Daniil Shvets, CEO and co-founder of ASAO DS: Data & AI Consulting Boutique, previously led various companies' Data Science and Product teams. Daniil sat down with Yuliia and Scott to share his opinion on Data Science being a business department with appropriate data skills rather than an IT department. He explained why having 54 ML models in one of the largest retailers in the USA is the wrong approach. Daniil also shared his views on the biggest challenges in perceiving Data Science's role. We also touched on AI and the consultancy business while Scott made all possible relationship analogies. :)Daniil's Linkedin: https://www.linkedin.com/in/daniilshvets/

Former co-host Julia Schottenstein returns to the show to go deep into the world of LLMs. Julia joined LangChain as an early employee, in Tristan's words, to "Basically solve all of the problems that aren't specifically in product and engineering." LangChain has become one of, if not the primary frameworks for developing applications using large language models. There are over a million developers using LangChain today, building everything from prototypes to production AI applications.

Welcome back to the podcast! The host, Mukundan Sankar, is an experienced data professional and AI researcher. This episode will discuss Retrieval Augmented Generation (RAG) and how it's transforming our relationship with information.23 The Problem of Information Overload: We are constantly bombarded with information, making it challenging to find what truly matters. Traditional AI models and search engines can provide inaccurate, outdated information, or even fabricate information (AI hallucination). What is RAG? RAG is an AI model combining retrieval and generation, offering the best of both worlds. Retrieval: Like a super-powered search engine, it searches vast data sources (documents, articles, reports) for the most relevant information based on the user's query. Generation: Takes the retrieved data and summarizes it clearly, concisely, and engagingly. How RAG Differs from Traditional Methods: RAG goes beyond simple keyword matching; it seeks deeper connections, patterns, and contextual data. It's grounded in real-time data from reliable sources, ensuring accuracy and trustworthiness. Real-World Applications of RAG: Personalized News Podcasts: RAG can scan news articles, extract key points, and convert them into an easily digestible audio format. Here is a look at my blog which looks at the application of RAG to convert Text News to Audio. Research Summarization: It can condense complex research papers and scientific reports into key takeaways, saving users time and effort. Efficient Workflows: RAG can summarize lengthy reports, highlighting the most crucial points for faster decision-making. The Benefits of RAG: Personalized Learning and Information Processing: RAG filters out irrelevant data and presents only what's useful to the individual. Increased Efficiency: It automates information gathering and summarization, freeing up time for other tasks. The Importance of Responsible AI Use: While RAG is a powerful tool, its impact depends on our choices. It's crucial to use RAG ethically and thoughtfully to shape a positive future. What’s Next? Don't miss out on future episodes exploring exciting tech trends, data projects, and innovations! If you found this useful, please subscribe to stay updated! Embrace curiosity, keep learning, and stay tuned – the AI revolution is just beginning! You can also find me on Medium and Substack. A blog that talks about application of RAG in News Articles here This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit mukundansankar.substack.com

A much better than expected US payroll report, along with a quick end to the port strike, shift the risk distribution away from recession. Whether this adds probability to the Goldilocks outturn or the boil-the-frog scenario we have warned about is still uncertain, but the odds of rates staying higher than previously thought are clearly up. The global goods sector still looks grim, as does European growth. We remain skeptical about the medium run outlook for China even if seeing potential upside to the near-term. 

Speaker:

Bruce Kasman

Joseph Lupton

This podcast was recorded on 4 October 2024.

This communication is provided for information purposes only. Institutional clients please visit www.jpmm.com/research/disclosures for important disclosures. © 2024 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

Michael Feroli, Chief US Economist, and Samantha Azzarello, Head of Content Strategy, discuss the Sept jobs report.

This podcast was recorded on October 4, 2024.

This communication is provided for information purposes only. Institutional clients please visit www.jpmm.com/research/disclosures for important disclosures. © 2024 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

The EU AI Act is a game-changer. We break down what this groundbreaking law means for your work, how the EU categorizes AI risk (from harmless to high-risk), and the Act's potential global impact. Don't miss this crucial look at the future of AI and privacy.

What happens when the EU decides to regulate AI? We break down the groundbreaking EU AI Act - why it matters (even if you don't build robots!) and how it aims to keep humans in control. We explore everything from "totally cool" AI to the "no-go zone," plus what it means for innovation and why this Act is just the beginning of AI's story.

