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    • AI set to revolutionize medical field with new tools like Microsoft's CopilotAI tools like Microsoft's Copilot are transforming the medical field, while YouTube invests in AI for content creation. However, some skills may become obsolete. Stay informed and learn AI usage daily.

      Artificial Intelligence (AI) is making significant strides in various sectors, including the medical field, and is poised to revolutionize medical knowledge and clinical trials. Microsoft's Copilot, a new AI tool, is set to be released on November 1st, bringing advanced AI functionalities to desktops. This could potentially surpass the impact of chat GPT. YouTube is also investing heavily in AI, launching new tools to simplify content creation. However, some skills, particularly technology and business operational skills, may become obsolete due to AI. The CEO of Indeed warns that these skills are at the highest risk, but also emphasizes that AI can help people land jobs if used effectively. To stay informed and learn how to use AI in daily life, tune in to Everyday AI daily at 7:30 AM Central Standard Time.

    • Turning complex research into meaningful conclusions for medical practice guidelinesFreelance medical writer Lefteris Teparakides compiles and analyzes clinical trials to create evidence-based guidelines, which significantly influence doctors' treatment decisions, despite the time-consuming process

      Freelance medical writer, Lefteris Teparakides, plays a crucial role in turning complex scientific research into meaningful conclusions for clinical practice guidelines. As a pharmacist and systematic review specialist, Lefteris compiles and analyzes clinical trials using validated methods to reach conclusions that influence medical recommendations. These guidelines, based on systematic reviews, are essential for doctors to determine the best treatment options for their patients. The process is time-consuming, with a systematic review taking up to a year to complete and guidelines being published two years after the research is finished. Despite the delay, these evidence-based guidelines form the foundation of modern medical practice.

    • AI's impact on healthcare researchAI can expedite clinical research, reduce approval times, and provide up-to-date clinical practice guidelines, but concerns about job loss persist within the medical community

      AI has the potential to revolutionize the healthcare industry by expediting the clinical research process and reducing approval times for medications, medical devices, and in vitro diagnostics. This could lead to quicker access to novel treatments and more up-to-date clinical practice guidelines for physicians worldwide. However, despite these benefits, there is a split opinion within the medical community about integrating generative AI into this process. Some fear that it may take away jobs, leading to resistance from the medical writing community. It's important to note that while AI can assist in tasks such as systematic reviews, it doesn't necessarily replace human expertise and judgment. Instead, it can be used as a tool to augment and enhance human capabilities, ultimately leading to better patient care and outcomes.

    • AI in systematic reviews: Controversy and ConcernsDespite potential benefits, controversy surrounds AI use in systematic reviews due to concerns over job loss and unreliability. As more validated and reliable AI tools emerge, resistance is expected to lessen, but education and resources are necessary to address concerns.

      The use of AI in systematic reviews is a topic of controversy within the medical writing community. While some see the potential for automation to streamline the process and improve efficiency, others express concerns over job loss and unreliability. The fear of losing jobs is a valid concern, but the same people who voice this worry also acknowledge the argument that AI tools are currently unreliable. This contradiction highlights a lack of understanding and experience with these tools. As more validated and reliable AI tools emerge, it's expected that more medical writers will begin to explore their use. However, the current denial and resistance to AI adoption is significant, and it's important to acknowledge both the potential benefits and risks. As an advocate for AI, it's crucial to find a balance between promoting its advantages and addressing the valid concerns of the medical community. This includes educating and providing resources for those who are hesitant or unfamiliar with AI technology. Ultimately, the goal should be to harness the power of AI to improve the efficiency and accuracy of systematic reviews, while minimizing the risks and ensuring the preservation of the human touch in medical writing.

    • Validating new tools and technologies, including AI models, is crucialUndergo rigorous testing and validation to understand strengths, weaknesses, and full picture of output. Establish trust between users and tools, fostering effective collaboration.

      Validating new tools and technologies, including AI models like ChatGPT, is crucial for ensuring their effectiveness and trustworthiness. This was emphasized during a discussion between Jordan, the host of Everyday AI, and Lindy, an educational consultant. Lindy shared her experience of taking the Priming, Prompting, and Polishing (PPP) course to improve her use of ChatGPT, highlighting the importance of correct priming and prompting. In the medical field, new treatments undergo rigorous testing through clinical trials before being approved. Similarly, tools and technologies, including AI models, need to be validated to understand their strengths, weaknesses, and the full picture of their output. This validation process can help establish trust between users and these tools, allowing them to work together more effectively. This validation process is not only important for the medical community but for everyone. By running these tools through various tests and publishing the results, we can better understand their capabilities and limitations, fostering a more peaceful coexistence between humans and technology.

