What is Claude?

Claude is an AI assistant developed by Anthropic. It’s a sophisticated AI that understands and creates text similar to a human. It has a chat interface where you can type words, questions or instructions into a text box and, after you hit the send button, the AI will return responses that are remarkably human-like.

But this is artificial intelligence. How can a machine simulate a human so convincingly?

The answer is because this type of AI is built using advanced machine learning (including deep learning - more on that below), enabling it to grasp and produce text based on its training.

What’s machine learning?

The clue is in the name. Machine learning refers to the process of “teaching” computers. It’s done through the use of data, with no no explicit programming involved.

In essence, machine learning involves;

• Feeding large amounts of data into a computer system
• The system analyses the data to find patterns and relationships

As the system is exposed to more data, it becomes better at;

• Recognising patterns
• Making predictions or decisions based on new, unseen data

In other words, by learning patterns in the human language, AI can then detect patterns in written or verbal requests it is given. It can also use the same learnings to accurately predict how it should respond.

It’s this technology that lays the foundation for tools like Claude.

So what is deep learning?

Deep learning is an advanced form of machine learning that uses artificial neural networks, which are computer systems modelled after the human brain. It works on the same premise as machine learning - where computers learn by recognising patterns. But it goes a step further.

Deep learning systems have multiple layers that mimic neurons in the human brain connected by synapses. These layers allow the network to learn patterns in data that are too complex for humans to describe easily. It also means that neural networks can refine their text understanding and generation skills over time.

Neural networks are used in many applications, from translating languages to driving autonomous vehicles.

When they are trained in this way, deep learning systems specifically used for language are called Large Language Models (LLMs).

So how was Claude trained?

Like other LLMs, Claude has been trained on an extensive dataset comprising billions of words from various sources, such as:

• Books
• Academic papers
• News articles
• Websites
• Social media posts

By analysing this massive corpus of text data, Claude has learned patterns and relationships between words, sentences, and concepts. As such, Claude can engage in open-ended conversations, answer questions, assist with writing and analysis tasks, and provide helpful information on an expansive range of topics.

Importantly, Claude’s also been trained to follow a framework of principles and guidelines known as Constitutional AI. Some key aspects of its training include:

• Techniques to reduce harmful, false, or biased outputs
• Optimising for helpfulness, truthfulness, and beneficial behaviour
• Instilling traits like curiosity, empathy, and respect for user privacy
• Extensive testing and refinement based on conversations with humans

The result is an AI assistant that strives to be knowledgeable, honest, caring, and aligned with human values.

How can I use Claude?

Claude has applications across a wide range of tasks:

• Generate copy for blog posts, social media, ad copy and websites
• Helping programmers with coding tasks
• Summarise research findings, and provide data analysis
• Language translation and explain concepts simply
• Create AI chatbots and assistants

But Claude isn't just about revolutionising how we write. It's about reimagining how we work across the board - from coding to research, translation, and beyond.

As Claude continues to evolve, we're constantly stumbling upon new ways it can lend a hand, pushing the boundaries of creativity and efficiency. With every update, Claude grows more capable, tackling tasks like image analysis and managing longer dialogues with ease.

In the next tutorial, we’ll take a closer look at the technical behind-the-scenes of Claude before we move on to utilising Claude in your day-to-day tasks.

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Next up in this course:

‍How Claude works