John Gleeson, COO of Storj, joins us on this episode of the Data Unchained podcast live from NAB! John talks with us about how bringing together organizations availale bandwidth and storage at lower costs with lower carbon footprints while also unifying data sets and getting the most value out of your data.

data #datascience #dataanalytics #AI #artificialintelligence #storage #genai #LLM #podcast #datastorage #technology #innovation #bandwidth #carbonfootprint #carbonfootprintreduction

Cyberpunk by jiglr | https://soundcloud.com/jiglrmusic Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Hosted on Acast. See acast.com/privacy for more information.

I've spent the last three weeks visiting the UK, Australia, and New Zealand. Here are my observations and anecdotes about the data and ML/AI industry from countless chats with executives, practitioners, and pundits.

The sheer number of tools and technologies that can infiltrate your work processes can be overwhelming. Choosing the right ones to invest in is critical, but how do you know where to start? What steps should you take to build a solid, scalable data infrastructure that can handle the growth of your business? And with AI becoming a central focus for many organizations, how can you ensure that your data strategy is aligned to support these initiatives? It’s no longer just about managing data; it’s about future-proofing your organization. Taylor Brown is the COO and Co-Founder of Fivetran, the global leader in data movement. With a vision to simplify data connectivity and accessibility, Taylor has been instrumental in transforming the way organizations manage their data infrastructure. Fivetran has grown rapidly, becoming a trusted partner for thousands of companies worldwide. Taylor's expertise in technology and business strategy has positioned Fivetran at the forefront of the data integration industry, driving innovation and empowering businesses to harness the full potential of their data. Prior to Fivetran, Taylor honed his skills in various tech startups, bringing a wealth of experience and a passion for problem-solving to his entrepreneurial ventures. In the episode, Richie and Taylor explore the biggest challenges in data engineering, how to find the right tools for your data stack, defining the modern data stack, federated data, data fabrics, data meshes, data strategy vs organizational structure, self-service data, data democratization, AI’s impact on data and much more.  Links Mentioned in the Show: FivetranConnect with TaylorCareer Track: Data Engineer in PythonRelated Episode: Effective Data Engineering with Liya Aizenberg, Director of Data Engineering at AwayRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

In this episode, host Jason Foster sits down with Manuel Heichlinger, inclusivity leader and Managing Director at Audeliss. The pair discuss the myths that often plague conversations around diversity and inclusion within the professional workforce and debunk these assumptions. They also explore some of the unexpected benefits of a diverse workforce, including increased productivity, competitive advantage and fostering a deeper connection with the consumer base.

Cynozure is a leading data, analytics and AI company that helps organisations to reach their data potential. It works with clients on data and AI strategy, data management, data architecture and engineering, analytics and AI, data culture and literacy, and data leadership. The company was named one of The Sunday Times' fastest-growing private companies in both 2022 and 2023, and recognised as The Best Place to Work in Data by DataIQ in 2023.  

Está no ar, o Data Hackers News !! Os assuntos mais quentes da semana, com as principais notícias da área de Dados, IA e Tecnologia, que você também encontra na nossa Newsletter semanal, agora no Podcast do Data Hackers !!

Aperte o play e ouça agora, o Data Hackers News dessa semana !

Para saber tudo sobre o que está acontecendo na área de dados, se inscreva na Newsletter semanal:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datahackers.news/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Conheça nossos comentaristas do Data Hackers News:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monique Femme⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

⁠Matérias/assuntos comentados:

CTO da OpenAI, Mira Murati anuncia saída da empresa;

Meta anuncia Orion, primeiro par de óculos de realidade aumentada;

Google lança novos Chromebooks com IA.

Baixe o relatório completo do State of Data Brazil e os highlights da pesquisa :

Demais canais do Data Hackers:

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Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! Find out which tools are most in demand, which are easiest to learn, and the best order to learn them. Learn about the Data Learning Ladder and how to quickly get started in the data industry. 💌 Join 30k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩‍💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com//interviewsimulator ⌚ TIMESTAMPS 02:23 The Big Six Data Skills 05:55 The Data Learning Ladder 🔗 CONNECT WITH AVERY 🎥 YouTube Channel 🤝 LinkedIn 📸 Instagram 🎵 TikTok 💻 Website Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Send us a text More on GenAI, Hallucinations, RAG, Use Cases, LLMs, SLMs and costs with Armand Ruiz, Director watsonx Client Engineering and John Webb, Principal Client Engineering.  With this and the previous episode you'll be wiser on AI than 98% of the world.