    • Testing AI's accuracy with hidden informationWhile AI can help manage biases in clinical trial systematic reviews, it's crucial to validate results and recognize that human biases exist and impact research communities differently.

      While using generative AI tools in business processes, it's crucial to validate the results and be aware of potential biases. Hiding irrelevant information in documents is an easy way to test the AI's accuracy. In the context of clinical trial systematic reviews, human and AI-generated biases exist, but AI's predictability offers an advantage in identifying and handling biases more effectively than dealing with the varying biases among human researchers. However, it's important to remember that AI is not bias-free. Systematic reviews addressing diverse populations' impacts in clinical trials are improved by ensuring diversity is considered during the trial phase itself. Cecilia's question about the consideration of diverse populations in clinical trials highlights the importance of addressing this issue earlier in the research process. While generative AI can help in predicting and managing biases, it's essential to recognize that human biases are inherent in any research community, and their impact can vary.

    • AI's Impact on Medical Writing and Systematic ReviewsAI streamlines medical writing, increases efficiency, and improves accuracy in systematic reviews. Its broader impact on healthcare includes personalized treatment plans and accelerated drug development.

      While AI can assist in various aspects of medical research, particularly in data analysis and information retrieval, its role in the systematic review process is limited. This is because the systematic review process relies on primary data from clinical trials, which must be completed before the review can begin. However, AI's impact on medical writing, including systematic reviews, is significant, as it can help streamline the process, increase efficiency, and improve accuracy. Regarding the broader question of where AI will have the most profound impact in healthcare, it's important to note that both direct patient care and research and writing will benefit greatly. AI's ability to analyze vast amounts of data and provide personalized treatment plans, as well as its potential to accelerate the discovery and development of new treatments and medicines, make it a game-changer in healthcare. For medical writers, specifically those involved in systematic reviews, the key takeaway is that AI is already making a significant impact on the field, and it's essential to stay informed and adapt to these changes to remain competitive and effective in their roles. Ultimately, the goal of AI in healthcare is to improve patient care, whether it's through more accurate diagnoses, personalized treatment plans, or faster drug development.

    • Revolutionizing Systematic Reviews with AIAI technology will significantly reduce the time required for data reporting and analysis in systematic reviews, allowing for more time interpreting data and gaining insights.

      AI technology is set to revolutionize the way we conduct systematic reviews in various industries, including pharma, by significantly reducing the time required for data reporting and analysis. Currently, the process can take up to 12 months to complete, but with AI, we can expect to spend more time interpreting data and gaining insights rather than performing legwork. This shift will lead to a more efficient and productive systematic review process, allowing us to answer questions and gain valuable insights more quickly. If you're not already familiar with this topic, it's worth noting that AI is making a significant impact on our daily lives, and staying informed about its advancements is essential. To learn more about this and other AI-related topics, be sure to sign up for the Everyday AI daily newsletter and explore the extensive AI learning tracks available on their website. Don't miss out on the latest AI magic – join us for another episode of Everyday AI soon!

    Recent Episodes from Everyday AI Podcast – An AI and ChatGPT Podcast

    EP 284: Building A Human-Led, AI-Enhanced Justice System

    EP 284: Building A Human-Led, AI-Enhanced Justice System

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    When we talk about AI, it's always about efficiency, more tasks, more growth. But when it comes to the legal system, can AI help law firms with impact and not just efficiency? Evyatar Ben Artzi, CEO and Co-Founder of Darrow,  joins us to discuss how AI can enhance the legal landscape.

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan and Evyatar questions on AI in the justice system

    Related Episode: Ep 140: How AI Will Transform The Business of Law

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
    Connect with Jordan on LinkedIn

    Topics Covered in This Episode:
    1. Use of generative AI in the legal system
    2. Use of LLMs in the legal system
    3. AI's impact on efficiency in the legal industry

    Timestamps:
    01:20 Daily AI news
    04:35 About Evyatar and Darrow
    06:16 Challenges accessing information for lawyers
    09:27 AI efficiency movement is responsible for workload.
    10:24 AI revolutionizing legal world for success.
    16:51 Efficiency affects law firm's ability to bill.
    21:30 Improving mental health in legal profession with agility.
    26:55 Loss of online communities raises concerns about memory.
    27:58 Law firms pursuing right to be remembered.

