g-f Fishing on the AI Revolution for the Week of 8/31/2024
Introduction
The genioux facts program, with its extensive foundation of over 2838 Big Picture of the Digital Age posts, remains at the forefront of documenting and disseminating cutting-edge knowledge about the AI Revolution. In the week of August 31, 2024, the program has curated a collection of 10 insightful videos that offer exceptional Golden Knowledge (g-f GK) on the advancements, challenges, and opportunities within the field of artificial intelligence. This collection serves as a vital resource for those aiming to navigate and master the rapidly evolving digital landscape.
genioux GK Nugget
"To thrive in the AI Revolution, it's essential to grasp not only the technological innovations but also the strategic implications and ethical considerations that shape our digital future." — Fernando Machuca, ChatGPT, and Gemini, August 31, 2024
genioux Foundational Fact
The curated collection of 10 videos from the genioux facts program provides a comprehensive overview of the current state of the AI Revolution. These videos explore diverse aspects of AI, including market dynamics, strategic innovations, ethical considerations, and educational impacts. By synthesizing insights from industry leaders, technological pioneers, and academic experts, this collection equips individuals and organizations with the knowledge needed to capitalize on AI's transformative potential while navigating its inherent complexities.
The 10 Most Relevant genioux Facts
- AI Product Strategy: The importance of understanding the evolving AI landscape, focusing on practical applications, and leveraging user experience and distribution for market success.
- Nvidia's Evolution: Nvidia's transformation from a gaming-focused company to a leader in AI hardware, underscores the interconnectedness of different industries.
- Enterprise AI: Aidan Gomez's insights on the transformative potential of generative AI in business, emphasize the importance of privacy, cloud agnosticism, and specific business needs.
- Nvidia's Blackwell Chip: The strategic significance of Nvidia's Blackwell architecture and its role in meeting the global demand for accelerated computing across various sectors.
- AI Chip Startups: Groq's unique approach to AI hardware, focuses on optimizing language processing and inference to make AI technology more accessible and impactful.
- OpenAI's Journey: How OpenAI's transition from a nonprofit to a capped-profit organization, along with strategic partnerships, propelled it to the forefront of the AI industry.
- Google's Custom Chips: The development and impact of Google's custom AI chips, TPUs, and their role in advancing AI capabilities for both Google and Apple.
- Talent Wars in AI: The trend of big tech companies acquiring AI startups for talent and technology, and its implications for innovation and regulatory scrutiny.
- AI in Education: Cynthia Breazeal's vision for AI-powered education, emphasizes personalized learning and AI literacy as critical components for future generations.
- Managing AI Complexity: Chris Howard's insights on balancing the complexity of AI with simplicity in implementation to achieve productivity and innovation.
Conclusion
The collection of videos curated by the genioux facts program for the week of August 31, 2024, offers invaluable insights into the multifaceted world of AI. From strategic innovations and technological advancements to ethical considerations and educational impacts, these videos encapsulate the essence of the AI Revolution. As we navigate this transformative era, it is crucial to stay informed and agile, leveraging Golden Knowledge to master the complexities and seize the opportunities that AI presents. This collection serves as a beacon for those committed to thriving in the g-f New World, where the mastery of AI is key to sustained success.
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The g-f GK Context
The genioux facts program has established a robust foundation of over 2838 Big Picture of the Digital Age posts [g-f(2)1 - g-f(2)2838]. In keeping the state-of-the-art of the AI Revolution updated, we present the collection of 10 videos from g-f Fishing on the AI Revolution for the week of 8/31/2024. This collection features exceptional Golden Knowledge (g-f GK) that provides valuable insights and advancements in the field.
Classical Summary of the Context
The genioux facts program, which has established a comprehensive foundation of over 2,838 posts focused on the Big Picture of the Digital Age, presents a curated collection of 10 videos from the week of August 31, 2024, under the theme of the AI Revolution. This collection is a testament to the program's ongoing commitment to keeping its audience informed about the latest developments and insights in artificial intelligence (AI).
The videos cover a broad spectrum of AI-related topics, including strategic identification of AI opportunities, the transformative role of companies like Nvidia and Cohere in advancing AI technologies, and the impact of AI on industries ranging from gaming to education. Each video offers valuable Golden Knowledge (g-f GK) that highlights the critical advancements, challenges, and opportunities presented by AI in the current digital landscape.
