20 Things You Need to Know About AI

Artificial intelligence (AI) is changing how we live, work, and interact with this revolutionising technology. 

From chatbots to self-driving cars, AI is already shaping the future.

But what exactly is AI, and why does it matter?

Whether you’re a tech enthusiast or just curious, understanding AI is essential.

Here are 20 key things you need to know about artificial intelligence.

What is AI?

AI refers to machines that can mimic human intelligence. These systems are designed to learn, adapt, solve problems, and make decisions; often faster than humans can.

At its core, it isn’t magic. It’s built on algorithms that process vast amounts of data.

Think of it like this: if you feed it thousands of photos of a specific problem, it can learn to identify one without being explicitly programmed to do so. This is called machine learning, one of its most powerful tools.

The biggest difference for humans is how we communicate with artificial intelligence. We use natural language. Not some kind of special programming or coding like we did in the past with computer technology.

There are different kinds of AI,which include:

Narrow AI

Designed for a specific task like facial recognition, chatbots, or recommendation algorithms. Most of it today falls into this category.

Narrow AI is the kind of artificial intelligence we use every day, often without even realising it. It’s called “narrow” because it’s built to do one specific task really well.

Think of it like this, if it were a student, Narrow AI would be someone who’s a genius in maths but clueless about anything else. It can’t think beyond its programming or purpose.

You’ve already encountered it when, for example, Netflix recommends what to binge next, Instagram filters enhance your selfies and your email sorts out spam with eerie accuracy.

Narrow AI doesn’t “understand” the world; it analyses data, spots patterns, and makes predictions. It’s incredibly fast and efficient, but it has no self-awareness, emotions, or broader understanding.

Despite being “narrow” in name, it’s the most powerful and widely used version today. And it’s also the backbone of Generative AI tools like ChatGPT and image generators, which are impressive, but still very much within the narrow category.

Generative AI

AI that creates content such as text, images, audio, video, and more based on patterns in data.

Examples include ChatGPT, Midjourney, Claude, Gemini, DALL·E, and AI music/video generators. It predicts what to generate next based on huge amounts of training data. It doesn’t “understand” in the human sense; it imitates.

Its uses include editing, summarising and writing text, making AI art, generating code, deepfakes, customer service chatbots, making music with lyrics, creating videos and lots more.

General AI (AGI – Artificial General Intelligence)

Still in development and not yet fully achieved, where the AI would be able to reason, learn, and solve problems like a human, across any domain.

It would understand context, emotion, abstract concepts, and adapt to new challenges without needing retraining. That’s where the line between helpful tool and possible threat starts to blur.

So, AI is already behind the tech you use every day, such as voice assistants, social media filters and internet searches. But its next moves are even more powerful.

It’s not just a fad, it is a technical revolution. It’s changing how we work, learn, shop, and how we will even date.

Who Started the AI Revolution?

The formal beginnings of AI as a field are often traced back to a workshop at Dartmouth College in 1956.

This event, organised by John McCarthy, Marvin Minsky, Claude Shannon, and Nathaniel Rochester, is widely considered the birth of AI research.

McCarthy is credited with coining the term “artificial intelligence.”  

Early pioneers like Alan Turing laid theoretical groundwork with his concept of the “Turing Machine” in the 1930s and later proposed the “Turing Test” in the 1950s as a way to assess machine intelligence. His ideas were foundational to the field.  

Throughout the mid-20th century, researchers like Allen Newell and Herbert Simon made significant strides with programs like the Logic Theorist and the General Problem Solver, demonstrating early capabilities in problem-solving and logical reasoning.

OpenAI, founded in December 2015, is a leading organisation in artificial intelligence research and development.

The company gained prominence with models like GPT-2 and GPT-3, showcasing impressive capabilities in natural language processing. 

In November 2022, OpenAI released ChatGPT, a generative AI chatbot based on the GPT-3.5 model. It quickly gained popularity, reaching one million users within five days.

ChatGPT’s conversational abilities marked a significant milestone in AI development.

Different AI Companies

There are many prominent companies today working in the AI industry. Many of them are leading the way as to how AI will be a staple aspect of our future life.

