesses operate, but with this change comes new challenges. How do you navigate the balance between innovation and risk, especially in a regulated industry? As organizations race to adopt AI, it’s crucial to ensure that these technologies are not only transformative but also responsible. What steps…
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#239 New Models for Digital Transformation with Alison McCauley Chief Advocacy Officer at Think with AI & Founder of Unblocked Future
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The pressure to innovate with AI is immense. There is seemingly a race against the clock for organizations to incorporate AI into their product offering, aside from continual digital transformation. As the speed of AI development accelerates, many organizations struggle to keep up, facing challenges from data readiness to changing traditional busin…
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#238 Data & AI for Improving Patient Outcomes with Terry Myerson, CEO at Truveta
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One of the prerequisites for being able to do great data analyses is that the data is well structured and clean and high quality. For individual projects, this is often annoying to get right. On a corporate level, it’s often a huge blocker to productivity. And then there’s healthcare data. When you consider all the healthcare records across the USA…
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#237 Guardrails for the Future of AI with Viktor Mayer-Schönberger, Professor of Internet Governance and Regulation at the University of Oxford
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Guardrails are not something we actively use in our day-to-day lives, they’re in place to keep us safe when we lack the control needed to keep us on course, and for that, they are essential. Navigating the complexities of decision-making in AI and data can be challenging, especially on a global scale when many are searching for any sort of competit…
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#236 Optimizing Sales Using AI with Ellie Fields, CPEO at Salesloft
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Doing sales better is perhaps the most direct route to making more revenue, so it should be a priority for every business. B2B sales is often very complex, with a mix of emails and video calls and prospects interacting with your website and social content. And you often have multiple people making decisions about a purchase. All this generates a ma…
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#235 Developing Generative AI Applications with Dmitry Shapiro, CEO of MindStudio
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One of the big use cases of generative AI is having small applications to solve specific tasks. These are known as AI agents or AI assistants. Since they’re small and narrow in scope, you probably want to create and use lots of them, which means you need to be able to create them cheaply and easily. I’m curious as to how you go about doing this fro…
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#234 High Performance Generative AI Applications with Ram Sriharsha, CTO at Pinecone
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Perhaps the biggest complaint about generative AI is hallucination. If the text you want to generate involves facts, for example, a chatbot that answers questions, then hallucination is a problem. The solution to this is to make use of a technique called retrieval augmented generation, where you store facts in a vector database and retrieve the mos…
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#233 Generative AI at EY with John Thompson, Head of AI at EY
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By now, many of us are convinced that generative AI chatbots like ChatGPT are useful at work. However, many executives are rightfully worried about the risks from having business and customer conversations recorded by AI chatbot platforms. Some privacy and security-conscious organizations are going so far as to block these AI platforms completely. …
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#232 How are Businesses Really Using AI? With Tathagat Varma, Global TechOps Leader at Walmart Global Tech
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There’s been a lot of pressure to add AI to almost every digital tool and service recently, and two years into the AI hype cycle, we’re seeing two types of problems. The first is organizations that haven’t done much yet with AI because they don’t know where to start. The second is organizations that rushed into AI and failed because they didn’t kno…
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#231 Manage Your Data Better with Shinji Kim, CEO at Select Star
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One of the most annoying conversations about data that happens far too often is: “Can you do an analysis and answer this business problem for me?” “Sure, where’s the data?” “I don’t know. Probably in one of our databases.” At this point more time is spent hunting for data than actually analyzing it. Rather than grumbling about it, it would obviousl…
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#230 Scaling Experimentation at American Express with Amit Mondal, VP & Head of Digital Analytics & Experimentation at American Express
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One of the best applications of data science is that it allows experimentation within any organization at scale. The ability to test a new checkout feature, the color of a button, and analyze whether that improves customer experiences can be truly magical when done correctly. However, doing this at scale means that the entire organization needs to …
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#229 Inside Meta's Biggest and Best Open-Source AI Model Yet with Thomas Scialom, Co-Creator of Llama3
