Sinan and Akshay sit down with Sudhir Hasbe, Chief Product Officer at Neo4j and a leading expert in graph databases and analytics. Sudhir shares insights from his career, including his time leading Google's analytics product lines and managing multi-million dollar data and ML initiatives.We explore why 2024 is a breakout year for graph databases and their role in Retrieval-Augmented Generation (RAG), diving into topics like:- The history and evolution of graph technology and knowledge graphs- Why knowledge graphs are vital for solving today’s complex AI challenges- The trifecta of cloud computing, LLMs, and big data fueling graph RAG adoption- Practical tips for building scalable, explainable, and secure graph RAG systems

In this insightful episode of Practically Intelligent, we sit down with Professor Philip Treleaven, Director of the UK Financial Computing Centre at UCL, to discuss the complex relationship between AI, finance, and regulation. From the early days of algorithmic trading to today’s pressing cybersecurity concerns, Professor Treleaven offers a unique perspective on how AI innovations are reshaping industries and the critical role of real-time compliance in the battle against cybercrime.We also explore the growing startup ecosystem and how Professor Treleaven has inspired the next generation of entrepreneurs through his hands-on mentorship at UCL. Whether you're an AI enthusiast, a founder, or working in finance, this episode is packed with actionable insights!

In this special episode of Practically Intelligent, we're trying something new! Sinan is opening his doors to answer your burning questions about AI, machine learning, data science, and more during our very first Office Hours episode.Do you wonder if prompt engineering is dying? Or maybe you're curious about what exactly an AI agent is and how it can be useful? Sinan tackles your questions, providing insights drawn from his O'Reilly lectures and real-world experience as an AI entrepreneur and consultant.Head over to practicallyintelligent.com to submit your questions, and we might just answer them in our next Office Hours session.

In this episode of Practically Intelligent, Sinan and Akshay sit down with Rich Skrenta, the Executive Director of the Common Crawl Foundation. Rich shares his extensive experience in data aggregation and AI and how that ties into the history, mission, and future of Common Crawl—a nonprofit organization responsible for one of the largest open-source web data repositories in the world. The three discuss the challenges and opportunities of expanding Common Crawl's global reach, the critical role of curated data in training large language models, and the importance of maintaining open access to the internet in the age of cutting edge AI.Key topics include:The importance of curated data in AI trainingChallenges of expanding Common Crawl globallyThe future of open internet access in the AI era

The advent of Generative AI presents a significant challenge for security in the enterprise. Join us as we deep dive into the common threat vectors with Sanjay Kalra, product leader at Zscaler and former CPO of Lacework. Sanjay offers insights into new threats generative AI creates for data security, access control, compliance, and more.

Dive into the intricate world of AI and open source with Rajiv Shah in the latest episode of "Practically Intelligent." Rajiv, with his extensive experience at DataRobot, Hugging Face, and now Snowflake, offers invaluable insights into how enterprises can leverage AI and data effectively. The conversation explores the current trends in open source LLMs, the dynamics of AI licensing and governance, and the implications for businesses looking to innovate in this space. Join us as we uncover the nuances of open source contributions to AI, predict future trends, and discuss the potential shifts in how AI is utilized across industries. This episode is a must-listen for anyone interested in the crossroads of technology, business, and open-source innovation.Rajiv's Website: https://rajivshah.com

Join us as we talk with Curtis Northcutt, founder and CEO of CleanLab.ai. Curtis shares his expert insights on the crucial role of data preparation and curation in enhancing AI model reliability. Discover how CleanLab.ai is pioneering no-code solutions to streamline data curation, making AI more accessible and effective across various industries. Learn about the challenges and innovative approaches to ensuring data you can trust, directly from a leader reshaping how businesses handle their most critical asset.

In episode 11 of Practically Intelligent, we take a look at the dynamic and intricate world of business intelligence (BI) with the esteemed Donald Farmer, a pioneer in BI and the driving force behind Power BI. This episode takes us on a journey through the evolution of BI, from its roots in decision support systems to the burgeoning era of machine learning and the transformative potential of language models.Donald shares insights on:The early days of BI and the launch of Power BI, setting the stage for today's AI advancements.The transition from traditional data warehousing to the necessity for centralization and the advent of self-service BI tools.How predictive analytics moved from a specialization to a mainstream necessity, paving the way for AI's role in strategic decision-making.The emergence of language models as key players in shaping strategic decisions, making AI not just a tool but a team member in the decision-making process.We also explore the broad spectrum of decisions influenced by BI tools, from operational to strategic, and how machine learning and AI are revolutionizing this landscape. Donald offers a critical perspective on the current hype cycle in AI, distinguishing between genuine innovation and overblown claims.

Dr. Nathan Lambert is back! Episode 10 of Practically Intelligent has us diving headfirst into a the tsunami of AI advancements and the hype cycles surrounding them. With the field evolving at breakneck speed, it's easy to oscillate between awe and skepticism. Join us in a thought-provoking conversation with Nathan Lambert as we explore how to navigate this complex landscape.This episode is tailored for both builders and investors in AI, as well as anyone curious about the technology's rapid development.We discuss:- How to separate mind-blowing AI advancements from overhyped claims.- Strategies for improving your 'information diet' in the AI space.- Practical tips for staying grounded and accurately informed about technical progress, including basic checks for affiliations and scrutinizing code.- Understanding general principles in machine learning to discern quality information.

What were the biggest trends in AI in 2023 that will accelerate into 2024? What will change/what is overhyped? In this episode, we go through charts and reports from Coatue's recent AI report to dissect the key assertions made about the future of AI, from its transformative impact on technology to the burgeoning role of open-source. We'll highlight the most compelling insights, challenge hyperbole, and correct any misleading narratives we find.Whether you're an AI enthusiast or skeptic, this episode promises a nuanced exploration of AI's potential and pitfalls, offering a clear-eyed perspective on what's genuinely revolutionary and what's just hype in the world of artificial intelligence.The Report: https://www.coatue.com/blog/perspective/ai-the-coming-revolution-2023Chart 1: "Despite intense demand, AI compute costs have decreased" - Page 78Chart 2: "Problem: Model evaluation is broken today" - Page 88Chart 3: "Synthetic data can augment fine-tuning" - Page 62Chart 4: "Data quality is just as important as data quantity" - Page 61Chart 5: "Data scarcity is a potential wall to scaling models" - Page 60Chart 6: "AI regulation may be more likely than most think" - Page 26