• OpenAI – OpenAI created ChatGPT, the first AI conversational tool. OpenAI is famous for its cutting-edge AI models. The GPT series powers ChatGPT. DALL-E generates images. Their API allows broad integration of their advanced AI capabilities into other applications.
• Microsoft – Microsoft was the company that backed OpenAI with its first release. Microsoft Copilot integrates AI into their productivity tools. Their OpenAI partnership brings advanced models. Azure AI, a suite of AI services, is a key offering from the company. Microsoft aims to make AI widely accessible to users and businesses.
• Anthropic – Anthropic is an AI safety and research company. They are known for developing the Claude family of AI assistants, which are designed to be helpful, harmless, and honest. Anthropic focuses on building reliable and interpretable AI systems, emphasizing responsible AI development and deployment.
• Google  – Google is a major AI player despite its early failures with AI, such as Bard. They conduct extensive research and deploy AI across their vast product ecosystem. Gemini powers their conversational AI. Google Cloud AI offers enterprise solutions. AI enhances Search, Gmail, and more. DeepMind focuses on advanced AI research.
• Amazon – Amazon Web Services (AWS) provides numerous AI and machine learning services. These include tools for building and deploying AI models. Amazon integrates AI into its e-commerce platform and devices like Alexa for enhanced functionality.
• NVIDIA – NVIDIA is crucial for AI development. Their high-performance GPUs are essential for training complex AI models efficiently. They also offer platforms and software to accelerate AI workflows across many different sectors.

What is a Large Language Model (LLM)?

A Large Language Model (LLM) is a type of AI designed to understand and generate human language. 

It’s trained on massive text datasets to predict words, answer questions, or create content based on prompts.

LLMs don’t think like humans. They recognise patterns in language and use probability to generate responses.

The more data they’re trained on, the more accurate and fluent their output tends to be.

LLMs are being released frequently and are used inside popular AI platforms like ChatGPT, Gemini and Claude. For example, Claude Sonnet, Gemini 2.5 Pro, GPT-5, etc.

They’re used in writing tools, chatbots, translation, coding, and even education. But they don’t know things, they simulate understanding based on text patterns. However, this might change in the future.

What is Prompting?

Prompting is how we communicate with an AI tool. It involves typing a question, instruction, or request, called a prompt, to get a response from an AI model like ChatGPT or Claude.

A prompt can be simple or complex. 

You can also ask it to write content, summarise news, or generate code with specific rules and tone.

The quality of the output depends on how well the prompt is written.

For example, asking, “Summarise this article in three points” will produce a concise summary.

Good prompting gets better results. The clearer and more detailed your instructions, the more accurate and relevant the AI’s reply. It’s like talking to a very fast, very literal assistant.

What are AI Agents?

AI agents are advanced systems that can make decisions, plan actions, and carry out tasks on your behalf. They go beyond simple tools, acting more like digital assistants with autonomy.

Unlike regular AI that only responds, AI agents can follow multi-step goals.

For example, booking travel, researching a topic, or managing emails, all without being told what to do at every step.

They combine skills like memory, reasoning, and goal-setting.

They can be programmed to communicate with each other or work alone. They act more like a human helper.

Agentic AI is a landscape of artificial intelligence that is set to grow hugely.

What is a Chatbot?

AI-powered chatbots are becoming the norm. They use artificial intelligence techniques to understand and process human language.

Specifically, Natural Language Processing (NLP) is a key AI component. NLP allows chatbots to interpret the meaning behind text or speech.

This enables them to respond in a contextually relevant way, rather than just following pre-programmed scripts.

Machine learning allows chatbots to learn from past conversations.

Over time, they can improve their ability to understand user intent and provide more accurate and helpful responses.

So, AI provides the intelligence that makes chatbots more than just simple question-and-answer systems.

It enables them to engage in more dynamic and human-like interactions, making them valuable tools for various applications.

Without AI, chatbots would be limited to very basic interactions based on keywords.

The integration of AI allows for a much richer and more useful user experience, driving their increasing adoption across industries.

AI Use in Different Industries

Artificial intelligence is used in healthcare, finance, education, and entertainment. It’s revolutionising industries globally.

In healthcare, AI aids diagnostics in the UK’s NHS, analyses medical images in Germany, and personalises treatment plans in the USA.

Virtual health assistants are emerging worldwide.

In manufacturing, AI-powered robots automate assembly lines in Japan and Germany, improving efficiency and precision.

Predictive maintenance using AI prevents equipment failures in factories across the globe, from China to the US.

The financial sector uses AI for fraud detection in banks worldwide, from London to Singapore.

