Welcome to the latest episode of "AI with Shaily," hosted by Shailendra Kumar! 🎙️ Today’s deep dive explores the cutting-edge trend of edge computing and its transformative impact on data science by 2026. 🚀

Picture yourself in a busy airport 🛫, where countless sensors monitor luggage, security checkpoints, and crowd movements. Traditionally, all this data would be sent to distant cloud data centers for processing, causing delays in receiving actionable insights. Edge computing changes the game by analyzing data locally, right at the airport terminals, enabling near real-time decision-making. This shift isn’t just about speed; it revolutionizes how quickly and effectively decisions can be made on-site. ⏱️✨

Edge computing moves data processing closer to where data is generated—think IoT devices in smart cities 🌆 or autonomous vehicles 🚗. This proximity drastically reduces latency, allowing industries to respond instantly. When combined with edge AI—powered by compact yet powerful chips like NVIDIA’s Jetson series—complex machine learning tasks can be executed directly on these devices. Imagine having the computational power of a full data center in the palm of your hand! 🤯💻

But it’s not only about faster processing. Data science is evolving from handling centralized, static datasets to managing dynamic, distributed data streams. Hybrid architectures that blend edge and cloud computing are redefining data workflows, offering a flexible and efficient approach. The edge data center market is booming, expected to exceed $300 billion by 2026, underscoring the critical infrastructure supporting this growth. 💡📊

The impact spans multiple sectors: healthcare benefits from real-time patient monitoring with minimal delays 🏥❤️, manufacturers can optimize production lines on the fly 🏭⚙️, and autonomous vehicles improve safety through instant decisions 🛡️. These advancements reduce operational costs and pave the way for innovations we’re only beginning to imagine. 🌟

Drawing from personal experience, Shailendra shares that early challenges in implementing edge AI in industrial environments included managing complexity and latency. However, with rapid technological advancements and scalable platforms, these hurdles are quickly diminishing. A valuable tip for those exploring edge AI: focus on understanding hybrid deployment models, which balance local processing with cloud analytics for maximum flexibility. 🎯🔧

To wrap up, Shailendra poses a thought-provoking question: How will your industry or daily life transform when data-driven decisions happen instantly, right where the action takes place? 🤔⚡

He closes with an inspiring quote from computer pioneer Alan Kay: “The best way to predict the future is to invent it.” Edge computing and data science are actively shaping that future today. 🌍✨

Don’t miss out—follow Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium for more AI insights. Subscribe, share your thoughts, and keep pushing the boundaries of innovation. Until next time, keep imagining, innovating, and questioning! 🙌🤖

Edge Computing Revolution: How AI and Data Science Will Transform Our Future by 2026

Episode 9.19 - At-Bat Indicator

9.20 covers some Derby & ASG stuff (0:44), peaks at the TGFBI standings (5:00), continues the K rate deep dive (6:42), reviews Lourdes Gurriel (20:15), and reviews Zac Gallen (25:48).

Episode 9.20 - Doing It Right

Welcome to "AI with Shaily," your weekly journey into the fascinating world of artificial intelligence, hosted by Shailendra Kumar, a passionate AI enthusiast. 🎙️🤖 In this episode, Shaily dives deep into the transformative power of data science on supply chains by the year 2026 — a hot topic buzzing across social media and revolutionizing how businesses approach logistics. 🚚📦

Imagine a supply chain so intelligent and adaptive that it functions like a self-driving car for your products. 🚗✨ Autonomous AI systems will soon be capable of rerouting shipments around traffic jams or unforeseen delays without any human input. For example, if a storm disrupts your gadget’s delivery route, AI will instantly find a new path to ensure your package arrives on time. This level of agility excites both businesses aiming for efficiency and consumers craving reliability. 🌩️➡️🛤️📬

But the innovation doesn’t stop there! Demand forecasting is set to become hyper-personalized, leveraging data from social media sentiment and real-time economic changes. 📊💬 This means supply chains will have a real-time pulse on consumer moods and trends, allowing inventory decisions to be made with near-perfect accuracy. Shaily recalls clients struggling with overstocking products that suddenly lost popularity — a problem that will soon be solved by these data-driven advances. 📉🛒

Transparency and trust are also taking center stage. By combining blockchain technology with AI, every transaction becomes tamper-proof and fully visible, making fraud nearly impossible. 🔗🛡️ This radical openness not only protects businesses but also boosts consumer confidence. Additionally, edge computing paired with IoT sensors enables supply chains to make lightning-fast decisions locally, optimizing routes and operations in real time without waiting for centralized data processing. ⚡📡

AI is also stepping up in risk management by predicting disruptions before they occur, giving companies a proactive edge. 🛑🔮 For environmentally conscious stakeholders, sustainability analytics will offer insights into carbon footprints, fuel consumption, and packaging impacts — paving the way for greener, more responsible logistics networks. 🌍♻️

Here’s a fascinating fact: by 2026, over 75% of enterprises are expected to deploy AI-based supply chain tools. 📈🚀 This massive adoption signals a future where data science becomes the heartbeat of supply chain strategy rather than just a back-office function.

