Why You Shouldn't Learn AI in 2024

Sundas Khalid
24 May 202408:26

TLDRIn 2024, only 35% of companies worldwide have adopted AI, suggesting it's not yet mainstream. However, as adoption rates are expected to rise, learning generative AI becomes increasingly valuable. The video discusses the importance of prompt engineering for both technical and non-technical professionals, highlighting its potential to enhance productivity. Examples illustrate how using generative AI can improve efficiency, with tech professionals like software engineers solving more tickets and non-tech roles like customer service representatives handling more calls. The video encourages learning prompt engineering to stay ahead as AI becomes more prevalent, emphasizing AI as a tool to augment human capabilities rather than replace them.

Takeaways

  • 🤖 As of 2024, only 35% of companies worldwide have adopted AI, indicating a significant potential for future growth in AI usage.
  • 🔮 The future of AI is expected to be mainstream, with a projected 100% adoption rate in the coming years.
  • 💡 Learning generative AI can be approached from two perspectives: as a consumer (prompt engineering) or as a creator (developing AI technologies).
  • 👩‍💻 For technical users, such as software engineers and data scientists, prompt engineering with generative AI can significantly increase productivity.
  • 👨‍💼 Non-technical users, including those in customer service and other fields, can also benefit from learning prompt engineering to enhance their work efficiency.
  • 📈 Generative AI tools like Google's AI Essential can train users to become power users, incorporating prompt engineering into daily tasks.
  • ✍️ Writing clear and structured prompts is crucial for getting the best results from generative AI models.
  • 🔄 Iteration is key when using generative AI; the first response may not be optimal, and refining prompts can lead to better outcomes.
  • 🏢 Companies that incorporate generative AI into their operations can expect to see improved efficiency and problem-solving capabilities.
  • 🌟 Generative AI is not a job replacement but a tool to augment human capabilities, making work more efficient and productive.
  • ⏰ Early adopters of generative AI will have an advantage as AI becomes more prevalent in the workplace, suggesting the importance of learning AI skills now.

Q & A

  • Why is the adoption rate of AI important in 2024?

    -In 2024, only 35% of companies worldwide have adopted AI, indicating that there is still a significant portion of companies not utilizing AI. This adoption rate is crucial as it shows the current state of AI integration and suggests potential for growth and learning opportunities in the future.

  • What are the two use cases for learning generative AI mentioned in the transcript?

    -The two use cases for learning generative AI are: 1) as a consumer or end-user of AI, which involves prompt engineering, and 2) as a creator of AI, where one is involved in developing AI technologies using machine learning and deep learning.

  • What is prompt engineering and why is it important for tech employees?

    -Prompt engineering is the skill of creating effective prompts to guide AI systems to provide accurate and useful responses. It's important for tech employees because it allows them to leverage generative AI to solve problems more efficiently, thereby increasing productivity and potentially standing out in performance evaluations.

  • How does the use of generative AI by Jessica and Jack illustrate its impact on performance?

    -Jessica and Jack are both software engineers. Jessica uses generative AI to solve 2 out of 3 tickets per month, while Jack, without using AI, solves only 1.5. Over a year, Jessica solves 85 tickets compared to Jack's 56, showing that using generative AI can significantly enhance an employee's performance.

  • What is the benefit of learning prompt engineering for non-tech employees?

    -Non-tech employees can benefit from learning prompt engineering by using generative AI to assist in their daily tasks, such as finding solutions to customer problems more quickly. This can lead to time savings and increased efficiency, as demonstrated by the example of Jeffrey and Jennifer in customer service.

  • What does Google's AI course teach about prompt engineering?

    -Google's AI course teaches four core aspects of prompt engineering: developing ideas, making informed decisions, writing clear prompts to receive better AI responses, and iterating on prompts to refine the AI's output.

  • Why is it suggested to start learning generative AI even if it's not mainstream yet?

    -It's suggested to start learning generative AI now to get ahead of the curve as adoption rates are expected to increase. Preparing in advance can provide a competitive edge when AI becomes more prevalent in the workplace.

  • How can generative AI be beneficial for non-tech job families like construction or medical professionals?

    -While generative AI may not be directly applicable to all tasks in non-tech fields, it can assist in research, problem-solving, and providing information quickly. For instance, construction workers could use it to find solutions to technical issues, and medical professionals could use it for research purposes, although direct patient care should still rely on professional judgment.

  • What is the concern about generative AI taking over jobs, and how is it addressed in the transcript?

    -There is a concern that generative AI might automate and take over jobs. However, the transcript addresses this by stating that while AI can automate simple tasks, it cannot replace human judgment and creativity. The focus should be on incorporating AI to make work more efficient and productive.

  • What is the potential future scenario for AI adoption discussed in the video?

    -The video discusses a potential future where AI adoption reaches 100%, with every company using generative AI in their operations. It emphasizes the importance of learning and adapting to generative AI to stay relevant in such a scenario.

Outlines

00:00

🤖 The Future of Generative AI and Prompt Engineering

The video script discusses the potential of learning generative AI, particularly in the context of prompt engineering. It suggests that while generative AI is not yet mainstream, its adoption is growing, with 35% of companies worldwide already using AI. The speaker argues that learning generative AI could be beneficial in the long term, especially as adoption rates are expected to reach 100%. The video focuses on prompt engineering, which involves using AI technologies to assist in tasks like brainstorming, proofreading, and coding. It distinguishes between technical users, such as those in programming or tech-related jobs, and non-technical users, like those in recruiting or construction. The script uses the example of software engineers Jessica and Jack to illustrate how using generative AI can lead to increased productivity and efficiency. Jessica, who uses generative AI, solves more tickets than Jack, who relies on traditional methods. The video also mentions Google's AI Essential course on Coursera, which teaches how to use generative AI effectively in daily tasks.

