LLMs, GPUs, and hallucinations — what you need to know about AI

• Generative AI is becoming increasingly omnipresent — and is a growing hot topic.
• Chatbots such as OpenAI's ChatGPT are changing the way we find information, generate images, and more.

It's becoming increasingly impossible to ignore AI in our everyday lives.

Since OpenAI released ChatGPT in late 2022, people have gotten used to using the chatbot in many ways. Workers are turning to AI to automate tasks, while others are using the technology to make improvements to their personal lives.

And as AI continues to advance, there may be a greater need for everyone to understand what it is and how it may affect us.

Here's a list of the people, companies, and terms you need to know to talk about AI, in alphabetical order.

The top AI leaders and companies

Sam Altman: The cofounder and CEO of OpenAI, the company behind ChatGPT. In November, Altman was ousted by OpenAI's board before returning to the company as CEO days later.

Dario Amodei: The CEO and cofounder of Anthropic, a major rival to OpenAI, where he previously worked. The AI startup is behind an AI chatbot called Claude 2. Google and Amazon are investors in Anthropic.

Demis Hassabis: The cofounder of DeepMind and now CEO of Google DeepMind, Hassabis leads its AI efforts at Alphabet.

Jensen Huang: The CEO and cofounder of Nvidia, the tech giant behind the specialized chips companies use to power their AI technology.

Satya Nadella: The CEO of Microsoft, the software giant behind the Bing AI-powered search engine and Copilot, a suite of generative AI tools. Microsoft is also an investor in OpenAI.

Mustafa Suleyman: The cofounder of DeepMind, Google's AI division, who left the company in 2022. He cofounded Inflection AI, before he joined Microsoft as its chief of AI in March 2024.

The AI terms you need to know

AGI: "Artificial general intelligence," or the ability for artificial intelligence to perform complex cognitive tasks such as displaying self-awareness and critical thinking the way humans do.

Alignment: A field of AI safety research that aims to ensure that the goals, decisions, and behaviors of AI systems are consistent with human values and intentions. In July 2023 OpenAI announced a "Superalignment" to focus on making its AI safe. That team was later disbanded and in May the company set up a safety and security committee to advise the board on "critical safety and security decisions."

Compute: The AI computing resources needed to train models and carry out tasks, including processing data. This can include GPUs, servers, and cloud services.

Deepfake: An AI-generated image, video, or voice meant to appear real which tends to be used to deceive viewers or listeners. Deepfakes have been used to create non-consensual pornography and extort people for money.

Effective altruists: Broadly speaking, this is a social movement which stakes its claim in the idea that all lives are equally valuable and those with resources should allocate them to helping as many as possible. And in the context of AI, effective altruists (EAs) are interested in how AI can be safely deployed to reduce suffering caused by social ills like climate change and poverty. Business leaders like Elon Musk, Sam Bankman-Fried, and Peter Thiel identify as effective altruists. (See also: e/accs and decels).

GPU: A computer chip, short for graphic processing unit, that companies use to train and deploy their AI models. Nvidia's GPUs are used by Microsoft and Meta to run their AI models.

Hallucination: A phenomenon where a large language model (see below) generates inaccurate information that it presents as a fact. For example, during an early demo, Google's AI chatbot Bard hallucinated by generating a factual error about the James Webb Space Telescope.

Large language model: A complex computer program designed to understand and generate human-like text. The model is trained on large amounts of data and produces answers by scraping information across the web. Examples of LLMs include OpenAI's GPT-4, Meta's Llama 2, and Google's Gemini.

Multimodal: The ability for AI models to process text, images, and audio to generate an output. Users of ChatGPT, for instance, can now write, speak, and upload images to the AI chatbot.

Neural network: A machine learning program, also known as deep learning, designed to think and learn like a human brain. Facial recognition systems, for instance, are designed using neural networks in order to identify a person by analyzing their facial features.

Open source: A trait used to describe a computer program that anyone can freely access, use, and modify without asking for permission. Some AI experts have called for models behind AI like ChatGPT to be open source so the public knows how exactly they are trained.

Prompt engineering: The process of asking AI chatbots questions that can produce desired responses. As a profession, prompt engineers are experts in fine tuning AI models on the backend to improve outputs.

Rationalists: People who believe that the most effective way to understand the world is through logic, reason, and scientific evidence. They draw conclusions by gathering evidence and critical thinking rather than following their personal feelings.

When it comes to AI, rationalists seek to answer questions like how AI can be smarter, how AI can solve complex problems, and how AI can better process information around risk. That stands in opposition to empiricists, who in the context of AI, may favor advancements in AI backed by observational data.

Singularity: A hypothetical moment where artificial intelligence becomes so advanced that the technology surpasses human intelligence. Think of a science fiction scenario where an AI robot develops agency and takes over the world.