Pop-up commerce
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The document provides insights into the vast array of user session data collected by eBay, highlighting 4-6 terabytes of data per day and over 150 million sessions. It discusses the distribution patterns of buyer and seller behaviors, revealing that buyers outnumber sellers and emphasizing power law distributions in various metrics. Additionally, it mentions the average lifespan of items listed on the platform and the high volume of new items introduced daily.
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Oh, the Possibilities - Balancing Innovation and Risk with Generative AI.pdfPriyanka Aash
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Oh, the Possibilities - Balancing Innovation and Risk with Generative AIRaman Bhaumik - Passionate Tech Enthusiast
Raman Bhaumik - Passionate Tech EnthusiastRaman Bhaumik
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A Junior Software Developer with a flair for innovation, Raman Bhaumik excels in delivering scalable web solutions. With three years of experience and a solid foundation in Java, Python, JavaScript, and SQL, she has streamlined task tracking by 20% and improved application stability.Securing Account Lifecycles in the Age of Deepfakes.pptx
Securing Account Lifecycles in the Age of Deepfakes.pptxFIDO Alliance
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Securing Account Lifecycles in the Age of DeepfakesA Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdf
A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and Privacy.pdfPriyanka Aash
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A Constitutional Quagmire - Ethical Minefields of AI, Cyber, and PrivacyThe Future of Technology: 2025-2125 by Saikat Basu.pdf
The Future of Technology: 2025-2125 by Saikat Basu.pdfSaikat Basu
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A peek into the next 100 years of technology. From Generative AI to Global AI networks to Martian Colonisation to Interstellar exploration to Industrial Nanotechnology to Artificial Consciousness, this is a journey you don't want to miss. Which ones excite you the most? Which ones are you apprehensive about? Feel free to comment! Let the conversation begin!9-1-1 Addressing: End-to-End Automation Using FME
9-1-1 Addressing: End-to-End Automation Using FMESafe Software
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This session will cover a common use case for local and state/provincial governments who create and/or maintain their 9-1-1 addressing data, particularly address points and road centerlines. In this session, you'll learn how FME has helped Shelby County 9-1-1 (TN) automate the 9-1-1 addressing process; including automatically assigning attributes from disparate sources, on-the-fly QAQC of said data, and reporting. The FME logic that this presentation will cover includes: Table joins using attributes and geometry, Looping in custom transformers, Working with lists and Change detection.OpenPOWER Foundation & Open-Source Core Innovations
OpenPOWER Foundation & Open-Source Core InnovationsIBM
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penPOWER offers a fully open, royalty-free CPU architecture for custom chip design.
It enables both lightweight FPGA cores (like Microwatt) and high-performance processors (like POWER10).
Developers have full access to source code, specs, and tools for end-to-end chip creation.
It supports AI, HPC, cloud, and embedded workloads with proven performance.
Backed by a global community, it fosters innovation, education, and collaboration.The Future of Product Management in AI ERA.pdf
The Future of Product Management in AI ERA.pdfAlyona Owens
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Hi, Im Aly Owens, I have a special pleasure to stand here as over a decade ago I graduated from CityU as an international student with an MBA program. I enjoyed the diversity of the school, ability to work and study, the network that came with being here, and of course the price tag for students here has always been more affordable than most around.
Since then I have worked for major corporations like T-Mobile and Microsoft and many more, and I have founded a startup. I've also been teaching product management to ensure my students save time and money to get to the same level as me faster avoiding popular mistakes. Today as Ive transitioned to teaching and focusing on the startup, I hear everybody being concerned about Ai stealing their jobs Well talk about it shortly.
But before that, I want to take you back to 1997. One of my favorite movies is Fifth Element. It wowed me with futuristic predictions when I was a kid and Im impressed by the number of these predictions that have already come true. Self-driving cars, video calls and smart TV, personalized ads and identity scanning. Sci-fi movies and books gave us many ideas and some are being implemented as we speak. But we often get ahead of ourselves:
Flying cars,Colonized planets, Human-like AI: not yet, Time travel, Mind-machine neural interfaces for everyone: Only in experimental stages (e.g. Neuralink).
Cyberpunk dystopias: Some vibes (neon signs + inequality + surveillance), but not total dystopia (thankfully).
On the bright side, we predict that the working hours should drop as Ai becomes our helper and there shouldnt be a need to work 8 hours/day. Nobody knows for sure but we can require that from legislation. Instead of waiting to see what the government and billionaires come up with, I say we should design our own future.
So, we as humans, when we dont know something - fear takes over. The same thing happened during the industrial revolution. In the Industrial Era, machines didnt steal jobsthey transformed them but people were scared about their jobs. The AI era is making similar changes except it feels like robots will take the center stage instead of a human. First off, even when it comes to the hottest space in the military - drones, Ai does a fraction of work. AI algorithms enable real-time decision-making, obstacle avoidance, and mission optimization making drones far more autonomous and capable than traditional remote-controlled aircraft. Key technologies include computer vision for object detection, GPS-enhanced navigation, and neural networks for learning and adaptation. But guess what? There are only 2 companies right now that utilize Ai in drones to make autonomous decisions - Skydio and DJI.
MPU+: A Transformative Solution for Next-Gen AI at the Edge, a Presentation...
MPU+: A Transformative Solution for Next-Gen AI at the Edge, a Presentation...Edge AI and Vision Alliance
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- 2. Up
- 10. 4-6 TB of User Session Data Collected Per Day 150+ million sessions 10+K event types Hundreds of millions of user guids
- 20. Miami Phoenix Tampa Miami DFW (Colts/Bears) (Giants/Patriots) (Steelers/Cardinals) (Saints/Colts) (Packers/Steelers)
- 32. Paris Hilton wii Temporal Pattern in Dotted line and Optimal State Sequence in Solid line
- 40. Multi-year Query Burst Bursty Queries Volume Time-series Detection Index the queries for periodicity search Periodically Bursting Queries Non-periodic , one-off buzz events royal Superbowl Hannukah wedding justin bieber hair Cluster co-occurring Bursty queries Auto-detected events Cleaning and based on other dimensions labeling
- 41. Valentine Wreath Back to school Primitive Valentines Girls backpack Valentine Cards Valentines Day Back To School alice costume boutique halloween handmade costume teen halloween costumes mummy costume bat costume viking costume alice in wonderland costumes rainbow brite costume handmade costume pikachu costume ghost costume dora costume couples costume pocahontas costume mens halloween costume jim shore halloween angel costume gorilla costume zorro costume couples halloween costumes bear costume referee costume devil costume jester costume mens pirate costume egyptian costume tinker bell costume leg avenue costume saloon girl costume longaberger halloween werewolf costume funny costume elmo costume wizard of oz costume homemade costume couples costumes red riding hood costume halloween animated halloween costumes women gangster costume pig costume frankenstein costume Halloween
- 53. Products/ Products/Categ Volume/Revenu eCategories ories Sellers Buyers
- 55. Buyers outnumber sellers 5:1 Seller-items sold has a power law distribution Seller-revenue has a power law distribution Buyer-items bought has a power law distribution For a sample period over 1 month mean is 3 and median is 1 Buyer-spent money has a power law distribution For a sample period of 1 month mean is 98$ and median was 45$ Categories browsed - mean 10.5, median 5 ~10M new items a day, most items eventually sell, items last from a day to 30 days, most items not cataloged, some auction-some fixed price