The Daily AI Show

Nicole is a CMO AI advisor and thought leader with over 20 years of marketing experience. Nicole's Background - Grew up in Colorado, then moved to Atlanta as a preteen which taught adaptability. - Was a Division 1 swimmer in college which taught persistence and putting in consistent work. - Founded an ecommerce chocolate company in the early 2000s before tools like Shopify existed. Had to build custom solutions. - Worked for a B2B SaaS company heading marketing which translated a lot of ecommerce skills. Leveraging AI in Marketing - Don't think marketers who embrace AI are at risk - it's those who refuse to adopt it. - Important to start learning early when additions are small and integrate them slowly. - Can secure job stability by staying ahead of AI advancements. Sharing AI Knowledge - Nicole shares 90% of what she knows publicly, but customizes the last 10% when working directly with companies. - Started a TikTok channel to share AI learnings which now has 13,000+ followers. - Uses stories to help people connect concepts to deployment. Working with Companies - Nicole trains marketing teams at companies from Series A to Fortune 50 on leveraging AI. - Specializes in B2B SaaS but works with all types of companies. - Focuses on understanding needs and customizing AI training. You can find Nicole https://nicoleleffer.com/ https://www.linkedin.com/in/nicoleleffer/ https://www.tiktok.com/@nicoleleffer/

In this episode, Brian, Beth, Karl, and Robert explored a variety of AI developments and their implications for business and society. Key Points Discussed: Microsoft Copilot in Business: The conversation opened with Microsoft introducing Copilot in their product suite. The panelists debated its potential to automate business operations and its impact on job roles, emphasizing the importance of training for effective utilization. AI's Role in Advertising: The team discussed Google's decision to cut jobs in its ad sales team, signifying AI's growing influence in ad sales and management. This highlighted the transformation in the advertising sector, driven by AI's efficiency and reduced need for human intervention. Healthcare Innovations with AI: The excitement was palpable when discussing Google's AI tool, Amy, designed for medical diagnoses. The tool's ability to ask intelligent questions and reason through symptoms illustrated the significant role AI can play in enhancing healthcare. Additional Discussions: The episode also touched upon other fascinating topics, including a new AI model by Stability AI capable of operating offline without a GPU, AI models learning to deceive humans, and the ethical implications of AI in the context of upcoming elections. AI in Consumer Products: The team briefly touched on Apple's decision to move its Siri team to Texas and its implications, as well as Elon Musk's focus on AI and robotics in Tesla. AI's Impact Across Sectors: Throughout the episode, there was a continuous theme of how AI is reshaping various industries – from business and healthcare to advertising and consumer products.

In this episode, Beth, Karl, Eran, and Brian had a discussion sparked by Pennsylvania's pilot program for Commonwealth employees which aims to utilize generative AI in government operations responsibly. Key Points Discussed Adoption of AI in Government Settings: The panel explored various national approaches to incorporating AI in government processes. International Perspectives: Australia: The conversation revealed Australia's cautious approach to AI adoption, with limited current applications and initiatives like the National Artificial Intelligence Center in the science sector. Canada: Canada's approach includes a comprehensive AI policy, focusing on responsible and ethical use of AI in federal institutions, excluding some like the Canada Revenue Agency. AI in Education and the Role of Unions: The team also discussed AI's impact on education, particularly in terms of policy and implementation. They addressed concerns like plagiarism and the proper use of AI tools in educational settings. Additionally, the potential implications of AI on government employment and unionized roles were considered, with AI's efficiency possibly leading to changes in workforce dynamics. The Future of AI in Government: The co-hosts expressed optimism about AI's potential to improve efficiency and service quality in government, while also acknowledging the challenges in policy making and implementation due to the rapid evolution of AI technologies.

