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Analyzing customer sentiment and key themes from textual data has always been a time-intensive task, requiring data collection, manual labeling, and fine-tuning specialized models. But what if you could skip the hassle of training a model and still achieve accurate results? Enter zero-shot text classification, a groundbreaking approach powered by Large Language Models (LLMs).
Multilingual knowledge graphs (KGs) provide high-quality relational and textual information for various NLP applications, but they are often incomplete, especially in non-English languages. Previous research has shown that combining information from KGs in different languages aids either Knowledge Graph Completion (KGC), the task of predicting missing relations between entities, or Knowledge Graph Enhancement (KGE), the task of predicting missing textual information for entities.
In today’s digital landscape, content repurposing has become crucial for maximizing reach and engagement. One effective strategy is transforming long-form content like blog posts into engaging Twitter threads. However, manually creating these threads can be time-consuming and challenging. In this article, we’ll explore how to build an application to automate blog to Twitter thread creation […] The post Automate Blog to Twitter Thread using Gemini-2.0, LangChain, and Streamlit a
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Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage
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For years, renowned fire experts Jack Cohen and Stephen Pyne have tried to shift the conversation on fire prevention strategies. This weeks destruction, they say, could have been minimized.
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Speaker: Andrew Skoog, Founder of MachinistX & President of Hexis Representatives
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AI imagery transparency is only half the creative war against the machines. How will increasing consumption of AI creations change our perception of hand-crafted imagery?
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In todays column, I examine a high-profile assertion that advancements in generative AI and large language models (LLMs) will be hampered or possibly curtailed by our soon-to-be dilemma of running out of available data.
AI is the problem. Continuing to find ways to use it can't be the solution. Late last year, I started writing a column on generative artificial intelligence.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
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Today's public incident writeup comes courtesy of Brendan Humphries, the CTO of Canva. Like so many other incidents that came before, this is another tale of saturation, where the failure mode involves overload. There's a lot of great detail in Humpries's write-up, and I recommend you read it directly in addition to this post.
The next time you go in for a checkup with your doctor there may be someone else in the room. Sort of. More doctors are turning to artificial intelligence to record conversations with patients and take notes.
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Members of the fledgling WordPress Sustainability Team have been left reeling after WordPress co-founder Matt Mullenweg abruptly dissolved the team this weekan action prominent tech journalist Kara Swisher has described as "bizarrely heinous behavior.
Summary: The article explores the differences between data driven and AI driven practices. The right approach is necessary to improve decisions and ensure your business remains competitive. Data-driven and AI-driven approaches have become key in how businesses address challenges, seize opportunities, and shape their strategic directions. Introduction Are you struggling to decide between data-driven practices and AI-driven strategies for your business?
Speaker: Chris Townsend, VP of Product Marketing, Wellspring
Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?
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