05:01

👩‍💼 Generative AI for Non-Tech Audiences

The second paragraph of the video script addresses the question of whether non-tech audiences should learn about generative AI. It uses the example of Jeffrey and Jennifer, who work in customer service. Jeffrey has learned prompt engineering and uses generative AI to solve customer problems more efficiently, taking 7 hours compared to Jennifer's 8 hours. The script suggests that even non-tech jobs can benefit from generative AI, leading to time savings and improved productivity. It also touches on the broader implications of AI adoption, predicting that it will become essential in many job fields. The speaker reassures viewers that generative AI is not about replacing humans but rather about making work easier and more productive. The video concludes by encouraging viewers to start preparing for a future where AI is ubiquitous and to share their thoughts on the topic.

Mindmap

Keywords

💡Generative AI

Generative AI refers to artificial intelligence systems that are capable of creating new content, such as text, images, or music, that is similar to content created by humans. In the context of the video, generative AI is likened to a human assistant that can help with tasks like brainstorming ideas, proofreading, and even writing and debugging code. The video emphasizes the potential of generative AI to enhance productivity across various job roles, both technical and non-technical.

💡Prompt Engineering

Prompt engineering is the art of formulating clear and effective prompts for generative AI systems to elicit the desired responses or outputs. The video discusses how learning prompt engineering can be beneficial for both technical and non-technical users. It gives the example of software engineers using generative AI to solve problems more efficiently and customer service representatives using it to find solutions to common customer queries.

💡AI Adoption Rate

The AI adoption rate refers to the percentage of companies that have integrated AI technologies into their operations. As of 2024, the video mentions that 35% of companies worldwide have adopted AI. This statistic is used to highlight the growing trend of AI integration and to suggest that learning about generative AI now could be advantageous as the adoption rate is expected to increase in the future.

💡Technical Users

Technical users are individuals who work in technology-related fields, such as software engineering, data science, or programming. The video discusses how technical users can leverage generative AI to improve their work efficiency, such as by using AI to debug code or analyze data more effectively. It provides examples of how software engineers, like Jessica and Jack, can benefit differently from using generative AI in their work.

💡Non-Technical Users

Non-technical users are those who work in fields that are not primarily technology-focused, such as customer service, construction, or medical professions. The video argues that even non-technical users can benefit from learning about generative AI, as it can assist in their daily tasks, like providing better customer support by quickly finding solutions to common issues.

💡LLM (Large Language Models)

LLM stands for Large Language Models, which are a type of generative AI that can understand and generate human-like text based on the input provided to them. The video explains that the effectiveness of generative AI is dependent on the quality of the prompts given to these models, and it encourages viewers to learn how to interact effectively with LLMs.

💡Google AI Essential

Google AI Essential is a course mentioned in the video that aims to teach users how to become proficient in using AI technologies, specifically focusing on prompt engineering. The course is available on Coursera and is designed to help users develop ideas, make informed decisions, and perform tasks more efficiently using AI, such as Google's own AI platform, Google Gemini.

💡Productivity

Productivity in the video is discussed in the context of how generative AI can help increase the efficiency and output of workers, both technical and non-technical. It is highlighted that by using AI tools, employees like Jessica can solve more tickets or tasks in the same amount of time, thus increasing their productivity and potentially their value to the company.

💡Job Automation

Job automation refers to the use of technology, including AI, to perform tasks that would otherwise be done by humans. The video addresses concerns that generative AI might lead to job loss by automation but argues that while AI can automate simple tasks, it is unlikely to replace the need for human judgment and creativity entirely. Instead, it suggests that AI should be viewed as a tool to augment human capabilities.

💡AI in Daily Work

The video suggests that as AI adoption becomes more widespread, generative AI will likely become an integral part of daily work across various industries. It encourages viewers to prepare for this future by learning about generative AI now, so they can adapt and make the most of these technologies when they become commonplace in the workplace.

Highlights

In 2024, only 35% of companies worldwide have adopted AI, indicating a significant potential for future growth.

The adoption rate of AI is expected to reach 100% in the coming years, making AI literacy increasingly important.

There are two primary ways to engage with generative AI: as a consumer (prompt engineering) or as a creator (developing AI technologies).

Generative AI can act as a human assistant, aiding in brainstorming, proofreading, structuring, writing, coding, and debugging.

Technical users, such as software engineers and data scientists, can leverage generative AI to enhance their problem-solving capabilities.

Non-technical users, including those in customer service and construction, can also benefit from learning prompt engineering.

Jessica, a software engineer using generative AI, solves more tickets per month compared to Jack, who doesn't use AI.

Data scientists can utilize tools like RAI to streamline their work, demonstrating the practical applications of generative AI.

Google AI Essentials is a course designed to turn users into power users of generative AI, available on Coursera.

The course teaches how to write clear prompts, iterate for better responses, and make informed decisions with AI.

The skills learned from Google AI Essentials are applicable to various AI models, not just Google's.

Non-tech audience, such as those in customer service, can save time and improve efficiency by using generative AI.

Jeffrey, a customer service representative using AI, saves an hour per day compared to Jennifer, who doesn't use AI.

Even professionals in fields like plumbing and medicine may find use cases for generative AI in their work.

Generative AI is not expected to replace human jobs but to automate simple tasks and enhance productivity.

Learning generative AI now can provide a competitive advantage as AI adoption continues to accelerate.

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