In today's show, Beth, Karl, Brian, Eran, and Robert discussed the newly released 'ChatGPT for Teams' feature. The conversation revolved around its functionality, advantages, limitations, and the potential impact on businesses and individual users. Key Points Discussed Introduction of ChatGPT for Teams: OpenAI's latest offering aims to facilitate better collaboration and AI integration for business teams. It offers features like increased usage limits and data privacy, catering to the needs of professional environments. Functionality and Limitations: While the concept of 'Teams' is promising, the hosts encountered several practical issues. These include billing complexities, the inability to see custom GPTs created by team members, and other user interface challenges. The discussion highlighted the importance of understanding these limitations before adopting the platform. Pricing Structure and Its Implications: The team examined the pricing model of ChatGPT for Teams, noting that it is separate from individual Plus accounts and entails additional costs. The discussion raised questions about the value proposition of the Teams feature, especially for businesses already using individual Plus accounts. Strategic Implications for Businesses: The conversation also touched upon strategic considerations for businesses. This includes the impact of integrating ChatGPT into business operations, the need for AI literacy among team members, and the potential long-term benefits and drawbacks of relying on a single AI provider like OpenAI. Action Steps for Business Professionals Evaluate the Need: Businesses should assess whether ChatGPT for Teams aligns with their specific requirements and the current state of AI integration within their operations. Consider the Costs: Understand the full cost implications, including the potential need for maintaining both individual and Teams accounts. Embrace AI Literacy: Encourage continuous learning and experimentation with AI tools among team members to leverage the full potential of these technologies. Conclusion While ChatGPT for Teams presents a significant step forward in making AI more accessible and functional for professional teams, this episode underscores the need for caution. Businesses should thoroughly understand the feature's current limitations and costs before integrating it into their workflow. The episode serves as a valuable resource for anyone considering adopting ChatGPT for Teams, providing insights into both its potential and pitfalls.

In this show, Jyunmi, Brian, Andy, and Beth discussed Apple's role in the AI landscape, particularly its anticipated comeback in 2024. The conversation discussed various facets of Apple's AI strategy, including the development of new language models, their AR/VR initiatives, and the company's unique approach to integrating AI into its ecosystem. Key Points Discussed: Apple's Language Models: The team highlighted two major AI projects at Apple - the AJAX framework for creating an Apple-specific GPT model, and a multimodal LLM developed with Columbia University focusing on spatial recognition, crucial for AR/VR applications. Apple Vision Pro: An in-depth look was given to the Apple Vision Pro, a $3,500 AR/VR headset. It's a standalone device noted for its eye-tracking abilities and lack of reliance on external controllers, representing Apple's forward-thinking in spatial computing. Siri's Evolution and AI Integration: The discussion touched upon the evolution of Siri, Apple's voice assistant, and the challenges in integrating it with more sophisticated AI technologies. The co-hosts speculated about future upgrades that could make Siri smarter and more versatile, possibly leveraging large language models. Apple's Investment in AI: The crew noted Apple's significant investment in AI, including plans to spend $4 billion on AI processors in 2024. This investment is indicative of Apple's commitment to advancing its AI capabilities. User Experience and AI Ecosystem: The episode also covered the importance of user experience in Apple's AI strategy. Apple aims to enhance its ecosystem with AI functionalities that are seamlessly integrated and user-friendly.

In this episode, Brian, Karl, Beth, Jyunmi, and Andy discussed two major announcements from OpenAI: the launch of the custom GPT store and the introduction of ChatGPT for Teams. The episode featured a detailed exploration of both developments, their implications, and potential use cases, especially for businesses. Key Points Discussed: 1. OpenAI's Custom GPT Store: The custom GPT store allows users to create and share their own custom GPTs. Approximately 3 million custom GPTs have been created, with options for public release. Custom GPTs can be specialized for specific tasks or interests, enhancing their utility. The store is a significant step in making custom GPTs more accessible and discoverable. The revenue-sharing model for creators is a notable aspect, though specifics are not yet clear. 2. ChatGPT for Teams: ChatGPT for Teams is a new tier offering, positioned between the Plus and Enterprise options. It allows for collaborative use of GPTs within a team or organization. Key features include a 32K context window, enhanced data privacy, and shared workspaces. This tier aims to cater to small and medium-sized businesses for efficient team collaboration.

In this episode, the crew, including Jyunmi, Beth, Andy, Robert, Brian, and Karl, discussed the most recent developments and news in the world of AI. The show focused on the impact of these advancements on businesses and professional life. News Discussed 1. The Rabbit R1 - AI-Powered Personal Assistant Device: The Rabbit R1, introduced at CES, is a handheld device that utilizes a large action model-based AI to perform tasks for users, such as ordering pizza or booking flights. It stands out due to its unique design, not based on a phone operating system but rather on a language model. The device's introduction to 'true agency' allows it to complete multiple steps before seeking user confirmation. 2. Magic Mirrors: Two types of 'magic mirrors' were discussed: one by Neurologics for health assessments and another by Barracuda for expression analysis. The Neurologics mirror can analyze facial blood flow to measure health metrics, while Barracuda's mirror assesses emotional and mental states, offering responses like guided meditation. 3. AI in Gaming and Legislation: Steam's official stance on AI-developed games opens opportunities for independent developers. The AI Literacy Act presented in Congress signifies a growing focus on AI education and regulation. 4. AI in Healthcare: Paris-based startup NABLA, specializing in AI for healthcare, raised significant funding. Their technology, like Copilot, assists doctors in note-taking and medical reporting. 5. OpenAI's Developments: OpenAI's potential feature for ChatGPT to learn from user chats suggests advancements towards personalized AI interactions. This feature would enable ChatGPT to remember details and preferences over time, tailoring its responses to individual users.

