Generation AI

By: Ardis Kadiu Dr. JC Bonilla
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  • Summary

  • GenerationAI is the groundbreaking podcast designed exclusively for higher education professionals who are keen to navigate the dynamic world of Artificial Intelligence. In a landscape where AI is rapidly transforming how we teach, learn, and engage, "GenerationAI" serves as your essential guide. Each episode delves into the most pressing AI topics, breaking down complex concepts into understandable, actionable insights. Whether you're a marketer, administrator, or tech enthusiast, this show will illuminate how AI is reshaping the academic experience and what it means for the future of education. Join us as we explore the latest news, trends, and developments in AI. From data-driven decision-making to personalized engagement and learning experiences, and the ethical implications of AI in education, "GenerationAI" covers it all. With expert commentary, in-depth analysis, and a focus on practical applications, this show is dedicated to empowering higher education professionals to leverage AI for strategic advantage. "GenerationAI" isn't just about understanding AI – it's about being part of the AI revolution in education. Tune in, get informed, and be inspired to innovate in your educational space with the power of AI.
    2024 Generative AI - Enrollify Network
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Episodes
  • Beyond the Limits: How AI Models Are Redefining Capabilities

    Beyond the Limits: How AI Models Are Redefining Capabilities
    Nov 19 2024
    In this episode of Generation AI, hosts Ardis Kadiu and JC Bonilla explore the intricate world of AI scaling in higher education. They break down the concept of scaling, from its foundational components to its implications for AI development and implementation. Drawing on real-world examples, they delve into the triad of model size, data, and computational power, and discuss challenges like data scarcity, computational limits, and diminishing returns. The episode also offers insights into how industry leaders like OpenAI, Google, and Meta are tackling these roadblocks.‍Key TakeawaysAI Scaling Defined: Scaling in AI refers to how efficiently and effectively models can accomplish tasks of increasing complexity, measured by speed and intelligence.The Triad of AI Scaling: Model size, data quality, and computational power are the key elements driving AI advancements.Challenges in AI Scaling:Data scarcity, particularly for high-quality, domain-specific datasets.Skyrocketing computational costs and energy requirements.Diminishing returns as larger models yield less exponential improvement.Mitigation Strategies: Techniques like synthetic data generation, hyperparameter tuning, and reasoning-focused models address scaling challenges.Future of AI Models: Companies are shifting focus from generalist models to domain-specific and reasoning-oriented solutions.‍What Does AI Scaling Mean?AI scaling refers to how effectively artificial intelligence can solve increasingly complex tasks. Hosts Ardis Kadu and JC Bonilla explain this through a lens of "smartness"—can a model achieve in minutes, hours, or days what humans might take weeks to accomplish? Scaling doesn’t just mean faster; it also means smarter. For example, GPT-4 is 10 times more capable than GPT-3.5 in many areas, but the diminishing returns of scaling larger models have prompted researchers to rethink strategies.‍What Are the Key Challenges in Scaling AI?The conversation explores three primary challenges in scaling AI:Data Scarcity: High-quality training data is increasingly hard to source. While earlier models relied on vast amounts of freely available online data, this resource has been largely exhausted. Additionally, domain-specific datasets, like those in healthcare or education, are often inaccessible or proprietary.Computational Costs: Training large models costs hundreds of millions—and soon billions—of dollars. Companies face challenges balancing the need for immense computing power with energy efficiency and sustainability.Diminishing Returns: As models grow, they require exponentially more computational resources to achieve only incremental improvements in performance. This raises questions about whether scaling efforts are sustainable.‍How Are Companies Tackling Scaling Challenges?The podcast highlights how leading tech companies are approaching these roadblocks:OpenAI: Focuses on reasoning-based models and test-time compute, allowing AI to think dynamically during task execution.Google: Invests in multimodal capabilities and domain-specific applications, such as its advancements in protein folding and specialized coding models.Meta: Explores alternative architectures and world models, aiming to overcome the limitations of transformer-based AI systems.XAI (Elon Musk's Initiative): Prioritizes "truth-seeking" AI and first-principles problem-solving.‍What Role Do Mitigation Strategies Play?To address the challenges of scaling, companies and researchers are leveraging innovative strategies, including:Synthetic Data Generation: Creating artificial datasets to fill gaps in training data.Hyperparameter Tuning: Optimizing how models learn to improve efficiency.Reasoning-Based Models: Enhancing AI’s ability to think and adapt dynamically during real-time tasks.The hosts share how these approaches are unlocking new possibilities for AI in higher education. For instance, at Element, reasoning-focused AI is being used to identify fraudulent applications by analyzing behavioral patterns and contextual data.‍What Does the Future Hold for AI Scaling?The episode closes with a discussion of where AI is headed. The hosts emphasize that while scaling generalist models may slow, there’s growing momentum around domain-specific applications and reasoning engines. These advancements could revolutionize fields like marketing attribution, student engagement, and personalized learning in higher education. - - - -Connect With Our Co-Hosts:Ardis Kadiuhttps://www.linkedin.com/in/ardis/https://twitter.com/ardisDr. JC Bonillahttps://www.linkedin.com/in/jcbonilla/https://twitter.com/jbonillxAbout The Enrollify Podcast Network:Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too! Some of our favorites include The EduData Podcast and Visionary Voices: The College President’s Playbook.Enrollify is made possible by Element451 — the next-generation AI student ...
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    41 mins
  • Post election AI agenda, Chegg's ChatGPT nightmare, Tech consolidation ahead