Algorithmic trading powered by AI is prevalent in major financial centres like New York and Hong Kong. AI also assists with risk assessment and customer service chatbots.

Retail sees AI enhancing customer experience through personalised recommendations on e-commerce platforms globally.

Inventory management is optimised with AI in warehouses from the UK to Australia, reducing waste and improving logistics.

In agriculture, AI analyses crop health via satellite imagery in countries like Brazil and India, optimising resource use.

Across various sectors, AI-powered chatbots provide 24/7 customer support.

These examples showcase the diverse and expanding impact of AI worldwide.

Fears About AI

Fears surrounding AI are diverse and widespread globally.

Job losses through automation across numerous sectors are a primary concern for workers worldwide, raising anxieties about future employment and the necessity for workforce adaptation.

Ethical dilemmas posed by increasingly autonomous AI systems are significant.

Questions of accountability in AI-driven decisions, from autonomous vehicles to medical diagnoses, generate global debate regarding responsibility and potential harm.

The potential for misuse of AI technologies for malicious purposes is a major international worry.

This includes sophisticated cyberattacks, the development of autonomous weapons, and the erosion of cybersecurity on a global scale.

Bias embedded within AI algorithms, reflecting existing societal inequalities, is another critical fear.

This can lead to unfair or discriminatory outcomes in various applications, impacting diverse populations across the globe.

Long-term existential risks associated with highly advanced AI surpassing human control are also a subject of global discussion and apprehension within the scientific and philosophical communities.

Ensuring the safe and ethical development of AI remains a paramount international challenge.

What is Quantum Computing?

Quantum computing is an AI-related advanced technology that processes information in ways traditional computers cannot.

Unlike classical computers, which use bits, quantum computers employ quantum bits, or qubits, for data representation.

Qubits can exist in multiple states at once due to superposition.

This unique property enables quantum computers to perform many calculations simultaneously, vastly increasing their processing power for specific tasks compared to traditional computers.

Another crucial aspect of quantum computing is entanglement, where qubits become interconnected.

When qubits are entangled, the state of one qubit instantly affects another, regardless of distance, allowing efficient problem-solving.

Quantum computing has the potential to revolutionise various fields, including cryptography, optimisation, and drug discovery.

For instance, quantum computers could break existing encryption methods, prompting the need for new security protocols to protect sensitive data.

Despite its promise, quantum computing is still developing. Creating and maintaining stable quantum systems poses significant challenges, as qubits are highly sensitive to their environment.

Researchers are working to overcome these obstacles.

As quantum computing advances, it may transform industries and change how we tackle complex problems.

The future of this technology could reshape our understanding of computation and information processing entirely.

Why Are Graphics Cards Important for AI?

AI requires hardware to process data efficiently.

Graphics Processing Units (GPUs) are essential for AI training and deep learning.

Unlike traditional CPUs, GPUs handle multiple tasks simultaneously, making them ideal for complex computations required in AI.

Nvidia is a leading artificial intelligence company in GPUs, powering many AI models.

AI tasks, particularly deep learning, involve processing vast amounts of data and performing numerous calculations.

GPUs accelerate this process by executing parallel operations, significantly reducing training times for machine learning models.

The architecture of GPUs allows them to manage thousands of threads at once.

This parallelism is crucial for tasks like neural network training, where numerous calculations occur simultaneously across multiple layers.

As AI evolves, the demand for powerful GPUs continues to grow.

Their ability to handle large datasets and complex algorithms makes them indispensable for researchers and companies working on cutting-edge AI applications.

In summary, graphics cards are vital for AI due to their capacity to accelerate computations, manage parallel tasks, and enhance the performance of machine learning, driving advancements in the field.

Jobs at Threat from AI

AI automation could replace roles in customer service, manufacturing, and data entry. 

It can handle repetitive tasks faster and more accurately than humans.

The rise of AI has sparked discussions about its impact on employment.

While AI automates repetitive tasks, it also creates new job opportunities in technology, data analysis, and AI management. The transition may not be seamless.

Certain industries may experience significant job displacement as AI systems take over tasks previously performed by humans.

For example, automation in manufacturing can reduce demand for assembly line workers, raising concerns about unemployment.

Conversely, AI can enhance productivity and efficiency in the workplace.

By automating mundane tasks, employees can focus on higher-value activities, fostering innovation and creativity. This shift may lead to new roles that require unique skills.