00:12 Hallucinations02:33 RAG Differentiation06:41 Why IBM in AI09:23 Use Cases11:02 The GenAI Resume13:37 watson.x 15:40 LLMs17:51 Experience Counts20:03 AI that Surprises23:46 AI Skills26:47 Switching LLMs27:13 The Cost and SLMs28:21 Prompt Engineering29:16 For FunLinkedIn: linkedin.com/in/armand-ruiz, linkedin.com/in/john-webb-686136127 Website: https://www.ibm.com/client-engineering

Love what you're hearing? Don't forget to rate us on your favorite platform! Want to be featured as a guest on Making Data Simple?  Reach out to us at [email protected] and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Show Notes  The Data Product Management In Action podcast, brought to you by Soda and executive producer Scott Hirleman, is a platform for data product management practitioners to share insights and experiences.  In Season 01, Episode 18, our host Frannie Helforoush is back again interviewing Katy Pusch about her extensive experience in data product management, particularly with decision-support data products. Katy shares her insights on incorporating machine learning and analytics to empower stakeholders in making informed decisions. They both explore team structure, the challenges encountered in product development, and the critical importance of validating products with users to ensure their effectiveness. About our host Frannie Helforoush: Frannie's journey began as a software engineer and evolved into a strategic product manager. Now, as a data product manager, she leverages her expertise in both fields to create impactful solutions. Frannie thrives on making data accessible and actionable, driving product innovation, and ensuring product thinking is integral to data management. Connect with Frannie on LinkedIn. About our guest Katy Pusch: Katy brings more than a decade of experience in product management and market strategy, driving market change and adoption of innovative technology solutions. She has successfully built and launched data products, IoT solutions, and SaaS platforms in multiple industries such as healthcare, education, and real estate. She is currently serving as a Sr.Product Line Director at Trintech. With a background in research, she brings data science and market intelligence to every aspect of her work. Katy is passionate about data privacy and tech-ethics, and is pursuing an MS in History and Sociology of Technology and Science at GeorgiaTech. When she’s not working with her team to deliver top solutions, Katy enjoys spending time with her husband, building Lego models, and pursuing a private pilot license. Connect with Katy on LinkedIn. All views and opinions expressed are those of the individuals and do not necessarily reflect their employers or anyone else.  Join the conversation on LinkedIn.  Apply to be a guest or nominate someone that you know.  Do you love what you're listening to? Please rate and review the podcast, and share it with fellow practitioners you know. Your support helps us reach more listeners and continue providing valuable insights!              

In this episode, I dive into the world of AI leadership with Andreas Welsh, a renowned AI expert and author of 'The AI Leadership Handbook'. We explore Andreas's impressive career at SAP, his new venture as an AI advisor and expert, his impactful journey on LinkedIn, and his insights into successful AI implementation. Topics we cover: Discover Andreas’s background and his remarkable 23-year career at SAP. He shares pivotal moments and lessons learned from working at one of the world’s largest tech companies.Learn what motivated Andreas to start sharing his expertise on LinkedIn in 2021, and the significant impact it has had on his professional life.Uncover the inspiration behind Andreas's book, The AI Leadership Handbook, and his mission to guide organisations in harnessing AI effectively.Andreas discusses the critical elements that must be in place for AI projects to thrive and avoid the common pitfalls that lead to failure.Understand the need for the emerging Chief AI Officer role, how it differs from a Chief Data & Analytics Officer, and the importance of giving it a strong mandate within organisations.Explore the concept of multiplier communities and their role in amplifying AI capabilities across organisations.Andreas shares his vision for AI over the next 5-10 years, including opportunities, potential risks, and disruptions.Andreas leaves listeners with a powerful lesson from 'The AI Leadership Handbook' that every leader should consider when integrating AI into their strategy.This episode is packed with valuable insights for anyone interested in AI leadership and innovation. Whether you're an executive, a tech enthusiast, or someone curious about the future of AI, Andreas Welsh offers guidance and inspiration to navigate this transformative field. Connect with Andreas Welsh on LinkedIn: https://www.linkedin.com/in/andreasmwelsch/ Leaders of Analytics Newsletter: https://www.leadersofanalytics.com/newsletter Subscribe to Leaders of Analytics via your favourite podcast app: Apple Podcasts Google Podcasts  Spotify