    Keywords:
    Generative AI, Legal System, Impact, Efficiency, AI News, Perplexity AI, Ultra Accelerator Link, NVIDIA, Apple, OpenAI, Siri, GPT Technology, Evyatar Ben Artzi, Darrow, Justice Intelligence Platform, Case Analysis, Herbicides, Pesticides, Cancer Rates, Large Language Models, ChatGPT, Right to be Remembered, Internet Deletion Practices, Fortune 500 Companies, Legal Industry, Billable Hours, Strategic Thinking, Legal Development, Mental Health, Multiverse in Law.

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    EP 283: WWT's Jim Kavanaugh GenAI Roadmap for Business Success

    EP 283: WWT's Jim Kavanaugh GenAI Roadmap for Business Success

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    Businesses are working out how to use GenAI in the best way. One company that's acing it? World Wide Technology. WWT's CEO, Jim Kavanaugh, is sharing their plan for implementing GenAI into business smoothly.

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan and Jim questions on GenAI

    Related Episodes:
    Ep 197: 5 Simple Steps to Start Using GenAI at Your Business Today
    Ep 146: IBM Leader Talks Infusing GenAI in Enterprise Workflows for Big Wins

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
    Connect with Jordan on LinkedIn

    Topics Covered in This Episode:
    1. Impact of Generative AI
    2. Role of GenAI in World Wide Technology
    3. AI Adoption for Business Leaders
    4. Large Language Models and AI Impact
    5. Challenges in the Generative AI Space
    6. Organization Culture and AI Implementation

    Timestamps:
    01:30 About WWT and Jim Kavanaugh
    06:59 Connecting with users for effective AI.
    10:06 Advantage of working with NVIDIA for digital transformation.
    13:10 Discussing techniques and client example.
    18:35 CEOs implementing AI, seeking solutions.
    20:46 Creating awareness, training, and leveraging technology efficiently.
    25:27 AI increasingly important, impacts all industries' outcomes.
    27:18 Use secure, personalized language models for efficiency.
    32:32 Streamlining data access for engineers and sales.
    35:42 CEOs need to prioritize technology and innovation.
    37:02 NVIDIA is the game-changing leader.

    Keywords:
    generative AI, challenges of AI implementation, Jim Kavanaugh, CEO, Worldwide Technology, digital transformation, value-added reseller, professional services, comprehensive solution, AI strategies, NVIDIA, OpenAI's ChatGPT, large language models, GenAI, Advanced Technology Center, data aggregation, real-time data access, intelligent prompts, business leaders, AI technologies, data science, Jensen and NVIDIA, multimodal languages, AI-first organization, financial performance, go-to-market strategies, software development efficiency, RFP process

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    EP 282: AI’s Role in Scam Detection and Prevention

    EP 282: AI’s Role in Scam Detection and Prevention

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    If you think you know scammers, just wait.
     
    ↳ Voice cloning will fool the best of us.
    ↳ Deepfakes are getting sophisticated.
    ↳ Once-scammy emails now sound real.
     
    How can AI help? In a lot of ways. Yuri Dvoinos, Chief Innovation Officer at Aura, joins us to discuss AI's role in scam detection and prevention.
     
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    More on this Episode: Episode page
    Join the discussion: Ask Jordan and Yuri questions on AI and scam detection

    Related Episodes: Ep 182: AI Efficiencies in Cyber – A Double-Edged Sword
    Ep 202: The Holy Grail of AI Mass Adoption – Governance

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
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    Topics Covered in This Episode:
    1. Sophistication of AI in Scams
    2. Countermeasures to Combat AI Scams
    3. Deepfakes and Their Increasing Prevalence

    Timestamps:
    01:20 Daily AI news
    04:45 About Yuri and Aura
    07:32 Growing impact of impersonation and trust hacking.
    12:35 Consumer app with state-of-the-art protection.
    13:48 New technology scans emails to protect users.
    19:36 Need for awareness of sophisticated multi-platform scams.
    20:33 Be cautious of potential multichannel scams
    26:44 Scams are getting sophisticated, AI may worsen.
    30:05 Different organizations need varying levels of security.
    31:25 Deepfakes raise concerns about truth and trust.
    34:47 It's hard to detect scam communication online.