To address challenges posed by AI, upskilling and reskilling initiatives are essential.

Educational institutions and employers must collaborate to equip the workforce with necessary skills to thrive in an AI-driven economy.

The future of work will likely involve a partnership between humans and machines.

By leveraging AI as a tool, workers can enhance their capabilities and contribute to a more dynamic workplace.

How AI is Transforming Education

AI is poised to significantly reshape education and teaching. It offers opportunities for personalised learning experiences tailored to individual student needs and paces.

AI-powered tools can provide instant feedback and support.  

For teachers, AI can automate administrative tasks, freeing up time for more direct student interaction and lesson planning.

AI can also assist in identifying learning gaps and adapting teaching strategies accordingly.  

 However, the integration of AI also presents challenges.

These include ensuring equitable access to technology and addressing concerns around data privacy and the potential deskilling of educators.

Careful consideration and thoughtful implementation are crucial.  

 Ultimately, the impact of AI on education will depend on how effectively it is used to enhance both the learning and teaching processes, always keeping the needs and well-being of students and educators at the forefront.

Surveillance & Privacy Concerns

AI technology has significantly enhanced surveillance capabilities, raising critical privacy concerns.

Governments and organisations utilise AI-powered systems for monitoring public spaces, often justifying their actions in the name of security and crime prevention.

Facial recognition technology is one of the most debated applications of AI in surveillance.

While it can aid law enforcement in identifying suspects, it also poses risks of misidentification and unwarranted tracking of innocent individuals, infringing on personal privacy.

The pervasive nature of AI surveillance can create a chilling effect on free expression.

People may alter their behaviour when they know they are being watched, limiting their willingness to engage in open dialogue or express dissenting opinions.

The convenience of enhanced security and efficiency through AI surveillance must be balanced against the fundamental right to privacy and freedom from constant monitoring. 

Algorithmic bias in AI surveillance systems could disproportionately affect certain demographics.

Transparency and robust oversight are crucial to prevent discriminatory outcomes and ensure fair application of these technologies.  

Ultimately, ongoing discussions about surveillance and privacy in the context of AI are vital. Public awareness and engagement can help shape policies that protect individual rights while harnessing the benefits of AI technologies.

Ethical Concerns

The rapid development of AI raises ethical considerations. One primary concern is bias in AI algorithms, which can lead to discriminatory outcomes.

Biased data can perpetuate stereotypes, necessitating transparency and fairness in AI systems.

Privacy is another critical issue, as AI relies on vast amounts of personal data.

Ensuring data protection and user consent is vital to maintain trust in AI technologies. Companies must prioritise ethical data practices to safeguard privacy.

Accountability in AI decision-making is crucial. As machines become more autonomous, determining responsibility for actions becomes complex.

Clear guidelines and regulations are needed to establish accountability and prevent misuse.

The potential for AI to be weaponised poses significant risks to global security.

Autonomous weapons and surveillance technologies raise ethical implications and unintended consequences, necessitating careful consideration and regulation.

Public engagement is essential in shaping AI policies. Diverse perspectives can help identify risks and develop guidelines that promote responsible AI use.

Collaborative efforts are vital for fostering ethical AI development.

How AI Affects Creativity

AI is reshaping creativity across various fields, enhancing and complementing human artistic expression.

While some fear AI may replace artists, it often serves as a powerful tool to inspire and innovate.

In music, AI algorithms can compose original pieces by analysing patterns in existing songs.

Music artists use these tools to generate new melodies, harmonies, and arrangements, broadening their creative possibilities while maintaining their unique styles.

AI tools like OpenAI’s MuseNet and Jukedeck allow musicians to create fully produced tracks in various genres.

These platforms enable artists to experiment with different sounds and styles, fostering collaboration between human creativity and machine-generated music.

Visual artists benefit from AI-driven software that can create stunning images or suggest enhancements.

These tools allow these artists to explore new techniques, automate tedious tasks, and experiment with different styles, leading to exciting creative outcomes.

In writing, AI language models assist authors by generating ideas, suggesting plotlines, or even drafting content.

While AI cannot replace the human touch, it can help writers overcome creative blocks and develop new narratives.

However, reliance on AI raises questions about originality and authorship. As AI-generated content becomes more prevalent, the definition of creativity may evolve, prompting discussions about the role of technology in artistic expression.

Ultimately, AI’s impact on creativity is transformative.