Once you decide to implement a data security strategy, it can be difficult to know where to start. With so many potential threats and challenges to resolve, teams often try to fix everything at once. But this boil-the-ocean approach is difficult to manage efficiently and ultimately leads to frustration, confusion, and halted progress. There's a better way to go. In this report, data science and AI leader Federico Castanedo shows you what to look for in a data security platform that will deliver the speed, scale, and agility you need to be successful in today's fast-paced, distributed data ecosystems. Unlike other resources that focus solely on data security concepts, this guide provides a road map for putting those concepts into practice. This report reveals: The most common data security use cases and their potential challenges What to look for in a data security solution that's built for speed and scale Why increasingly decentralized data architectures require centralized, dynamic data security mechanisms How to implement the steps required to put common use cases into production Methods for assessing risks—and controls necessary to mitigate those risks How to facilitate cross-functional collaboration to put data security into practice in a scalable, efficient way You'll examine the most common data security use cases that global enterprises across every industry aim to achieve, including the specific steps needed for implementation as well as the potential obstacles these use cases present. Federico Castanedo is a data science and AI leader with extensive experience in academia, industry, and startups. Having held leadership positions at DataRobot and Vodafone, he has a successful track record of leading high-performing data science teams and developing data science and AI products with business impact.

Growth was relatively strong across the EM Edge economies in 2Q. Nicolaie, Steven and Katie debate the influence that diverging growth risks in US, China and Europe has for growth in the Edge. While the US influence may predominate, fiscal and monetary policies, structural reforms and changing trade patterns (among others) enable some differentiation between Edge economies. Differing cyclical conditions in part explain why Fed easing won’t alter most Edge central banks’ reaction functions.

Speakers:

Katherine Marney, Emerging Markets Economic and Policy Research

Nicolaie Alexandru, EM, Economic and Policy Research

Steven Palacio, EM, Economics Research

This podcast was recorded on October 1, 2024.

This communication is provided for information purposes only. Institutional clients can view the related report at https://www.jpmm.com/research/content/GPS-4803854-0  and https://www.jpmm.com/research/content/GPS-4799145-0 for more information; please visit www.jpmm.com/research/disclosures for important disclosures. © 2024 JPMorgan Chase & Co. All rights reserved. This material or any portion hereof may not be reprinted, sold or redistributed without the written consent of J.P. Morgan. It is strictly prohibited to use or share without prior written consent from J.P. Morgan any research material received from J.P. Morgan or an authorized third-party (“J.P. Morgan Data”) in any third-party artificial intelligence (“AI”) systems or models when such J.P. Morgan Data is accessible by a third-party. It is permissible to use J.P. Morgan Data for internal business purposes only in an AI system or model that protects the confidentiality of J.P. Morgan Data so as to prevent any and all access to or use of such J.P. Morgan Data by any third-party.

Episode Summary: In this episode, we dive into the exciting world of AI and Large Language Models (LLMs) and how they're revolutionizing marketing. Gone are the days of generic campaigns and guesswork. With AI, marketing is becoming highly personalized, insight-driven, and responsive to individual customer needs—all in real-time. Key Points Covered: * The Shift from Data-Driven to Insight-Driven MarketingDiscover how marketing is evolving from simply collecting data to understanding the "why" behind customer behavior. AI allows marketers to predict customer preferences, making campaigns more targeted and effective. * AI-Powered Personalization at ScaleLearn how AI can dig into customer data to deliver hyper-personalized experiences, like suggesting a product based on your previous purchases, time of day, or even the weather in your location. * Customer Journey Mapping with AIAI is now capable of mapping every step of a customer’s interaction with a brand, from the first website visit to the final purchase, helping marketers identify friction points and optimize the entire journey. * The Power of Real-Time AI DashboardsForget the overwhelming spreadsheets! AI-powered dashboards are the new standard, delivering clear, actionable insights in real-time across all marketing channels. * Ethical Considerations in AI-Driven MarketingWith great power comes great responsibility. We explore how marketers can walk the fine line between personalization and privacy, and why transparency and trust are critical in this AI-powered era. * The Future of AI in Customer ExperienceFrom chatbots that truly understand your needs to online shopping experiences that adapt to you, AI is poised to make our everyday interactions with brands smoother and more enjoyable. Memorable Quote:"It’s like having a dedicated marketing team for every single customer." Ethical Discussion:We discuss the responsibility marketers have in ensuring AI respects data privacy and builds trust with consumers. Regulations like GDPR are setting important standards, but it’s up to each brand to find the balance between personalization and privacy. Final Thought:As AI continues to reshape the marketing landscape, it's crucial for brands and customers alike to stay informed, ask questions, and participate in the conversation about how these technologies are used. Have thoughts on how AI is transforming marketing? Share your insights with us, and stay curious for the next episode as we dive deeper into the world of AI, marketing, and beyond. Send me an email at [email protected] This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit mukundansankar.substack.com

Ilya Reznik has been in the ML game for ages, having worked at Adobe and Twitter and led teams at Meta, among others.

We chat about leading ML teams, AI today, creating content, and much more.

LinkedIn: https://www.linkedin.com/in/ibreznik/