What You Need to Know About AI

What is all the buzz about artificial intelligence (AI)? Many don’t realize that AI is everywhere– from streaming recommendations to virtual assistants. Artificial intelligence has become part of our daily lives and is transforming our personal and business worlds. Companies are using AI to make smarter, faster decisions—from analyzing data to predicting trends and detecting fraud to automating customer service with chatbots that answer questions 24/7. 

AI is also helping industries like healthcare, finance, and manufacturing work more efficiently, reduce costs, and offer personalized experiences. With so much news about  AI, we prepared this guide to frequently asked questions about AI.

1. What is AI?

AI refers to the simulation of human intelligence in machines that are designed to perform tasks typically requiring human cognitive functions. These tasks include learning, problem-solving, reasoning, understanding natural language, and adapting to new information. AI systems are built using algorithms, mathematical models, and large datasets that allow them to process information and make decisions autonomously. 

Algorithms are a step-by-step set of instructions for solving a problem or completing a task. It’s like a recipe that tells a computer exactly what to do, in what order, to get the desired outcome.

AI is used across a wide range of applications, improving efficiency, driving innovation, and solving complex problems that were previously beyond the reach of traditional software systems. Here are some key areas where AI is making a significant impact:

• Healthcare: AI is transforming the healthcare industry by improving diagnostic accuracy, predicting disease outbreaks, and aiding in the development of personalized medicine. AI-powered tools can analyze medical images, detect patterns in large datasets, and assist doctors in making more informed treatment decisions. AI is also used in drug discovery, where it helps identify potential drug candidates and optimize clinical trials.
• Finance: In the financial sector, AI is used for fraud detection, algorithmic trading, and credit risk assessment. AI algorithms can analyze vast amounts of data to detect fraudulent activities in real time. Financial institutions also use AI to automate customer service through chatbots and to optimize investment portfolios using predictive analytics.
• Transportation: AI plays a critical role in the development of autonomous vehicles, allowing them to navigate roads, avoid obstacles, and make real-time decisions. AI is also used in optimizing logistics and supply chain management, improving route planning, and reducing fuel consumption.
• Customer Service: Many companies are using AI to enhance customer service through the deployment of chatbots and virtual assistants. These AI-driven tools can provide quick, efficient responses to customer inquiries, helping businesses improve customer satisfaction and reduce operational costs.
• Manufacturing: AI is being integrated into manufacturing processes for predictive maintenance, quality control, and automation of production lines. Machine learning models can analyze data from sensors in equipment to predict when maintenance is needed, preventing costly downtime. AI-driven robots are also capable of handling complex tasks on assembly lines with precision.
• Education: AI is transforming education by providing personalized learning experiences for students. AI platforms can adapt to a student's learning style and pace, offering tailored resources and feedback. AI is also used in grading and assessment, helping educators evaluate student performance more efficiently.
• Software Development: AI is revolutionizing software development by automating code generation, debugging, and testing. It helps optimize code performance, enhance security, and improve code quality through intelligent analysis and suggestions. AI-powered tools also assist in automating documentation, modernizing legacy systems, and streamlining project management. By reducing manual tasks, AI enables developers to focus on more complex, creative, and innovative aspects of software creation, leading to faster development cycles and higher-quality products.
• Entertainment: In the entertainment industry, AI is used for content recommendation, video game development, and even content creation. Streaming services like Netflix and Spotify use AI algorithms to analyze user preferences and recommend content based on viewing or listening habits
• Answering Questions. AI platforms can answer questions over a great variety of topics, typically within seconds.

 2. What is ChatGPT?

ChatGPT is an AI-powered assistant developed by OpenAI that can help with all kinds of tasks, from answering questions and brainstorming ideas to just having a chat. It’s like having a knowledgeable digital companion that’s always ready to help ChatGPT is trained to understand your questions and respond in a friendly, human-like way, so it feels natural to use. Multiple versions of ChatGPT have been issued, including GPT-3, GPT-4o, and GPT-4.5.

3. What is OpenAI?

OpenAI is an AI research and development company that aims to ensure that artificial general intelligence (AGI) benefits all of humanity. Founded in 2015 by Elon Musk, Sam Altman, and others, OpenAI has produced groundbreaking models like GPT-4o and DALL-E, which focus on natural language understanding and generative AI. The company is known for its focus on the ethical development of AI technologies.

4. What is machine learning?

Machine learning is a subset of AI that involves training algorithms to learn from data and make predictions or decisions without being explicitly programmed. The machine learns patterns from input data and adjusts its parameters to improve its performance over time. Applications include recommendation systems, fraud detection, and facial recognition.

5. What is a deepfake?

A deepfake is a type of video, audio, or image created using artificial intelligence to realistically mimic someone else’s appearance, voice, or movements. You might have seen deepfake videos online where a celebrity appears to be saying or doing something they never actually did. In business, deepfakes have both intriguing opportunities and some serious risks. 

On the positive side, companies could use deepfakes to create virtual training materials, or to translate video content across languages with a natural feel, without needing to reshoot everything. However, there are concerns about misuse—like spreading false information or impersonating people for fraud. Businesses need to stay aware of deepfake technology to protect their brand’s reputation and security, while also keeping an eye on creative, ethical ways it might enhance customer engagement.