From Nvidia's evolution from a gaming company to a dominant force in AI hardware, to the innovative business models of AI startups like Groq, and the societal implications of AI's rapid growth, the collection provides a diverse set of perspectives and insights. The series also explores the ethical considerations, regulatory challenges, and the future trajectory of AI as it continues to reshape industries and societies worldwide.
This collection not only enriches the understanding of AI's current state but also equips individuals and organizations with the knowledge needed to navigate the ongoing digital transformation. Through these videos, the genioux facts program reinforces its role as a vital resource for mastering the complexities of the AI Revolution and the broader Digital Age.
The Collection of 10 Videos from g-f Fishing on the AI Revolution for the Week of 8/31/2024
Classical Summary of "Stanford Webinar - Identifying AI Opportunities: Strategies for Market Success"
DESCRIPTION
- 15,072 views Aug 26, 2024
- Crafting an AI product strategy? Don’t waste time chasing the latest hype.
- Aditya Challapally (Stanford Online instructor, machine learning expert, and product manager) debunks myths and shares what truly works with Generative AI, backed by insights from over 300 users and 50+ executives.
- In this practical, data-driven webinar, you will:
- Uncover the truth behind common AI misconceptions
- Learn how industry leaders are setting the standard for AI innovation
- Explore the most promising AI opportunities on the horizon
SUMMARY
This webinar by Aditya Challapally, a machine learning engineer and product lead at Microsoft, focuses on identifying and capitalizing on AI opportunities, particularly in the context of generative AI (GenAI).
Key Takeaways:
- GenAI's Trajectory: GenAI is following a similar adoption curve to the internet, and its potential value is immense.
- Technical Understanding: It's important to understand the technical stack and the differences between various types of GenAI applications.
- Investment Opportunities: The democratization of AI models has created new investment opportunities, with the most lucrative being in companies that take existing models and add value through user experience and distribution, rather than model creation itself.
- Personal Success in AI: For business professionals, gaining technical proficiency is crucial for success in the AI-driven world. Understanding AI technologies, data boundaries, and systems architecture, along with the ability to communicate these concepts effectively, can lead to significant career advancement.
- Prioritizing Opportunities: When evaluating GenAI projects, focus on user-facing features that prioritize content consumption and integration into existing products rather than building internal tools or standalone chatbots.
Overall, the webinar emphasizes the importance of understanding the evolving AI landscape, leveraging distribution and user experience, and focusing on practical applications to achieve market success in the age of generative AI.
Classical Summary of "How Nvidia Changed the Game"
DESCRIPTION
- 136,188 views Aug 30, 2024
- From AI-powered cars to crypto and OpenAI’s ChatGPT, tiny Nvidia chips play an outsized role in facilitating our daily routines. Before it became the world’s most valuable chipmaker, worth more than $3 trillion, the company had the more humble calling of manufacturing graphics cards for video game consoles. How will Nvidia further harness the power of its earliest innovation with advanced AI?
SUMMARY
Nvidia, a leading company in artificial intelligence, has its roots in the gaming industry, where it initially designed graphics processing units (GPUs) to render 3D visuals in games. The company's success in gaming enabled it to invest in research and development, leading to the realization that GPUs excel at parallel computing, making them valuable for various non-gaming applications, including oil and gas exploration and weather mapping.
The rise of deep learning and neural networks further fueled Nvidia's growth. GPUs' ability to efficiently process complex mathematical operations made them ideal for training and running AI models, particularly in image and pattern recognition tasks. Nvidia capitalized on this trend, becoming the dominant player in the AI hardware market.
Today, Nvidia's revenue from gaming is dwarfed by its income from data centers and AI applications. The company's diversified portfolio includes AI model development, data center infrastructure, and even streaming services.
While Nvidia's primary focus has shifted from gaming to AI, the gaming industry remains significant and is undergoing rapid evolution. The increasing accessibility of gaming across various devices, including mobile phones, presents new opportunities for growth and innovation.
The video concludes by highlighting the transformative potential of AI and how Nvidia is at the forefront of this revolution, benefiting from the world's exploration of AI's possibilities. It also underscores the interconnectedness of seemingly disparate industries like gaming and AI, showcasing how innovation in one field can lead to unexpected advancements in another.