    Keywords:
    AI Scams, Jordan Wilson, Yuri Dvoinos, Deepfakes, AI Technology, Verification System, Online Interactions, Cyberattacks, Business Security, Scam Detection, Communication Channel Verification, Language Models, AI impersonation, Small Business Scams, Scammer Automation, Aura, Message Protection Technology, Call Analysis, Email Scanning, Voice Synthesizer Technology, Multichannel Scams, 2FA, Cybersecurity Training, Digital Trust, Cybersecurity, Sophisticated Corporate Scams, OpenAI, NVIDIA, Aura Cybersecurity Company, Online Safety.

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    EP 281: Elon Musk says AI will make jobs 'optional' – Crazy or correct?

    EP 281: Elon Musk says AI will make jobs 'optional' – Crazy or correct?

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    Will AI make jobs... optional? Elon Musk seems to think so. His comments struck a chord with some. And rightfully so. As polarizing as Elon Musk can be, does he have a point? Let's break it down.
     
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    More on this Episode: Episode page
    Join the discussion: Ask Jordan questions on AI and jobs

    Related Episodes: Ep 258: Will AI Take Our Jobs? Our answer might surprise you.
    Ep 222: The Dispersion of AI Jobs Across the U.S. – Why it matters

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
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    Topics Covered in This Episode:
    1. Elon Musk's statement and its implications
    2. Future of work with AI advancements
    3. AI's impact on human purpose and employment
    4. Job displacement and AI investment over human employment

    Timestamps:
    01:40 Daily AI news
    07:47 Exploring the implications of generative AI.
    10:45 Concerns about AI impact on future jobs
    13:20 Elon Musk's track record: genius or random?
    17:57 Twitter's value drops 72% to $12.5B.
    22:34 Elon Musk predicts 80% chance of job automation.
    25:54 AI advancements may require universal basic income.
    29:03 AI systems rapidly advancing, surpassing previous capabilities.
    32:11 Bill Gates worries about AGI's misuse.
    35:04 AI advancements foreshadowing future efficiency and capabilities.
    39:42 Ultra-wealthy and disconnected elite shaping AI future.
    43:32 AI will dominate future work, requiring adaptation.
    46:19 US government may not understand future of work.

    Keywords:
    Elon Musk, AI, XAI, funding, chatbot, Grok, OpenAI, legal battle, Apple, Siri, integration, core apps, model, capabilities, safety, speculation, future, work, Tesla, market cap, value, investor sentiment, vision, promises, performance, Viva Tech, conference, robots, job market, society, purpose.

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    EP 280: GenAI for Business - A 5-Step Beginner's Guide

    EP 280: GenAI for Business - A 5-Step Beginner's Guide

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    Everyone is trying to wrap their heads around how to get GenAI into their business. We've had chats with over 120 experts and leaders from around the globe, including big companies, startups, and entrepreneurs. We're here to give you the lowdown on how you can start using GenAI in your business today.

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    More on this Episode: Episode page
    Join the discussion: Ask Jordan questions on AI

    Related Episodes:Ep 189: The One Biggest ROI of GenAI
    Ep 238: WWT’s Jim Kavanaugh Gives GenAI Blueprint for Businesses

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
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    Topics Covered in This Episode:
    1. AI in Business
    2. Implementing AI
    3. AI Guidelines and Guardrails
    4. Practical Application of AI

    Timestamps:
    02:00 Daily AI news
    06:20 Experienced in growing companies of all sizes
    11:45 AI not fully implemented yet
    19:13 Generative AI changing workforce dynamics, impact discussion.
    21:32 Rapidly adapt to online business, seek guidance.
    31:19 AI guardrails and guidelines
    34:25 Companies overcomplicating generative AI, driven by peer pressure.
    37:45 Focus on measurable impact in AI projects.
    45:17 Leverage vendors and experts for AI education.
    51:48 AI may replace jobs - plan for future.
    54:48 Ethical AI implementation involves human and AI cooperation.
    01:00:42 Culmination of extensive work to simplify generative AI.

    Keywords:
    AI training, Employee education, Generative AI tools, Communication skills, Job displacement, AI implementation, Business ethics, AI in business, Guidelines for AI, Data Privacy, AI statistics, Transparency in AI, Bottom-up approach,  AI impact on work, Everyday AI Show

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    Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

    EP 279: Google’s New AI Updates from I/O: the good, the bad, and the WTF

    EP 279: Google’s New AI Updates from I/O: the good, the bad, and the WTF

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    Did Google say 'AI' too many times at their I/O conference? But real talk – it's hard to make sense of all of Google's announcements. With so many new products, updated functionality, and new LLM capabilities, how can you make sense of it all?  Oh.... that's what we're for.

