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Præsentation fra seminaret "Fremtiden er mobil". Tak til eBay!

Technologie Business

Mobile hos eBay
Thomas Jensen
Snr. Product Manager Mobile

Vores overvejelser

Marketing basics

eBay Inc. confidential 3

Vores overvejelser

Winner takes most

eBay Inc. confidential 4

Vores overvejelser

Mobile er core for eBay

eBay Inc. confidential 5

Platforme

Mobile Web eller App

eBay Inc. confidential 6

Platforme

Native apps eller HTML5 apps

eBay Inc. confidential 7

Platforme

Apple iOS / Android / Windows Phone

eBay Inc. confidential 8

Løsninger

DBA

eBay Inc. confidential 10

eBay Mobile - Løsninger

BilBasen

eBay Inc. confidential 11

eBay Mobile - Løsninger

MyDealNow

eBay Inc. confidential 12

eBay Mobile - Løsninger

RedLaser

eBay Inc. confidential 13

eBay Mobile - Løsninger

Watch with eBay

eBay Inc. confidential 14

eBay Mobile - Løsninger

PayPal Here

eBay Inc. confidential 15

Erfaringer

Kvalitet

eBay Inc. confidential 17

Erfaringer

”Mobile first” approach

eBay Inc. confidential 18

Erfaringer

Opdateringer

eBay Inc. confidential 19

Erfaringer

Lyt til brugerne

eBay Inc. confidential 20

Erfaringer

”Fulde løsninger” eller ”lidt men godt”

eBay Inc. confidential 21

Erfaringer

API er vitalt

eBay Inc. confidential 22

Erfaringer

Fancy features

eBay Inc. confidential 23

Resultater

Det virker !

eBay Inc. confidential 25

Resultater

Andel af trafik

eBay Inc. confidential 26

Resultater

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eBay Inc. confidential 27

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Omsætning

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Sara Mae O’Brien Scott and Tatiana Baquero Cakici, Senior Consultants at Enterprise Knowledge (EK), presented “AI Fast Track to Search-Focused AI Solutions” at the Information Architecture Conference (IAC24) that took place on April 11, 2024 in Seattle, WA. In their presentation, O’Brien-Scott and Cakici focused on what Enterprise AI is, why it is important, and what it takes to empower organizations to get started on a search-based AI journey and stay on track. The presentation explored the complexities of enterprise search challenges and how IA principles can be leveraged to provide AI solutions through the use of a semantic layer. O’Brien-Scott and Cakici showcased a case study where a taxonomy, an ontology, and a knowledge graph were used to structure content at a healthcare workforce solutions organization, providing personalized content recommendations and increasing content findability. In this session, participants gained insights about the following: Most common types of AI categories and use cases; Recommended steps to design and implement taxonomies and ontologies, ensuring they evolve effectively and support the organization’s search objectives; Taxonomy and ontology design considerations and best practices; Real-world AI applications that illustrated the value of taxonomies, ontologies, and knowledge graphs; and Tools, roles, and skills to design and implement AI-powered search solutions.

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

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Hvad gør eBay

1. Mobile hos eBay Thomas Jensen Snr. Product Manager Mobile

2. Overvejelser eBay Inc. confidential 2

3. Vores overvejelser Marketing basics eBay Inc. confidential 3

4. Vores overvejelser Winner takes most eBay Inc. confidential 4

5. Vores overvejelser Mobile er core for eBay eBay Inc. confidential 5

6. Platforme Mobile Web eller App eBay Inc. confidential 6

7. Platforme Native apps eller HTML5 apps eBay Inc. confidential 7

8. Platforme Apple iOS / Android / Windows Phone eBay Inc. confidential 8

9. Løsninger eBay Inc. confidential 9

10. Løsninger DBA eBay Inc. confidential 10

11. eBay Mobile - Løsninger BilBasen eBay Inc. confidential 11

12. eBay Mobile - Løsninger MyDealNow eBay Inc. confidential 12

13. eBay Mobile - Løsninger RedLaser eBay Inc. confidential 13

14. eBay Mobile - Løsninger Watch with eBay eBay Inc. confidential 14

15. eBay Mobile - Løsninger PayPal Here eBay Inc. confidential 15

16. Erfaringer eBay Inc. confidential 16

17. Erfaringer Kvalitet eBay Inc. confidential 17

18. Erfaringer ”Mobile first” approach eBay Inc. confidential 18

19. Erfaringer Opdateringer eBay Inc. confidential 19

20. Erfaringer Lyt til brugerne eBay Inc. confidential 20

21. Erfaringer ”Fulde løsninger” eller ”lidt men godt” eBay Inc. confidential 21

22. Erfaringer API er vitalt eBay Inc. confidential 22

23. Erfaringer Fancy features eBay Inc. confidential 23

24. Resultater eBay Inc. confidential 24

25. Resultater Det virker ! eBay Inc. confidential 25

26. Resultater Andel af trafik eBay Inc. confidential 26

27. Resultater Vækst eBay Inc. confidential 27

28. Resultater Omsætning eBay Inc. confidential 28

29. Spørgsmål eBay Inc. confidential 29

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