Classical Summary of "How Cohere CEO Aidan Gomez Says AI Will Directly Profit Companies"
DESCRIPTION
- 35,318 views Jul 7, 2024
- Aidan Gomez is the CEO and co-founder of Cohere and he’s been at the center of generative AI since its early days. He was an intern at Google in 2017 when he helped write the foundational paper that conceptualized the transformer - the tech that makes generative AI possible. Now he’s focused on building generative AI models for companies instead of consumers. CNBC’s Steve Kovach sat down with Gomez to talk about the burgeoning tech and specific ways his models will boost profits for companies.
- Produced by - Katie Tarasov
- Correspondent - Steve Kovach
- Shot by - Beatriz Bajuelos, Tasia Jensen
- Edited by - Marc Ganley
- Supervising Producer - Jeniece Pettitt
- Additional Footage - Cohere, Nvidia
SUMMARY
This video is an interview with Aidan Gomez, the CEO and co-founder of Cohere, a company focused on making AI products for businesses. Gomez was an intern at Google in 2017 when he co-authored the paper that introduced the transformer, the technology behind generative AI.
Key points from the interview:
- Transformer's Origin: The transformer was initially developed to improve Google Translate. The team didn't foresee its broader impact.
- Google's Missed Opportunity: Google may have missed the potential of large-scale AI models due to the risk and investment required.
- Cohere's Focus: Cohere is an enterprise AI platform prioritizing privacy, cloud agnosticism, and addressing specific business needs.
- AI's Value Proposition: AI is now delivering tangible value, driving adoption in both consumer and enterprise sectors.
- Addressing Concerns: Gomez acknowledges concerns about AI's potential risks but emphasizes that the real dangers lie in deploying it in high-consequence scenarios where it's not yet ready.
- Future Outlook: Gomez believes we're still in the early stages of AI adoption and expects significant acceleration in the next two years.
- Advice to Students: He encourages students passionate about AI to immerse themselves in the field and persevere through initial challenges.
- Impact on Business Models: AI is enabling businesses to gain a competitive advantage through increased productivity and efficiency.
The interview concludes with Gomez highlighting the transformative potential of AI and Cohere's commitment to building a sustainable and impactful AI business.
Classical Summary of "Nvidia CEO Jensen Huang on Earnings, Demand and Blackwell Chip (Full Interview)"
DESCRIPTION
- 158,936 views Aug 28, 2024
- Nvidia CEO Jensen Huang defends the rollout of its next-generation Blackwell chips after the company admitted problems with its design. Nvidia failed to live up to investor hopes with its latest results, delivering an underwhelming forecast. Huang spoke exclusively to Bloomberg's Ed Ludlow.
SUMMARY
In this Bloomberg interview, Nvidia CEO Jensen Huang addresses key questions regarding the company's recent earnings, future product demand, and the much-anticipated Blackwell GPU architecture.
Key Takeaways:
- Blackwell Production and Demand: Despite some production adjustments to improve yield, Blackwell is on track for volume production and shipping in Q4. Demand far exceeds supply, and Nvidia expects billions of dollars in Blackwell revenue in Q4, with continued growth in subsequent quarters.
- Demand for Accelerated Computing: Beyond hyperscalers, demand for accelerated computing is strong across various sectors, including internet service providers, sovereign entities, enterprises, and industries. The applications range from generative AI and database processing to scientific simulations and image processing.
- Sovereign AI: Several countries are investing in their AI infrastructure, recognizing that digital data is a national resource. Sovereign AI refers to these government-funded initiatives to build AI capabilities within their borders.
- Energy Efficiency: Nvidia focuses on improving performance efficiency in its next-generation GPUs like Blackwell. Additionally, liquid cooling support further enhances energy efficiency.
- AI Model Evolution: AI models are becoming larger, learning more languages and modalities, and being developed by a wider range of organizations, driving increased demand for Nvidia's products.
- Nvidia GPU Cloud: Nvidia's GPU cloud strategy is to build its cloud within existing cloud platforms, ensuring the best performance and total cost of ownership. Nvidia is a large consumer of its own cloud, using it for AI model development, self-driving cars, robotics, and Omniverse.
- AI Foundry: Nvidia also acts as an AI foundry, helping companies build AI models. This service leverages Nvidia's expertise in AI and its GPU cloud infrastructure.
Overall, the interview highlights Nvidia's strong position in the AI market, driven by increasing demand for accelerated computing and the company's focus on innovation and energy efficiency. It also underscores the global trend of governments investing in AI infrastructure and the expanding applications of AI across diverse industries.