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan questions on Google AI

    Related Episode:  Ep 204: Google Gemini Advanced – 7 things you need to know

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
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    Topics Covered in This Episode:
    1. Google's Updates and Announcements
    2. Google AI Evaluations
    3. Concerns Over Google's AI Development and Marketing

    Timestamps:
    01:30 Daily AI news
    05:30 What was announced at Google's I/O
    09:31 Microsoft and Google introduce AI for teams.
    12:38 AI features not available for paid accounts.
    16:12 Doubt Google's claims about their Gemini model.
    19:26 Speaker live-drew with Pixel phone, discussed code.
    22:24 Exciting city scene, impressive Vio and Astra.
    24:44 Gems and GPTs changing interactions with language models.
    29:26 Accessing advanced features requires technical know-how.
    33:45 Concerns about availability and timing of Google's features.
    36:14 Google CEO makes joke about overusing buzzwords.
    41:06 Google Gems: A needed improvement for Google Gemini.
    41:50 GPT 4 ranks 4th behind Windows Copilot.

    Keywords:
    Google IO conference, AI updates, NVIDIA revenue growth, Meta acquisition, Adapt AI startup, OpenAI deal, News Corp, Project Astra, Gemini AI agent, Gemini 1.5 pro, Ask photos powered by Gemini, Gemini Nano, Android 15, GEMS, Google AI teammate, Microsoft team copilot, Google Workspace, Google search, Veo, Imagine 3, Lyria, Google's AI music generator, Wyclef Jean, Large language models, GPT 4.0, Google Gemini, AI marketing tactics, Deceptive marketing, Discoverability issues, Branding issues.

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    EP 278: Microsoft Build AI Recap - 5 things you need to know

    EP 278: Microsoft Build AI Recap - 5 things you need to know

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    To end a week-ish full of AI happenings, Microsoft has thrown all kinds of monkey wrenches into the GenAI race. What did they announce at their Microsoft Build conference? And how might it impact you? Our last takeaway may surprise you.

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan questions on Microsoft AI

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
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    Topics Covered in This Episode:
    1. Microsoft Build Conference Key AI Features
    2. Microsoft Copilot Updates
    3. On-device AI and its future

    Timestamps:
    01:50 Startup Humane seeks sale amid product criticism.
    09:00 Using Copilot increases latency and potential errors.
    11:15 Copilot changing work with edge AI technology.
    13:51 Cloud may be more secure than personal devices.
    19:26 Recall technology may change required worker skills.
    20:24 Semantic search understands context, improving productivity.
    28:41 Impressive integration of GPT-4 in Copilot demo.
    31:41 New Copilot technology changes how we work.
    36:13 Customize and deploy AI agent to automate tasks.
    38:08 Uncertainty ahead for enterprise companies, especially Apple.
    46:09 Recap of 5 key announcements from build conference.

    Keywords:
    Microsoft CEO, Satya Nadella, Copilot stack, personal Copilot, team's Copilot, Copilot agents, Copilot Studio, Apple ecosystem, enterprise companies, Microsoft Teams, OpenAI, Jordan Wilson, Microsoft Build Conference, edge AI, Copilot Plus PC, recall feature, gpt4o capabilities, iPhone users, AI technology, data privacy and security, GPT 4 o desktop app, AI systems, recall, mainstream AI agents, Humane AI, Scarlett Johansson, ChatGPT, Anthropic Claude, COPilot Studio Agent, Microsoft product.

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    EP 277: How Nonprofits Can Benefit From Responsible AI

    EP 277: How Nonprofits Can Benefit From Responsible AI

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    Generative AI offers significant benefits to nonprofits. What obstacles do they encounter, and how can they utilize this innovative technology while safeguarding donor information and upholding trust with stakeholders? Nathan Chappell, Chief AI Officer at DonorSearch AI, joins us to explore the responsible use of AI in the nonprofit sector.

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    More on this Episode: Episode page
    Join the discussion: Ask Jordan and Nathan questions on AI and nonprofits

    Related Episodes:
    Ep 105: AI in Fundraising – Building Trust with Stakeholders
    Ep 148: Safer AI – Why we all need ethical AI tools we can trust

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
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    Timestamps:
    01:50 About Nathan and DonorSearch AI
    05:52 Decreased charity giving, AI aids nonprofit efficiency.
    09:39 AI enhances nonprofit efficiency, prioritizes human connections.
    13:35 Nonprofits need to embrace AI for advancement.
    16:22 Use AI to create engagement stories, scalable.
    18:59 Internet equalized access to computing power.
    25:02 Nonprofits rely on trust, need responsible AI.
    29:52 Ensuring trust and accountability in generative AI.
    33:35 AI is about people leveling up work.
    34:16 Daily exposure to new tech terms essential.

