I'm reading about the history of artificial intelligence, and this passage on the development of machine learning is a bit confusing. Can you help me summarize the key ideas, emphasizing the role of data and algorithms in shaping this field? 

Here's the excerpt: 

Machine learning, a subfield of artificial intelligence, emerged in the 1950s as a way for computers to learn from data without explicit programming. Early work in machine learning focused on developing algorithms that could recognize patterns and make predictions from data. The rise of computing power and the availability of large datasets in the 1980s and 1990s led to a resurgence of interest in machine learning, with researchers focusing on developing more sophisticated algorithms and applying machine learning to a wide range of applications, including image recognition, natural language processing, and robotics. This evolution has been driven by the increasing availability of data and the development of powerful algorithms capable of analyzing vast amounts of information, leading to significant advancements in machine learning capabilities.
I'm reading about the history of artificial intelligence, and this passage on the development of machine learning is a bit confusing. Can you help me summarize the key ideas, emphasizing the role of data and algorithms in shaping this field? 

Here's the excerpt: 

Machine learning, a subfield of artificial intelligence, emerged in the 1950s as a way for computers to learn from data without explicit programming. Early work in machine learning focused on developing algorithms that could recognize patterns and make predictions from data. The rise of computing power and the availability of large datasets in the 1980s and 1990s led to a resurgence of interest in machine learning, with researchers focusing on developing more sophisticated algorithms and applying machine learning to a wide range of applications, including image recognition, natural language processing, and robotics. This evolution has been driven by the increasing availability of data and the development of powerful algorithms capable of analyzing vast amounts of information, leading to significant advancements in machine learning capabilities.
user
- Machine learning aims to enable computers to learn from data without explicit programming.
- Early machine learning focused on developing algorithms for recognizing patterns and making predictions.
- The growth of computing power and large datasets in the late 20th century led to a resurgence of interest in machine learning.
- This resurgence has seen the development of more sophisticated algorithms and applications in areas like image recognition, natural language processing, and robotics.
- The availability of large datasets and powerful algorithms have driven significant advancements in machine learning capabilities.
assistant
Generate a series of (instruction, response) pairs that are similar in context and structure to the example provided below. Each pair should consist of a concise instruction followed by an appropriate, detailed response. The instruction should pose a clear task or question, while the response should provide a comprehensive answer or solution that could be understood by someone with a basic understanding of the subject.

Example pair: 
Instruction: Im going through an article on the best digital nomad jobs, can you summarize these paragraphs about travel blogging into bullet points for me? What should I know about travel blogging beforehand?

Here is the excerpt:

Few digital nomad careers combine the work-and-travel lifestyle in such a meta way as travel blogging. 

The industry has grown and become very competitive over the last decade, but it is never too late to learn how to start a travel blog. If you can provide fresh and original content, people will want to read that shit.

Obviously, you don’t have to write about travel. Some of the most profitable types of blogs are about lifestyle, fashion, and finance, for example.

One crucial way to make money as a blogger is through affiliate marketing. Affiliate marketing means recommending products on your site, including links to them, and if a reader buys the product through your recommendation link, the blogger gets some money without an extra cost to the reader. (That’s how we afford to keep The Broke Backpacker ad-free!)

Learning effective affiliate marketing strategies is a gold-plated highway, a gift that keeps on giving. You do need the traffic – but once you’ve got the eyeballs, affiliate marketing is a pretty simple way to get a lot of passive income.
Response: - Travel blogging combines work and travel.

- It’s very competitive, but that’s not a reason not to try. If you write original content, people will want to read it.

- Blogging can be about subjects other than travel.

- Recommending products and providing affiliate links is a great way to make money.

- Affiliate marketing can generate a lot of passive income once you have the audience.

Your task is to generate more pairs that maintain this level of clarity and detail. The topic is Summarization. Write a long text of instruction by yourself, then summarize the given instruction in a response. Ensure that the responses are informative and accurate, suitable for an educational context. 

Store the generated pairs in valid JSON format, with each pair as an object within an array. Each object should have two key-value pairs: "instruction" and "response". For instance: 

{"contents": [{"instruction": "text", "response": "text"}, {"instruction": "text", "response": "text"}, ...]} 

Remember to maintain consistency in the format and ensure the generated pairs are diverse and cover a broad range of subjects. You must return the response in the asked format and you must not add any additional text in your response.
