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 contextual ai


Knowledge Graphs for Contextual AI

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The Neo4j Graph Data Platform is the most trusted and advanced suite of graph technology products, helping the world make sense of data. Available as a fully managed cloud service, or self-hosted, Neo4j gives developers and data scientists the tools they need to quickly build intelligent applications and ML workflows.


Council Post: Understanding Contextual AI In The Modern Business World

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Emilia Kirk is the Global Head of Growth at Seedtag, responsible for Client, Marketing and Product Growth. Visit Seedtag's site to hear more There are certain developments in the world of business that cannot be ignored. They revolutionize the way you work and become absolutely essential in the ways you operate. However, some developments, such as contextual AI, work quietly in the background and are sometimes seen as nice-to-have rather than business-critical. In my experience, this is a flawed assumption. I believe contextual AI needs to be seen as part of the absolute necessities to drive success.


Is Machine Learning The Key To Unlocking Gen Z Engagement? A Discussion With Jonathan Jadali Of Ascend

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The jury is still out on what makes Gen Z'ers tick, but while the research is still ongoing there is much evidence to suggest that a marketing strategy utilizing machine learning is exponentially more effective with the next generation. One thing is abundantly clear to every marketer worth his salt; Gen Z customers are "ninja-level" efficient at swatting away regular ads and pop-ups. They are strongly immune to hard sales and obvious sales content. Despite all the difficulties that marketers are facing in reaching a wide Gen Z audience, Jonathan Jadali, CEO and Founder at Ascend Agency has found great success in leading Gen Z-focused startups to victory in this marketing struggle. So what makes the typical Gen Z customer tick and how can businesses and startups build a brand that is appealing to them, utilizing cutting edge technologies?


How AI Can Help To Moderate Content

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The Internet is ripe with toxic content. Social Media companies such as Facebook, Twitter, Instagram, etc., have been using a combination of human content moderators and technology to try to limit the amount of harmful content. With the advancement of AI algorithms, companies such as Spectrum Labs are rushing into the space to use contextual AI algorithms to improve toxic content detection. They've just raised a 10 million round of funding in September 2020. It seems content platforms want more sophisticated solutions.


AI in messaging: Hard to solve, but full of promise

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There is a huge whitespace waiting to be filled by the tech companies that recognize the power and potential of messaging. Roughly 63% of people prefer to share information on "dark social," or closed, private messaging environments like Facebook Messenger and WhatsApp. However, the experience on these platforms remains painfully circuitous. In order to share a single piece of content within a conversation, users typically have to leave their active chat, open a new window to locate and copy the file, then re-enter the original chat to paste and share. So there is a big opportunity in providing more intelligent ways to share content on messaging – whether that content is a funny animation, a dinner reservation, or the directions for getting somewhere.