Classical Summary of "The $2.8 Billion AI Startup Taking On Nvidia"
DESCRIPTION
- 51,577 views Aug 19, 2024
- Armed with a newly raised $640 million, Groq CEO Jonathan Ross thinks it can challenge one of the world’s most valuable companies with a purpose-built chip designed for AI from scratch.
SUMMARY
This video is an interview with Jonathan Ross, the CEO of Groq, an AI chip startup valued at $2.8 billion. The company focuses on developing Language Processing Units (LPUs), which are specialized chips designed for sequential processing, making them ideal for language tasks that require understanding context and generating coherent responses.
Key points from the interview:
- Groq's focus: Groq builds LPUs, a type of chip specifically optimized for language processing tasks, unlike GPUs that are better suited for parallel processing.
- Importance of inference: Inference, the process of generating responses to AI queries, is crucial for real-world AI applications and is computationally expensive. Groq aims to make inference cheaper, faster, and more accessible.
- Speed and user experience: Faster inference leads to improved user engagement and enables more complex AI use cases, like agentic workloads where AI performs multiple tasks to achieve a goal.
- Competition and differentiation: Groq competes with established players like Nvidia and other AI chip startups. They differentiate themselves through their focus on LPUs, a cloud-based service model, and an easy-to-use API that integrates with existing code.
- Impact of ChatGPT: The release of ChatGPT significantly boosted Groq's business, as it highlighted the need for faster inference to handle the demands of large language models.
- Challenges and scaling: Groq's biggest challenge is scaling its hardware deployment to meet the growing demand for AI inference capabilities.
- Compute as the new oil: Ross argues that compute, or processing power, is the foundation of the generative age, akin to how oil fueled the industrial age.
- Future of AI: Ross believes we are still in the early days of AI adoption and that it will become an integral part of our daily lives, both at work and in our personal lives.
Overall, the interview provides insights into the fast-growing AI chip industry and highlights Groq's unique approach to addressing the challenges of AI inference. It also emphasizes the importance of speed and accessibility in making AI technology more widely available and impactful.
Classical Summary of "Why ChatGPT Turned OpenAI Into A $80 Billion AI Leader"
DESCRIPTION
- 136,891 views Aug 10, 2024
- The company behind the popular artificial intelligence chatbot, ChatGPT, OpenAI was founded as a nonprofit in 2015 by several researchers, academics, and entrepreneurs including Sam Altman, Greg Brochman, and Elon Musk. Musk left OpenAI in 2018 and now has his own artificial intelligence company called xAI.
- In its early years, OpenAI flew somewhat under the radar, at least from the point of view of the general public. The company released its first project in 2016, a toolkit called “OpenAI Gym” used for developing and comparing reinforcement learning algorithms. That same year, OpenAI also released Universe, a tool to train intelligent agents on websites and gaming platforms. But the release of ChatGPT in 2022 is what propelled the company to stardom. Today, OpenAI is valued at over $80 billion and counts Microsoft, which has invested around $13 billion into OpenAI since 2019, as a major supporter and partner. But OpenAI’s wild success has also raised concerns from regulators and experts who question the outsized power that artificial intelligence companies and Big Tech could have on our society as well as the toll that the technology could take on our power grid.
SUMMARY
The video "Why ChatGPT Turned OpenAI Into A $80 Billion AI Leader" from CNBC provides an in-depth exploration of how OpenAI, the company behind the popular AI tool ChatGPT, became a dominant force in the artificial intelligence industry. The video outlines OpenAI's journey from its founding in 2015 by notable figures such as Sam Altman, Greg Brockman, and Elon Musk, to its current status as a leader in AI development with an $80 billion valuation.
The video explains that OpenAI initially started as a nonprofit with a mission to advance AI in a way that benefits all of humanity. However, the organization later shifted to a capped-profit model to attract more funding and talent, a move that led to significant investments, particularly from Microsoft, which has invested $13 billion in OpenAI to date. This partnership allowed OpenAI to leverage Microsoft's Azure cloud platform, giving it the computing power needed to scale its AI innovations.
The launch of ChatGPT in 2022 marked a turning point for OpenAI, catapulting the company into the public consciousness and making ChatGPT a household name. The video highlights how ChatGPT's ease of use and the timing of its release during a period of heightened interest in AI contributed to its rapid adoption, reaching 100 million monthly users within two months.