In this episode, the DAS crew; Jyunmi, Beth, Andy, and Brian, discussed the "Wait Equation" in AI investments. The concept, inspired by a tweet from Ethan Malek, explores whether businesses should immediately invest in AI technologies or wait for advancements that could offer more efficient solutions. Key Points Discussed Origin of the Wait Equation: The idea stems from deep space exploration, questioning if waiting for better technology could result in more efficient outcomes. Application to AI: The hosts examine how this concept applies to AI, with contrasting views on whether companies should invest now or wait for future advancements. Importance of Early Education and Experimentation: A recurring theme is the significance of educating teams about AI and experimenting with current technologies like chat GPTs. Risk of Obsolescence: The discussion highlights concerns about investing in technologies that might soon become outdated, emphasizing the dynamic nature of AI development. Potential of Self-Initiating Agent Technology: Future developments in AI, such as self-initiating agents, could significantly change the approach to designing AI applications. Balancing Investment and Adaptability: The episode talked about the balance between investing in current AI tools and being adaptable to integrate future advancements. Action Steps for Business Professionals Educate Teams on AI: Encourage ongoing learning about AI technologies and their applications. Experiment with Current Tools: Experiment with tools like chat GPT to understand their capabilities and limitations. Prepare for Rapid Changes: Be ready to adapt quickly to new AI technologies and understand their implications for existing systems and processes. This show underscores the importance of balancing immediate investment with the flexibility to adapt to future technologies, ensuring businesses remain competitive and efficient in the ever-evolving AI landscape.

In this episode, the conversation centered around the rapidly evolving job landscape due to advancements in AI. Hosts, Brian, Beth, Jyunmi, Robert, Karl, and Andy talked about how AI innovations, particularly in big companies like Google, are influencing job security and the changing nature of various roles. Key Points Discussed Layoffs Linked to AI Innovations: The episode opened with a focus on recent layoffs at Google, highlighting a significant reduction in their workforce, particularly in the ad sales department. This move was linked to the company's exploration of AI for operational efficiency. Impact on Small and Medium-Sized Businesses: The panel shifted to discuss how AI is affecting smaller businesses, noting that even these entities are considering how AI can reduce their headcount. The conversation highlighted examples where companies replaced part of their workforce with AI solutions, particularly in customer support and administrative roles. Evolution of Job Roles Due to AI: A critical point of discussion was the evolution of job roles in the face of AI advancements. The panelists noted that while some jobs are being eliminated, others are transforming, requiring a different set of skills, especially in managing and working alongside AI technologies. The Need for Enhanced Skills and Adaptability: It was emphasized that the workforce must adapt by enhancing their skills, particularly in understanding and leveraging AI. The conversation touched on the potential necessity for employees to acquire new skill sets to remain valuable in an AI-driven job market. Societal and Economic Implications: The broader societal and economic implications of AI-driven job shifts were also discussed. Concerns were raised about the pace of technological change and whether the workforce could adapt quickly enough. Wrap Up The episode concluded with a reflection on the fast-paced evolution of AI and its impact on the job market. The crew agreed that adaptability and continuous learning are crucial for professionals to stay relevant. For businesses, the integration of AI presents both challenges and opportunities in workforce management and operational efficiency. The episode serves as a reminder of the ongoing need for individuals and organizations to stay informed and agile in an ever-changing technological landscape.

In this episode, the conversation revolved around the art of prompt engineering in the context of AI language models like ChatGPT, Bard, and Claude. The hosts discuss various aspects of prompt crafting, offering insights into how to effectively communicate with and extract desired responses from these advanced AI systems. Key Points Discussed: Meta Prompting for New Users: The discussion highlights the concept of meta prompting, especially for beginners. This involves asking the AI how to improve a prompt or what instructions would be most effective, thereby teaching the user how to interact more effectively with the AI. Complex Prompts and Few Shot Learning: The hosts delve into handling complex queries and the importance of providing clear, structured instructions, often using few shot learning (providing examples) to guide the AI. Custom GPTs and Prompt Improvement: The conversation touches on the use of custom GPTs (language models tailored for specific tasks or industries) and strategies for continually improving prompts based on AI feedback. Natural Language Use and Iterative Refinement: Emphasis is placed on using natural language when interacting with AI and the necessity of iterative refinement of prompts to achieve desired outcomes. Practical Applications and Tips: The episode provides practical tips for various applications such as sales, email outreach, and content creation, demonstrating how to use AI to enhance productivity and effectiveness in these areas.