    Post election AI agenda, Chegg's ChatGPT nightmare, Tech consolidation ahead
    Nov 12 2024

    In this timely episode of Generation AI, hosts Ardis Kadiu and Dr. JC Bonilla examine how the recent election results could reshape AI's role in higher education. They analyze potential shifts in AI regulation, funding, and innovation under the new administration. The hosts explore how changes in merger policies and efficiency mandates might accelerate AI adoption, while also discussing the cautionary tale of Chegg's dramatic market value loss due to ChatGPT's emergence. This episode offers crucial insights for education professionals navigating the rapidly evolving intersection of politics, AI, and higher education.

    Election Impact on AI Regulation (00:00:07)

    • Introduction of key themes around election results
    • Expected rollback of Biden's AI executive order
    • Shift toward less regulation and oversight of AI development

    Mergers and Innovation in AI (00:07:14)

    • Discussion of potential changes to merger regulations
    • Impact on AI company acquisitions and innovation
    • Analysis of how reduced regulation could benefit AI startups

    Efficiency and Government Reform (00:16:16)

    • Role of AI in government efficiency initiatives
    • Analysis of FAFSA implementation failures
    • Discussion of potential Department of Education reforms

    AI and National Competition (00:24:31)

    • Meta's LLAMA model licensing changes for government use
    • Discussion of US-China AI competition
    • Analysis of semiconductor regulations and AI compute power

    The Chegg Case Study (00:28:44)

    • Detailed analysis of Chegg's market collapse
    • Impact of ChatGPT on education technology
    • Loss of $14.5 billion in market value
    • Failed attempts at AI adaptation

    Future of Educational Content (00:37:26)

    • Discussion of AI's impact on learning management systems
    • Analysis of content generation in education
    • Implications for service providers and agencies
    • Examples of new AI-powered learning platforms

    Closing Thoughts (00:41:13)

    • Summary of key points about AI under new administration
    • Discussion of accelerated technology adoption
    • Final insights on AI's future in education


    - - - -

    Connect With Our Co-Hosts:
    Ardis Kadiu
    https://www.linkedin.com/in/ardis/
    https://twitter.com/ardis

    Dr. JC Bonilla
    https://www.linkedin.com/in/jcbonilla/
    https://twitter.com/jbonillx

    About The Enrollify Podcast Network:
    Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too! Some of our favorites include The EduData Podcast and Visionary Voices: The College President’s Playbook.

    Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.

    Attend the 2025 Engage Summit!
    The Engage Summit is the premier conference for forward-thinking leaders and practitioners dedicated to exploring the transformative power of AI in education. Explore the strategies and tools to step into the next generation of student engagement, supercharged by AI. You'll leave ready to deliver the most personalized digital engagement experience every step of the way.