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Meta has been at the absolute edge of the open-source AI ecosystem, and with the recent release of Llama 3.1, they have officially created the largest open-source model to date. So, what's the secret behind the performance gains of Llama 3.1? What will the future of open-source AI look like? Thomas Scialom is a Senior Staff Research Scientist (LLMs…
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#228 Are Spreadsheets Still Relevant For Data Analysis? with Jordan Goldmeier, Author of Data Smart
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Excel often gets unfair criticism from data practitioners, many of us will remember a time when Excel was looked down upon—why would anyone use Excel when we have powerful tools like Python, R, SQL, or BI tools? However, like it or not, Excel is here to stay, and there’s a meme, bordering on reality, that Excel is carrying a large chunk of the worl…
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#227 DataFramed x Analytics On Fire: Riding the AI Hype Cycle with Mico Yuk, Co-Founder at Data Storytelling Academy
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This special episode of DataFramed was made in collaboration with Analytics on Fire! Nowadays, the hype around generative AI is only the tip of the iceberg. There are so many ideas being touted as the next big thing that it’s difficult to keep up. More importantly, it’s challenging to discern which ideas will become the next ChatGPT and which will …
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#226 Creating Custom LLMs with Vincent Granville, Founder, CEO & Chief Al Scientist at GenAltechLab.com
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Despite GPT, Claude, Gemini, LLama and the other host of LLMs that we have access to, a variety of organizations are still exploring their options when it comes to custom LLMs. Logging in to ChatGPT is easy enough, and so is creating a 'custom' openAI GPT, but what does it take to create a truly custom LLM? When and why might this be useful, and wi…
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Feeling Down But Looking Up, Faces with Braces, Ashley's Health, & Some New Children
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Support the Show.بقلم Cole McCauley
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#225 The Full Stack Data Scientist with Savin Goyal, Co-Founder & CTO at Outerbounds
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The role of the data scientist is changing. Some organizations are splitting the role into more narrowly focused jobs, while others are broadening it. The latter approach, known as the Full Stack Data Scientist, is derived from the concept of a full stack software engineer, with this role often including software engineering tasks. In particular, o…
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#224 What History Tells Us About the Future of AI with Verity Harding, Author of AI Needs You
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Conversations about the future of AI tend to be rather divisive, with opinions ranging from artificial superintelligence arriving to save the world, or to eradicate humanity. There's a sense that the latter is undesirable and that something ought to be done to prevent it. In order to get from that vague feeling to having steps that are practical in…
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#223 [Radar Recap] Charting the Path: What the Future Holds for Generative AI
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Generative AI is here to stay, fundamentally altering our relationship with technology. But what does its future hold? In this session, Tom Tunguz, General Partner at Theory Ventures, Edo Liberty, CEO at Pinecone, and Nick Elprin, CEO at Domino Data Lab, explore how generative AI tools & technologies will evolve in the months and years to come. The…
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#222 [Radar Recap] Scaling Data Quality in the Age of Generative AI
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Generative AI's transformative power underscores the critical need for high-quality data. In this session, Barr Moses, CEO of Monte Carlo Data, Prukalpa Sankar, Cofounder at Atlan, and George Fraser, CEO at Fivetran, discuss the nuances of scaling data quality for generative AI applications, highlighting the unique challenges and considerations tha…
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#221 [Radar Recap] The Future of Programming: Accelerating Coding Workflows with LLMs
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From data science to software engineering, Large Language Models (LLMs) have emerged as pivotal tools in shaping the future of programming. In this session, Michele Catasta, VP of AI at Replit, Jordan Tigani, CEO at Motherduck, and Ryan J. Salva, VP of Product at GitHub, will explore practical applications of LLMs in coding workflows, how to best a…
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#220 [Radar Recap] Building Tomorrow's Workforce, Today: Scaling Internal AI Academies
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As AI continues to be a critical driver of innovation and competitive advantage, the imperative for organizations to upskill their workforce in this domain has never been more pressing. In this session, Mike Baylor, Vice President & CDAO at Lockheed Martin, Carolann Diskin, Senior Technical Program Manager at Dropbox, and Giorleny Altamirano Rayo, …
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#219 Building a Data Platform that Drives Value with Shuang Li, Group Product Manager at Box
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Whether big or small, one of the biggest challenges organizations face when they want to work with data effectively is often lack of access to it. This is where building a data platform comes in. But building a data platform is no easy feat. It's not just about centralizing data in the data warehouse, it’s also about making sure that data is action…
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