OpenAI's advancements in generative AI, including tools like Dall-E 3 for image generation and Sora for video creation, are also discussed. The video touches on the broader implications of AI, including concerns about job displacement, ethical issues, and regulatory scrutiny. Despite these challenges, OpenAI continues to innovate and expand its influence in the tech world, partnering with major corporations and shaping the future of AI.
The video concludes by noting that while there are significant challenges ahead, the rapid pace of AI development and OpenAI's leadership position suggest that AI will continue to play a transformative role in society.
Classical Summary of "How Google Makes Custom Cloud Chips That Power Apple AI And Gemini"
DESCRIPTION
- 299,707 views Aug 23, 2024
- Google was the first cloud provider to make its own custom AI chips, called TPUs when they first came out in 2015 - a trend both Amazon and Microsoft followed years later. Now, Apple has revealed it uses TPUs to train its AI models, positioning Google chips as an alternative to Nvidia's market-leading GPUs. CNBC got an exclusive look inside the lab where Google makes its chips, and its top executive showcased TPU Version 6, Trillium, and its new Arm-based CPU, Axion, both coming out later in 2024.
SUMMARY
This video offers an exclusive look inside Google's chip lab, where they design and test their custom microchips, Tensor Processing Units (TPUs), which power various Google services, including AI models like Gemini, and surprisingly, Apple's AI as well.
Key takeaways:
- Google's TPU journey: Driven by the need for efficient voice recognition, Google started developing TPUs in 2014. These application-specific integrated circuits (ASICs) are more efficient than general-purpose CPUs or GPUs, leading to significant cost and power savings.
- TPUs and AI advancements: TPUs enabled Google to conceive and execute computationally expensive AI algorithms like the transformer, the foundation of generative AI.
- Market competition: Google's early adoption of custom AI chips helped it gain ground in the cloud market, prompting other major players like Amazon and Microsoft to follow suit.
- Collaboration with Broadcom: Google collaborates with Broadcom for chip development, leveraging its expertise in peripheral components and packaging.
- Geopolitical risks: The reliance on Taiwan Semiconductor Manufacturing Company (TSMC) for chip fabrication poses geopolitical risks, but Google is prepared for contingencies.
- Expansion into CPUs: Google recently announced its general-purpose CPU, Axion, aiming to further optimize its infrastructure and reduce reliance on external providers.
- Sustainability challenges: The massive power and water consumption of AI servers is a concern, but Google is committed to improving efficiency and reducing its carbon footprint.
- Looking ahead: Despite challenges, Google remains committed to advancing AI and developing custom chips to meet the growing computational demands of this field.
Overall, the video showcases Google's significant investments in custom chip development, driven by the need for efficiency, performance, and control in the rapidly evolving AI landscape. It also highlights the complex ecosystem of chip development and the geopolitical and environmental challenges associated with it.
Classical Summary of "How Google, Microsoft And Amazon Are Raiding AI Startups For Talent"
DESCRIPTION
- 152,797 views Aug 30, 2024
- Microsoft, Google, and Amazon, along with other tech companies, have been getting creative in how they’re poaching talent from top artificial intelligence startups. Earlier this month, Google inked an unusual deal with Character.ai to hire away its prominent founder, Noam Shazeer, along with more than one-fifth of its workforce while also licensing its technology. It looked like an acquisition, but the deal was structured so that it wasn’t. Google wasn’t the first to take this approach.
- In March, Microsoft signed a deal with Inflection that allowed Microsoft to use Inflection’s models and to hire most of the startup’s staff. Amazon followed in June with a faux acquisition of Adept where it hired top talent from the AI startup and licensed its technology.
- It’s a playbook that skirts regulators and their crackdown on Big Tech dominance provides an exit for AI startups struggling to make money, and allows megacaps to pick up the talent needed in the AI arms race.
- But while tech giants might think they’re outsmarting antitrust enforcers, they could be playing with fire. CNBC’s Deirdre Bosa has the story.
SUMMARY
This video talks about the recent trend of big tech companies acquiring AI startups for talent and technology, but not through traditional acquisitions. Instead, these big tech companies are making deals with AI startups to license their technology and hire away their talent. This way, big tech companies can avoid the scrutiny of regulators while still acquiring the talent and technology they need.