    Register now to secure your spot in Charlotte, NC, on June 24-25, 2025! Early bird registration ends February 1st -- https://engage.element451.com/register
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    44 mins
  • Gen AI Powered Search - How will ChatGPT Search and Perplexity change SEO?

    Gen AI Powered Search - How will ChatGPT Search and Perplexity change SEO?
    Nov 5 2024
    In this live episode of Generation AI, hosts Ardis Kadiu and JC Bonilla dive into the groundbreaking shifts happening in AI-powered search technology. They discuss how major players like OpenAI, Google, and Meta are driving a paradigm shift in online search. Joined by Ty Fujimura, an expert in UX and SEO, they explore how generative AI is transforming the way users interact with information, from natural language search to real-time personalization. This conversation highlights both the opportunities and challenges for marketers, content creators, and higher education professionals looking to stay ahead in an AI-driven digital landscape.‍Key TakeawaysNatural Language Search: Generative AI enables search without keywords, allowing users to communicate queries conversationally, transforming how they find information.Personalization in Real Time: AI-powered search adapts based on user behavior, location, and even time of day, enabling a more tailored information retrieval experience.The Role of Authentic Content: As AI search engines source information from various platforms, producing authentic, context-rich content across multiple channels is key to maintaining brand presence.Impact on SEO and Website Strategy: Traditional SEO practices are shifting; now, the emphasis is on creating diverse, authoritative content that AI can reference and summarize effectively.Predicted Drop in Organic Traffic: As AI search improves, website visits may decline, making social media and paid search essential for driving traffic and engagement.‍Episode SummaryWhat Is AI-Powered Search, and Why Does It Matter?In this episode, Ardis and JC discuss the evolution of AI-powered search and how it’s disrupting traditional methods of information retrieval. Unlike traditional keyword-based searches, AI-powered search relies on natural language processing, making it more intuitive and conversational. The hosts highlight how tools like ChatGPT, Perplexity, and Google’s Gemini are enabling users to ask complex questions in everyday language, making search experiences feel more interactive and responsive. By bridging the gap between keywords and conversation, AI is setting the stage for a more user-centric internet, particularly significant for higher education and content-driven industries.‍How Does Personalization Transform the Search Experience?AI-powered search isn’t just conversational; it’s also deeply personalized. According to the hosts, AI can now remember preferences and adapt its responses to individual users based on their browsing habits, location, and even the device they use. Ty Fujimura adds that personalization can extend to contextualizing responses based on user history, allowing searches to align more closely with individual needs and timing. For example, if a user often searches for research articles in the morning, AI could prioritize academic sources. The ability to provide such a customized experience makes it vital for marketers to rethink content strategies, ensuring their material remains relevant across varied user contexts.‍How Will AI Change SEO and Content Strategy?With generative AI reshaping search, SEO is evolving from keyword optimization to content diversification and authenticity. Ty suggests that instead of focusing on keywords, website owners and marketers need to emphasize genuine, unique content. AI now aggregates information from multiple sources, including websites, social media, and forums, to deliver comprehensive answers, bypassing the need for users to click on individual links. In the higher education space, this shift means that content must be readily accessible and informative across channels like Substack, Medium, and even Reddit, as AI pulls from these diverse data streams.This trend of reduced organic traffic to websites emphasizes the importance of social media as a branding tool and reinforces the value of paid search to drive user engagement. As AI technologies like Perplexity and ChatGPT enhance user experience with organized, real-time search results, it’s clear that SEO strategies must pivot to include broader content ecosystems and a heightened focus on brand authenticity.‍What Are the Implications for Content Monetization and Advertising?One potential challenge discussed is the future monetization of AI-powered search. As AI search tools from companies like OpenAI, Meta, and Google gain popularity, the ad-free experience may not last indefinitely. JC points out that, much like social media before it, AI search platforms could begin incorporating subtle paid influences, raising questions about transparency and the authenticity of information. In the meantime, brands should capitalize on the ad-free landscape by establishing a solid, authentic content presence across platforms AI frequently references.For marketers, this shift also means strategizing around paid search and social media for direct traffic, as organic traffic from traditional search engines ...
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    41 mins

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