By collaborating with AI, artists can push boundaries, explore new frontiers, and redefine the creative process, leading to a richer cultural landscape.

Artists and writers use AI tools for inspiration and efficiency.

However, AI-generated content raises questions about originality and copyright.

The balance between human creativity and assistance is still being debated.

AI and the Future of Healthcare

AI is revolutionising healthcare by improving diagnostics and patient care.

Machine learning algorithms analyse medical data to identify patterns, enabling doctors and medical professionals to detect early diseases and produce personalised treatment plans for patients.

AI tools are assisting doctors in making informed decisions.

These systems can evaluate medical images, detect anomalies, and suggest potential diagnoses, enhancing the accuracy and speed of assessments. This leads to better patient outcomes.

AI-powered robots assist in surgeries, increasing precision.

Telemedicine and virtual health assistants leverage AI technologies to provide patients with accessible care.

These platforms enable remote consultations, health monitoring, and personalised recommendations, improving healthcare accessibility for individuals worldwide.

AI also plays a vital role in drug discovery and development.

By analysing vast datasets, AI algorithms can identify potential drug candidates, speeding up the research process and reducing costs for pharmaceutical companies.

The healthcare industry is investing heavily in AI for better patient care.

Despite the benefits, challenges exist in AI healthcare implementation.

Data privacy concerns, regulatory hurdles, and the need for clinician training must be addressed to ensure the responsible integration of AI into healthcare systems.

AI in Entertainment

AI is transforming the entertainment industry in various ways, enhancing content creation, distribution, and audience engagement.

From streaming services to video games, AI technologies play a crucial role in shaping the user experience.

Streaming platforms like Netflix and Spotify use AI algorithms to recommend content based on user preferences.

These personalised recommendations increase user satisfaction, retention, and engagement, helping platforms maintain their competitive edge in a crowded market.

In film and television, AI aids in scriptwriting, casting, and even editing. AI-driven tools analyse successful scripts, helping writers develop compelling narratives and characters.

For example, cloning characters for different scenes is enhancing creativity and streamlining the production process.

Video games increasingly employ AI to create realistic, adaptive environments. AI-controlled characters can learn from player behaviour, adjusting their actions to provide a more immersive experience.

This leads to dynamic gameplay and greater player satisfaction.

AI also plays a role in content moderation on social media platforms, detecting harmful or inappropriate content.

By ensuring a safer online environment, AI enhances user experiences while protecting the integrity of entertainment platforms.

Should You Care About AI?

AI impacts daily life, from search engines to smart assistants.

Understanding AI helps individuals adapt to job markets and industries. 

Businesses that leverage AI can improve efficiency and innovation.

AI technologies influence everything from social media algorithms to personal assistants like Siri and Alexa.

AI enhances convenience by automating tasks and providing personalised recommendations.

By learning user preferences, AI systems can improve our experiences, making them more efficient and tailored to individual needs.

However, it is crucial to be aware of the ethical implications surrounding AI.

Issues like data privacy, surveillance, and algorithmic bias can affect our lives. Understanding these concerns helps us navigate the potential risks of AI technologies.

Moreover, AI is transforming industries, creating new job opportunities while also posing challenges to existing roles.

Being informed about AI developments allows individuals to adapt and prepare for changes in the job market.

Engaging in discussions about its implications can shape policies that promote responsible use, ensuring that AI serves the best interests of society.

Ultimately, caring about AI is vital for making informed decisions.

It aids better decision-making in personal and professional life while mitigating potential drawbacks.

The Future of AI

AI will continue to evolve, impacting life worldwide.

The future of AI is poised for transformative advancements.

Ongoing research focuses on creating general AI systems capable of performing any intellectual task a human can do.

Progress in narrow AI continues to shape various industries.

AI is expected to enhance human capabilities, leading to improved healthcare, education, and environmental sustainability.

Personalised learning experiences, early disease detection, and efficient resource management are potential benefits of AI integration.

The proliferation of AI technologies will likely lead to new ethical and regulatory challenges.

Policymakers must adapt to the evolving landscape, establishing frameworks that ensure responsible AI development and deployment.

As AI systems become more integrated into society, public awareness and understanding will be crucial.

Education and outreach can demystify AI, empowering individuals to navigate the changing technological landscape.

Ultimately, the future of AI holds immense potential.

By fostering collaboration between researchers, policymakers, and society, we can harness AI’s capabilities to create a better, more equitable world.