    Topics Covered in This Episode:
    1. Impact of Generative AI for Nonprofits
    2. Digital Divide in Nonprofit Sector
    3. Role of Trust in Nonprofits and responsible AI usage
    4. Traditional Fundraising vs. generative AI
    5. Future of AI in Nonprofits

    Keywords:
    Nonprofits, generative AI, ethical use of AI, Jordan Wilson, Nathan Chappell, DonorSearch AI, algorithm, gratitude, machine learning, digital divide, AI employment impact, inequality, LinkedIn growth, Taplio, trust, Fundraising AI, responsible AI, AI explainability, AI accountability, AI transparency, future of nonprofits, AI adaptation, predictive AI, personalization, data for donors, generosity indicator, precision and personalization, AI efficiency, human-to-human interaction, AI tools.

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    EP 276: AI News That Matters - May 20th, 2024

    EP 276: AI News That Matters - May 20th, 2024

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    OpenAI and Reddit’s data partnership, will Google’s AI plays help them catch ChatGPT, and what’s next for Microsoft?  Here's this week's AI News That Matters!

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan questions on AI

    Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup
    Website: YourEverydayAI.com
    Email The Show: info@youreverydayai.com
    Connect with Jordan on LinkedIn

    Topics Covered in This Episode:
    1. Key Partnerships and Deals in AI
    2. Google's New AI Developments
    3. Microsoft's Upcoming Developer Conference
    4. Apple's Future AI Implementation

    Timestamps:
    02:00 Reddit partners with OpenAI for AI training, content.
    04:28 Large companies lack transparency in model training.
    06:58 Reddit becoming preferred search over Google, value in partnerships.
    12:08 OpenAI announced GPT 4 o and new feature.
    14:48 Google announced live smart assistance, leveraging AI.
    18:19 Customize data/files, tap into APIs, virtual teammate.
    21:06 Impressed by Google's new products and features.
    26:33 Apple to use OpenAI for generative AI.
    29:08 Speculation around AI safety, resignation raises questions.
    32:22 Concerns about OpenAI employees leaving is significant.
    34:20 Google and Microsoft announce AI developments, drama at OpenAI.

    Keywords:
    Jan Leakey, smarter than human machines, Reddit, OpenAI, data deal, model training, Google, AI project Astra, Microsoft's Build developer conference, AI developments, Apple partnership, safety concerns, everydayai.com, Ask Photos, Gemini Nano, Android 15, AI powered search, Gemini AI assistant, Google AI teammate, Microsoft developer conference, Copilot AI, AI PCs, Intel, Qualcomm, AMD, Seattle, Jordan Wilson, personal data, Reddit partnership, Google IO conference.

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    EP 275: Be prepared to ChatGPT your competition before they ChatGPT you

    EP 275: Be prepared to ChatGPT your competition before they ChatGPT you

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    If you're not gonna use AI, your competition is. And they might crush you. Or, they might ChatGPT you. Barak Turovsky, VP of AI at Cisco, gives us the best ways to think about Generative AI and how to implement it. 

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    More on this Episode: Episode Page
    Join the discussion: Ask Jordan and Barak questions on ChatGPT

    Related Episodes: Ep 197: 5 Simple Steps to Start Using GenAI at Your Business Today
    Ep 246: No that’s not how ChatGPT works. A guide on who to trust around LLMs

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    Topics Covered in This Episode:
    1. Large Language Models (LLMs) and Business Competitiveness
    2. Understanding LLMs for Small to Medium-Sized Businesses
    3. Use Cases and Misconceptions of AI
    4. Data Security and Privacy

    Timestamps:
    01:35 About Barak and Cisco
    05:44 AI innovation concentrated in big tech companies.
    07:14 Large language models can revolutionize customer interactions.
    12:01 ChatGPT fluency doesn't guarantee accurate information.
    13:41 Considering use cases over two dimensions
    18:16 OLM is good fit for specific industries.
    21:17 Emphasizing the importance of large language models.
    23:20 Maintaining control over unique AI model elements.
    28:50 Questioning the data use in large models.
    31:27 Barak discusses leveraging AI for various use cases.
    33:50 Industry leader shared great insights on AI.

    Keywords:
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