Before wrapping up, Shaily shares a valuable tip: if you work in supply chain or logistics, start learning about AI tools and blockchain basics now. Early adopters of these technologies will not only survive but thrive in the hyper-connected future ahead. 🧠💡

Finally, Shaily poses a thought-provoking question: Are we ready to trust machines with decisions traditionally made by humans? The future says yes, and watching this transition unfold will be truly fascinating. 🤔🤖

Quoting legendary computer scientist Alan Kay, “The best way to predict the future is to invent it.” In the realm of supply chains, AI and data science are the inventors crafting tomorrow’s logistics today. 🔮✍️

To stay informed with more AI insights, follow Shailendra Kumar on YouTube, Twitter, LinkedIn, and Medium. Subscribe for your weekly AI news fix and share your thoughts on autonomous supply chains in the comments — Shaily is eager to hear your perspective! 📱💬

This is Shailendra Kumar signing off from "AI with Shaily" — where artificial intelligence meets real-world impact. Catch you next time! 👋🤖✨

AI Revolution: How Data Science Will Transform Supply Chains by 2026

„Aki kalapácsot fog a kezébe, hirtelen mindent szögnek lát” – mondja Ignácz Péter, a KPMG Data Science managere, aki a Spirit FM „MI és más” című műsorában árulta el, miért nem mindig mesterséges intelligencia a legjobb válasz egy üzleti problémára.

A beszélgetésből kiderül, hogyan építhető be a generatív AI a vállalati folyamatokba értékteremtő módon, mikor érdemes inkább RPA-t választani, és miért kulcskérdés az adatminőség.

MI bevezetés és használat biztonságosan és értékteremtő módon

9.21 takes in some Cape Cod Baseball League action (0:40), peeks at the TGFBI standings (3:30), works matrix magic into batting order similarities by team (3:50), reviews Jackson Merrill (16:56), and reviews Dylan Cease (25:46). 

Episode 9.21 -Sophomore Slump Experience

9.22 walks through the Twins fire sale (0:41), peeks at the TGFBI standings (5:10), sorts through the bevy of player movement (6:18), reviews Ben Rice (20:41), and reviews Will Warren (27:40) 

Episode 9.22 - Closer Bloodbath

9.23 wonders at the Blue Jays (0:41), notes TGFBI standings (3:54), finds a Rose Field (4:48), dusts off the binomial PA predictor (5:37), reviews Nick Kurtz (20:30), and reviews Luis Severino (26:27).

Episode 9.23 - Pelt Him With Balls

9.24 brews some Brewers thoughts (0:44), notes the TGFBI standings (2:31), checks recent changes in player ownership (3:50), reviews Bennet Sousa (18:53), and reviews Mauricio Dubon (24:23).

Episode 9.24 - Significant Drop

9.25 brushes on some homer topics (0:40), glances at TGFBI standings (4:37), scrutinizes decisions (5:30), reviews Max (20:45), and reviews Addison Barger (24:55)

Episode 9.25 - King of Disaggregate Analysis

Unlock the secrets of data mastery with Shailendra, a 27-year veteran in AI, ML, and Data Science, driving AU$ 6 Billion in transformative value. As the author of 'Making Money out of Data,' their strategies redefine digital success. With expertise honed at IBM and Accenture, they drive innovation and data monetization. Explore how loyalty programs like Flybuys and Everyday Rewards revolutionize business—connect with Shaily today.

To quote Dr. Evil, "The details of our lives are quite inconsequential." What's important is that we like fantasy, as it applies to the genre and the game derived from baseball statistics. We also enjoy developing analytical and computational “tools” for supporting the latter habit. Our goal is to share our fantasy baseball tools with a little help from the fantasy genre for context, allusion, and (fire and) ice breaking. In doing so, we hope to broaden the way our audience approaches fantasy baseball. Our podcast presents our methods to the public in the spirit of OpenSource - through freely helping others we promote active conversation that improves our tools.

Kövesd a KPMG Hungary folyamatosan frissülő csatornáját és maradj naprakész legyen szó jelenről vagy jövőről, gazdasági vagy társadalmi témákról. #KPMGVoice
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A KPMG könyvvizsgálati, adóügyi és tanácsadási szolgáltatásokat nyújtó független szakmai szolgáltatók globális szervezete. 144 országban és tartományban működünk, világszerte 236 000 fő dolgozik tagtársaságainknál. Mindegyik KPMG-tagtársaság jogilag különálló gazdálkodó egység, és ilyenként határozza meg magát. A KPMG International Limited („KPMG International”) angol “private English company limited by guarantee” társasági formában működik. A KPMG International és kapcsolt gazdálkodó egységei ügyfelek részére nem nyújtanak szolgáltatásokat.

A magyarországi KPMG-tagtársaságoknál több mint 1400 fő dolgozik – a KPMG Hungária Kft. könyvvizsgálati szolgáltatásokat, a KPMG Tanácsadó Kft. tanácsadási szolgáltatásokat, a KPMG Legal Tóásó Ügyvédi Iroda jogi szolgáltatásokat kínál magyar és multinacionális társaságoknak, kormányzati szerveknek és külföldi befektetőknek, míg a KPMG Global Services Hungary Kft. (KGSH) megfeleléssel kapcsolatos szolgáltatásokat nyújt multinacionális vállalatcsoportoknak több mint 35 országban.

New tracks tagged #datascience