6. What is natural language processing (NLP)?

NLP is a field of AI focused on the interaction between computers and humans through natural language. NLP allows computers to understand, interpret, and generate human language in a way that is valuable for tasks like translation, sentiment analysis, and virtual assistants. Popular applications of NLP include chatbots and voice assistants like Siri and Google Assistant.

7. Can I use AI to create digital art and images?

Yes, AI can be used to create digital art and images through generative models like DALL-E, Canva, Midjourney and other platforms. These models allow users to input prompts or descriptions and generate unique artwork based on that input. AI-powered art generators are increasingly used in fields like design, advertising, event planning and entertainment.

8. What is deep learning?

Deep learning is a subset of machine learning that uses neural networks with multiple layers (hence the "deep" in deep learning) to model complex patterns in data. Deep learning is the driving force behind many modern AI applications, including image recognition, natural language processing, and autonomous driving.

9. What is a neural network?

Neural networks are computational models designed to mimic how the human brain works, helping computers recognize patterns, learn from data, and make predictions. Imagine it as a web of interconnected "neurons" (tiny units in the computer) that work together to analyze and process information. 

Each neuron in the network learns something specific from the data it receives and then passes its findings along to other neurons, gradually building up an understanding of complex information. They are particularly effective in tasks that require learning from large amounts of data.

In business, neural networks are used in all sorts of creative and powerful ways. For example, they help banks detect fraudulent transactions by spotting unusual patterns, enable personalized recommendations for online shopping, and assist companies in improving customer service by analyzing customer queries and providing faster responses. 

10. Does AI have risks?

While AI has immense potential for positive impact, it also poses risks. Unchecked development could lead to unintended consequences, such as bias in decision-making algorithms, job displacement, or the misuse of AI technologies like deepfakes. Many organizations, including OpenAI and Anthropic, stress the importance of developing AI responsibly and ensuring its benefits are widely distributed.

11. What is computer vision?

Computer vision is an area of AI that enables machines to interpret and understand visual information from the world. This technology is used in applications such as facial recognition, object detection, and autonomous vehicles. By analyzing images and video, AI systems can make sense of the visual world, allowing machines to perform tasks that require vision-based input

12. Can AI output have mistakes?

Artificial intelligence, while powerful, can still make mistakes, a phenomenon that can significantly impact business applications. One type of mistake, known as hallucinations, occurs when AI generates responses that are entirely inaccurate or fabricated, even though they may sound convincing. Hallucinations happen when AI systems attempt to provide answers in scenarios where they lack sufficient information or context, leading them to "fill in the gaps" inaccurately.

In business applications, this can be problematic, especially in customer service, data analysis, or decision support, where AI-generated errors could mislead teams or customers. For example, an AI-powered chatbot might generate incorrect responses about product features or prices, causing confusion and potentially harming customer trust. By understanding these limitations, businesses can implement quality checks and keep refining AI to minimize mistakes and improve reliability over time. Even ChatGPT warns:: "ChatGPT can make mistakes. Check important info."

13. Can AI write software code?

Yes, AI can assist with writing software code using models like OpenAI’s Codex, which powers GitHub’s Copilot tool. These AI tools can generate code snippets, suggest improvements, and even write entire functions based on the user’s input. While AI is helpful in speeding up coding tasks, human oversight is still required to ensure accuracy.

14. What is artificial general intelligence (AGI)?

AGI refers to the hypothetical development of AI systems that possess the ability to perform any intellectual task a human can do. Unlike narrow AI, which is task-specific, AGI would have the ability to learn, reason, and solve problems in a wide range of domains. While AGI is a long-term goal of AI research, it does not yet exist.

15. What is a chatbot?

A chatbot is like a digital helper that can chat with people, answering questions, guiding them through tasks, or even offering recommendations—all through simple conversation. In business, chatbots have become popular because they are available 24/7, helping customers get instant support without waiting for a live agent. 

For example, they’re often used on company websites to answer common questions like “What’s your return policy?” or “Where’s my order?” Some chatbots go a step further, assisting customers with product choices, scheduling appointments, or even placing orders. By handling routine questions, chatbots let customer service teams focus on more complex issues, making them a helpful tool that saves time for everyone and enhances customer satisfaction!

16. What is ethical AI?

Ethical AI is all about making sure that artificial intelligence is developed and used responsibly. It’s about asking questions like, “How can we make sure AI treats everyone fairly?” or “How can we keep people’s data private and secure?” 

By focusing on ethical AI, developers aim to build systems that respect human rights, avoid biases, and work transparently, so people can trust them. This also means keeping a close eye on how AI is used, especially as it grows more advanced, to prevent unintended consequences. When done right, ethical AI can lead to tools and technologies that truly benefit society, making life easier while respecting our values and principles. Organizations must consider the ethical implications of their AI models, ensuring they do not perpetuate discrimination or negatively impact marginalized groups.

17.Can AI be biased?

