Introduction to AI: Lecture 0: Basics and Statistics about AI

Intro to AI Key Insights

Investment and Market Growth in AI

• 🌍 To understand the growth in artificial intelligence, look at the countries or institutes producing the most research papers, such as China and the US.
• 💰 Training large language models with billions of parameters requires a significant investment, with costs reaching millions of dollars for companies like Facebook and OpenAI.
• 💰 The substantial investment in AI indicates that the technology will continue to thrive and create jobs for at least the next five years.
• 💰 The year 2023 saw a significant increase in investment in generative AI startups, with the US, China, and the UK emerging as the top investors in this field.
• 💰 The AI market is expected to reach around $180 billion by 2025, highlighting the significant growth and potential of AI technology in various industries.

Applications and Developments in AI

• 📚 Similar to educating a child, AI models need to learn from previous experiences through continuous feeding of data, which is known as training the model.
• 🖼️ The technology of image generation using AI has significantly improved over the years, to the point where it is difficult to distinguish between AI-generated images and real ones.
• 📈 Machine learning programming within AI received the most job applicants, indicating its high demand and potential for growth in the field of artificial intelligence.
• 💼 Earnings calls are crucial for companies as they provide insights into the company’s performance and future plans, and giving false information can have serious consequences, including termination.
• 🏥 The implementation of AI technology in hospitals is a significant development, potentially revolutionizing healthcare.

Impact and Potential of AI

• 💰 The release of chat GPT has sparked a revolution of new ideas and applications in the field of artificial intelligence, attracting significant investments and attention.
• 💰 “When a lot of money is being invested into a particular field, it’s important to pay attention to that field and its potential impact.”
• 💰 The US is leading in terms of investment and testing of electric vehicles, highlighting their commitment to advancing this technology.
• 💡 Focusing on ethical AI is crucial to prevent wasted investments and negative market reactions, and it should be prioritized from the beginning of algorithm development.

Intro to AI Video Summary

The key idea of the video is that AI is rapidly evolving and has various applications, but it is crucial to prioritize ethical AI and there is a high demand for AI talent.

• 00:00 📚 This lecture is an introduction to AI, covering theory and practical work, with a focus on the basics, Python programming, and AI libraries, and the possibility of covering deep learning and natural language processing.
  • The lecture is an introduction to artificial intelligence, taught in English with the option to take the final exam and assignments in either English or Norwegian, and the class has 244 students, the largest in the course’s history.
  • The speaker is a head of data and artificial intelligence, founder of a community for AI employees, and runs a startup, and they encourage students to contact the teaching staff for assistance and use the conversation feature on canvas for help.
  • Grading in this course is based solely on the final project and written exam, with programming assignments serving as a way for students to attempt and demonstrate their understanding rather than being graded.
  • Passing three assignments and either a final project or an academic report will determine your grade, with the exam being in-person and group sizes limited to two to four students unless special reasoning is provided.
  • This course is a mix of theory and practical work, covering the basics of AI, how it works, and how to make practical applications using Python programming and AI libraries.
  • The course is designed to cover the basics of AI, including the importance of data, different algorithms, and basic programming, with the possibility of covering deep learning and natural language processing if time allows, but focusing on chat GPT architecture and responsible AI.

• 12:59 📚 The lecture covers the format of the exam, final project, and provides information on AI, its relationships, terminologies, working with data, business use cases, and ethics; AI is evolving rapidly with new ideas and applications, creating a divide between traditional AI and chat GPT; research in AI is crucial for innovation, with China and the US leading in producing research papers.
  • Assignments will only be done in Python, labs will be recorded and identical on both days, grading will be based on a final project (30%) and a final exam (70%).
  • The lecture covers the format of the exam, the final project, and provides information on artificial intelligence, its relationships, terminologies, working with data, and business use cases and ethics in AI.
  • There is no required book for the course, but there are reading guides and slides provided, as well as two open source free books on machine learning that will be shared later; now the speaker will shift to discussing statistics.
  • AI is evolving rapidly with new ideas and applications emerging every day, creating a divide between the traditional AI field and the noise surrounding chat GPT and its ecosystem.
  • Research in AI is crucial for innovation and advancements in the field, as evidenced by the development of and other tools, with countries like China and the US leading in producing research papers.
  • Israel is a small country that is doing fantastic work in AI research, while Norway, despite being tiny, does not produce as much research.

• 21:59 📚 Training AI models requires time and data, but advancements in hardware have improved the process; large language models have been trained on billions of parameters, with reduced time and cost; AI image generation has improved and is used in Hollywood; Singapore is investing heavily in AI; machine learning programming and generative AI are popular job fields; prompt engineering is a new field where engineers ask the right questions for language models.
  • Training an AI model requires time and data to educate it, historically a bottleneck but now improving with faster hardware.
  • Large language models like chat chipity have been trained on billions of parameters, requiring months of training and millions of dollars, but there have been advancements in reducing the time and cost of training these models.
  • AI image generation has significantly improved over the years, with Hollywood using it for content creation, and the technology becoming even more powerful in 2023.
  • Singapore is one of the countries investing the most in AI and hiring a lot of people in the field.
  • Machine learning programming within AI received the most job applicants, with a growing interest in generative AI.
  • Prompt engineering is a new field in AI where prompt engineers specialize in asking the right questions to get the most out of large language models, and companies are now looking for prompt engineers to work with these models.

