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The 2024 social media marketing trends report highlights significant shifts influenced by generative AI, including the emergence of personalized content, the rise of virtual influencers, and a stronger focus on user-generated content. Insights were gathered from 33 experts across 23 leading independent agencies, providing a perspective that emphasizes creativity and authenticity in marketing strategies. Key trends also include the blending of B2B and B2C approaches, reflecting changes in consumer behavior and the evolving landscape of social media engagement.Trends In Paid Search: Navigating The Digital Landscape In 2024
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The document discusses trends in paid search for 2024, highlighting changes in user behavior, the implications for financial services, and privacy challenges. It emphasizes the importance of adapting search strategies, utilizing AI-driven tools like performance max and smart bidding, and leveraging first-party data for better marketing efficacy. Key takeaways include holistic SEO and SEM approaches, monitoring shifting user intents, and the need for continuous performance evaluation.5 Public speaking tips from TED - Visualized summary
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The document outlines five public speaking tips from Chris Anderson, TED Talks curator, emphasizing the importance of eye contact, vulnerability, humor, humility, and storytelling. These skills are presented as essential for engaging audiences effectively and are increasingly valuable in today's economy. The article posits that mastering these techniques can enhance speakers' ability to communicate ideas powerfully.ChatGPT and the Future of Work - Clark Boyd
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The document provides an overview of generative AI, particularly focusing on ChatGPT and its implications for business and the job market. It discusses the rapid growth of generative AI, its applications in marketing, and the skills needed for the AI era while addressing potential job displacement and the need for adaptation. The agenda includes a Q&A session and emphasizes rethinking work in collaboration with AI technology.Getting into the tech field. what next
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The document provides career advice for getting into the tech field, including:
- Doing projects and internships in college to build a portfolio.
- Learning about different roles and technologies through industry research.
- Contributing to open source projects to build experience and network.
- Developing a personal brand through a website and social media presence.
- Networking through events, communities, and finding a mentor.
- Practicing interviews through mock interviews and whiteboarding coding questions.Google's Just Not That Into You: Understanding Core Updates & Search Intent
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1. Core updates from Google periodically change how its algorithms assess and rank websites and pages. This can impact rankings through shifts in user intent, site quality issues being caught up to, world events influencing queries, and overhauls to search like the E-A-T framework.
2. There are many possible user intents beyond just transactional, navigational and informational. Identifying intent shifts is important during core updates. Sites may need to optimize for new intents through different content types and sections.
3. Responding effectively to core updates requires analyzing "before and after" data to understand changes, identifying new intents or page types, and ensuring content matches appropriate intents across video, images, knowledge graphs and more.How to have difficult conversations
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The document provides essential tips on how to handle difficult conversations in a workplace setting, emphasizing the importance of preparation, environment, and timing. It highlights that many employees dread such conversations, often leading to avoidance and worsening situations. Ultimately, the guide aims to promote positive outcomes while maintaining professional relationships.Introduction to Data Science
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The document discusses the rise and importance of data science and machine learning, highlighting the growing demand for data scientists and the challenges they face. It explains machine learning concepts such as supervised and unsupervised learning, along with various real-world applications and the necessary steps involved in a machine learning workflow. Additionally, the document emphasizes the iterative process of model improvement and feature engineering used to enhance machine learning outcomes.Artificial Intelligence, Data and Competition ¨C SCHREPEL ¨C June 2024 OECD dis...
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