Yes, AI can sometimes be biased, which happens when it makes unfair or unbalanced decisions because of the data it was trained on. In life and business, this can have real consequences, like when an AI system unintentionally favors certain groups over others. 

For example, if an AI-powered hiring tool is trained on past hiring data that’s biased, it might unfairly overlook qualified candidates from underrepresented groups. Or, in everyday life, an AI recommendation system might suggest products or content that reinforce stereotypes. These biases often come from patterns in the data used to train AI, which may reflect human prejudices or limitations. This is why it is important for companies and developers to carefully review and adjust their AI systems to promote fairness, ensuring that the technology is as inclusive and balanced as possible.

18. What is generative AI?

Generative AI refers to AI systems that can create new content, such as text, images, music, or even video. Examples include GPT-4o for generating text, and DALL-E for creating images based on textual descriptions. Generative AI is used in creative industries, marketing, and even scientific research to produce innovative content.

19. What is the difference between AI and machine learning?

AI is the broader concept of machines being able to perform tasks intelligently, whereas machine learning is a specific subset of AI that focuses on enabling machines to learn from data. In machine learning, algorithms are trained to improve performance based on exposure to data without needing explicit programming.

20. What is Siri?

Siri is a virtual assistant built into Apple devices like iPhones, iPads, and Macs. With a simple “Hey Siri” or the push of a button, you can ask it to do all sorts of things such as: set reminders, send messages, look up directions, or even check the weather. Siri listens to what you need, figures it out, and gives you a quick response, making everyday tasks faster and easier. Plus, the more you use Siri, the better it gets at understanding what you need.

21. How is AI used in autonomous vehicles?

Autonomous vehicles, or self-driving cars, are high-tech vehicles that can drive themselves using sensors, cameras, and artificial intelligence to navigate, avoid obstacles, and obey traffic rules. They’re designed to make travel safer by reducing human error, but there’s also some hesitation about having these vehicles on the road. Concerns include how well they can handle unpredictable situations, like sudden changes in weather or complex urban environments, and the worry that technical glitches could lead to accidents. 

Despite this, companies like Waymo are moving forward, with self-driving taxis already operating in some U.S. cities. Tesla’s “Autopilot” mode handles much of the highway driving for its vehicles. Even some self-driving trucks are being used for deliveries. 

22. Who are some of the most prominent companies involved in AI?

• Open AI
• Anthropic
• MIcrosoft
• Safe Superintelligence
• xAI
• Apple
• NVIDIA
• Google
• IBM

23. How does AI impact privacy? 

AI has a big impact on privacy, both for individuals and businesses, and it’s something we’re all becoming more aware of. For personal use, AI often processes large amounts of data to provide personalized recommendations or services, like in social media, e-commerce, or even health apps. While this can be helpful, it also raises questions about how much personal data is being collected, who has access to it, and how securely it’s being stored. 

For businesses, AI can analyze customer behavior, employee productivity, and market trends, which provides valuable insights but also requires handling sensitive information responsibly. Misuse or leaks of this data can lead to privacy concerns or even legal issues. Ensuring that AI respects privacy means putting strong security measures in place and being transparent about data use, which helps to build trust and confidence among customers and employees alike.

24. What is the singularity?

The singularity is a theoretical point in the future where artificial intelligence surpasses human intelligence, leading to rapid and uncontrollable technological growth. At that stage, machines would be able to improve themselves without human intervention, potentially leading to exponential advancements in various fields such as medicine, engineering, and science.

A variety of popular movies have focused on the theme of AI and singularity, including The Terminator movies, Her, 2001: A Space Odyssey, and The Matrix.

25. What are some of the biggest challenges of AI in business?

One of the biggest challenges of using AI in business is balancing innovation with reliability and security. While AI offers powerful insights and automation that can transform how businesses operate, it’s not always perfect. AI models require high-quality data to make accurate predictions, but many businesses struggle with managing and cleaning their data or may lack enough relevant data to train effective models. 

Additionally, there’s the challenge of explainability—understanding why an AI made a particular decision. This is crucial, especially in fields like finance or healthcare, where decisions need to be transparent and backed by clear reasoning. On top of that, data privacy and security are major concerns, as AI systems often process large volumes of sensitive information. Ensuring that data is secure and used responsibly is essential to maintain customer trust and comply with regulations. 

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About the Authors:

Richard D. Harroch is a Senior Advisor to CEOs, management teams, and Boards of Directors. He is an expert on M&A, venture capital, startups, and business contracts. He was the Managing Director and Global Head of M&A at VantagePoint Capital Partners, a venture capital fund in the San Francisco area. His focus is on internet, digital media, AI and technology companies. He was the founder of several Internet companies. His articles have appeared online in Forbes, Fortune, MSN, Yahoo, Fox Business and AllBusiness.com. Richard is the author of several books on startups and entrepreneurship as well as the co-author of Poker for Dummies and a Wall Street Journal-bestselling book on small business. He is the co-author of a 1,500-page book published by Bloomberg on mergers and acquisitions of privately held companies. He was also a corporate and M&A partner at the international law firm of Orrick, Herrington & Sutcliffe. He has been involved in over 200 M&A transactions and 250 startup financings. He can be reached through LinkedIn.