• 29:46 💰 Pay attention to investments in new technologies like cryptocurrencies and blockchain, as well as the increasing investments in AI, particularly in autonomous driving, cancer studies, drug studies, and facial recognition, as they indicate job opportunities and growth in these fields for the next five years.
  • Pay attention to where the money is being invested in new technologies, such as cryptocurrencies and blockchain, as it indicates the right time to be concerned about and follow those fields.
  • Investments in AI have been increasing, indicating that the field will continue to grow and create job opportunities for at least the next five years.
  • In 2023, there was increased investment in generative AI startups, with the US, China, and the UK emerging as the top investors, while Norway focused on oil and lacked serious investment in the tech industry.
  • Investments in AI, particularly in autonomous driving, cancer studies, drug studies, and facial recognition, have been increasing in Europe, with the UK leading the way, due to both government and private investments, as companies like Volkswagen, Tesla, and BMW have high-cost products that drive investment in these areas.
  • Investors are more likely to invest in companies that promise to revolutionize the car industry with autonomous driving, and Tesla’s high valuation is partly due to its positioning as an AI autonomous driving car company; however, smaller investors can also invest in areas such as digital content and facial recognition.
  • Investments in AI are not solely focused on autonomous driving, but also on various sectors such as fashion retail tech, data tools, automation, oil and gas, tax analysis, fintech, chatbots, and marketing, with countries like Israel, Singapore, United States, and China leading in AI development due to their strong technical infrastructure.

• 39:59 📈 Financial companies are increasingly investing in AI, while health professionals face challenges in implementing AI due to the complexity of the health system and personal data limitations; self-driving car technology is being heavily invested in and tested worldwide, with the US leading in investment and testing.
  • The mention of artificial intelligence in earnings calls of publicly traded companies has been increasing, indicating a growing focus and investment in AI by financial companies.
  • Health professionals are looking to invest in AI to reduce the time spent on preparing data sets for algorithms, but the complexity of the health system and personal data limitations make it challenging to find solutions.
  • One hospital implemented AI technology, while in the transportation industry, only a few companies, like Luther, are utilizing AI.
  • Automating transportation is necessary, but the speaker forgot to record and there was a break.
  • Most countries, including the US, Middle East, and Europe, are heavily investing in and testing self-driving car technology, with the US leading in investment and testing.

• 46:29 🚗 Self-driving cars prioritize safety over traffic flow, but face challenges with regulations, capacity, and determining responsibility in the event of a crash, delaying their widespread adoption.
  • Autonomous cars are not being widely implemented due to safety concerns and regulations, as self-driving cars prioritize safety by immediately stopping when encountering a problem, unlike human drivers who may cause chaos in traffic.
  • Self-driving cars prioritize safety over traffic flow, and Norway is investing heavily in this technology despite thought-provoking questions from public authorities.
  • If self-driving cars become popular, everyone will start buying them, causing the cars to pick up passengers, drop them off, and then return home to be charged instead of being parked in downtown Oslo.
  • The problem with implementing AI in transportation is the lack of capacity to handle increased demand, leading to long delays and policy makers considering not allowing it, despite efforts to encourage people to use public transport instead of owning cars.
  • Policy makers are struggling to determine who is responsible in the event of a crash involving a self-driving car, which is hindering the widespread adoption of autonomous vehicles.
  • Self-driving cars are still in the testing phase and it will take five to ten years before they are seen in production due to government regulations and public concerns about safety.

• 53:17 🤖 The defense industry is investing in AI for autonomous weapons, while the perception of AI as killer robots has shifted to a desire for intelligent life forms; AI is now focused on specific functions in manufacturing and creating algorithms that are ethical and unbiased.
  • The defense industry is investing heavily in autonomous weapons and incorporating AI into drones, with both government contractors and private investors funding these developments due to the ongoing war in Ukraine.
  • Autonomous weapon systems in developed countries like the USA and NATO already use AI for predicting missile paths, but there is also a lot of infrastructure that relies on basic information without intelligence; while in Asia AI is not widely used in weapons, the perception of AI as killer robots has shifted in recent years to understanding it as a functionality and a desire to create intelligent life forms.
  • The concept of robots in the field of AI has shifted from human-like robots to mechanical devices that can learn on their own and assist in specific functions, with a focus on specific installations in manufacturing companies.
  • Google Trends is a useful tool to see what topics people are talking about, and currently, machine learning is receiving the most attention, while chat GPD is becoming less popular.
  • Ethical AI involves creating algorithms that can be explained and do not harm or create problems for communities or users, as exemplified by Amazon’s recruitment algorithm that unintentionally recommended more men for positions due to historical data bias.
  • People tried removing gender identifiers from data and running the algorithm again, but the same gender-specific problem persisted.

• 01:05:19 🤖 Ethical AI is crucial and should be prioritized, as demonstrated by examples of biased algorithms, and there is a high demand for AI talent despite a market slump.
  • The AI algorithm developed in the project was shut down due to its unethical and sexist behavior in identifying male and female applicants based on certain patterns in the application.
  • Ethical AI is crucial and should be prioritized before building algorithms, as demonstrated by examples of biased data leading to biased algorithms, and the increasing focus on ethical AI in recent years.
  • The focus of the lecture is on the importance of ethical AI and the need to generate new artificial data to improve predictions and reduce bias in AI algorithms.
  • The demand for AI talent has increased significantly, with various job opportunities available in fields such as AI product management, AI QA, and data analysis, and it is important to consider ethical challenges in AI development.
  • AI is deeply rooted in various industries and will continue to shape our lives, with potential for both artificial general intelligence and smart devices, and there is significant investment and usage in the field.
  • AI developers are in high demand and earning good salaries despite a slump in the market for developers.