The video discusses three examples of this trend:
- Google and Character AI: Character AI is a startup that develops generative AI technology. Google did not acquire Character AI outright but instead entered into a deal to license Character AI's technology and hire away some of its employees, including its founder.
- Microsoft and Inflection: Inflection is a startup that develops chatbots. Similar to Google, Microsoft did not acquire Inflection outright but instead entered into a deal to license Inflection's technology and hire away most of its staff, including its founder.
- Amazon and Adept AI: Adept AI is another startup that develops AI technology. Amazon did not acquire Adept AI outright but instead entered into a deal to license Adept's technology and hire away some of its AI researchers.
The video concludes by noting that regulators are starting to wise up to this trend, and that big tech companies may be less willing to enter into these types of deals in the future.
Classical Summary of "Innovations in AI for Education: A Talk by Cynthia Breazeal"
DESCRIPTION
- 571 views Aug 15, 2024
- MIT Open Learning Dean for Digital Learning and Professor Cynthia Breazeal recently joined the MIT Jameel World Education Lab to explore the revolutionary potential of AI-powered education.
- In this talk, Breazeal set the stage with highlights from her groundbreaking work with Jibo, the social robot she designed. She shared her reflections on launching a new field and described her current work at the MIT Media Lab on intelligent personified robots that help learners–particularly children–learn and flourish.
- As the Director of MIT RAISE (Responsible AI for Social Empowerment and Education), Breazeal also spoke about her approaches for AI-supported learning to empower teachers and engage students. At RAISE she launched a K-12 education outreach program and the Day of AI, an event for teachers across the U.S. to introduce foundational concepts in AI and its education role. Breazeal offered her thoughts on what the growth of these initiatives reveals about global interest in AI.
SUMMARY
This video features a talk by Cynthia Breazeal, MIT Dean for Digital Learning and Professor of Media Arts and Sciences, on the innovations in AI for Education. The discussion revolves around the potential of AI to transform education, particularly through personalized learning companions and AI literacy programs.
Breazeal emphasizes the importance of human-centered AI design, drawing from her research in social robotics and Positive Psychology. She introduces the concept of AI fluency, going beyond mere literacy to empower individuals to create solutions with AI technologies.
The talk highlights MIT's RAISE initiative, which aims to promote equity and empower diverse learners through AI education. The Day of AI program, a flagship initiative of RAISE, offers a free, short-format curriculum for teachers to introduce AI literacy to students from kindergarten to 12th grade. Breazeal also underscores the importance of teacher support and provides resources like an online course developed with Grow with Google on utilizing generative AI in teaching practices.
The presentation concludes by emphasizing the need for critical thinking and responsible AI usage. Breazeal stresses the distinction between AI's capabilities and human understanding, highlighting the importance of evaluating AI outputs critically.
Classical Summary of "AI Complexity Is Growing. Here’s What You Need to Simplify"
DESCRIPTION
- 1,203 views Aug 9, 2024
- With various types of AI moving through the Hype Cycle, we’re now seeing some of the most talked about and used among them, including GenAI, enter the trough of disillusionment.
- In this episode of Top of Mind, Gartner Global Chief of Research Chris Howard explores how to understand the increasingly complex nature of managing AI — from budgeting to rollout, to measuring performance — and how this can lead to reaching the plateau of productivity.
SUMMARY
The video is about complexity and simplicity, and how they coexist in our world. The speaker, Chris Howard, uses the example of a mechanical clock tower to illustrate this point.
The video starts with Chris Howard visiting St. Steven's Church in the Netherlands. The church has a clock tower with a complex mechanism for ringing bells. This mechanism, while old and seemingly unnecessary, is a tourist attraction because it represents the ingenuity of human engineering.
Chris Howard then discusses the concept of simplicity and complexity. Simplicity is generally considered good, but too much simplicity can blind people from other possibilities. Complexity, on the other hand, can be bad when it creates confusion and chaos. However, some complexity is necessary, such as having multiple partners in a supply chain for resilience.
The video then moves on to discuss AI (Artificial Intelligence). AI is a complex technology that is still under development. However, the complexity of AI should not deter people from using it, because the benefits outweigh the drawbacks. One challenge with AI is managing its complexity during implementation.
The video concludes with Chris Howard inviting viewers to attend Gartner conferences to learn more about AI and other topics related to simplicity and complexity.
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