News about artificial intelligence appears almost daily. AI capabilities are improving every month, and many people are increasingly afraid of losing their jobs. But AI can not only replace certain professions, but also provide new opportunities for earning money. Let’s figure out what neural networks are and how to build a business with their help.
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The history of artificial intelligence
The idea of creating artificial intelligence arose in the 1940s. The founder of this technology is considered to be the English mathematician Alan Turing. In 1950, he published the article “Computing and Intelligence”. It was in this work that the famous Turing test was first made public. Its essence is to test the machine’s ability to reproduce human speech. During the test, you need to determine where the questions are answered by a computer and where by a person.
In 1956, a conference was held at Dartmouth College at which the leading scientists of the time tried to find out whether computers could simulate human intellectual processes. A definite answer was never found then. But this conference brought together many talented specialists who were working on the problem of machine learning. Participants also identified the main tasks of AI:
- Pattern recognition.
- Text analysis.
- Management and planning.
- Automatic programming.
- Systems modeling.
At the same time, the first programs were created that could solve simple problems.
In the 1960s, scientists began creating expert systems that used human expertise to solve complex problems. In the 1970s, the first neural networks were created – information systems that imitate the functioning of the human brain. In the 1980s, the first artificial vision systems appeared and were used for image and face recognition. In the 1990s, the first chatbots and agents were created that could communicate with people. Today, artificial intelligence is used in a variety of fields, from medicine to finance. It helps optimize work processes, reduce costs and improve the quality of services.
Artificial intelligence and neural network: differences
Artificial intelligence and neural network are two terms that are often used in the field of computer science. They are related, but have some differences.
A neural network is a machine learning algorithm that uses interconnected nodes to form conclusions and decisions based on input data. Neural networks can learn from large amounts of data, allowing them to make accurate predictions and solve complex problems. Examples of uses of neural networks include image processing, speech recognition, price forecasting, and more.
Artificial intelligence is a broader term that includes not only neural networks, but also other machine learning methods. Artificial intelligence is used to solve various problems. But most often for data analysis, pattern recognition and creation of robots. There are already many artificial intelligence tools that can greatly simplify your workflow. For example, ChatGPT, Bard, GigaGPT, Notion AI, Bing AI. They allow you to receive answers to queries, speeding up the search for information. They also help explain complex concepts in simple terms and generate detailed instructions for performing specific tasks.
If you want to create a computer program that recognizes pictures of animals, you can use AI. But if you want the program to learn to recognize the animals themselves, then you need to use a neural network. The neural network will learn from specific examples and find patterns in the data.
How to make money on AI and neural networks
With the development of technology, it is possible to make money on artificial intelligence. For example, one of the most popular business ideas is the creation of startups that use AI technologies in their work. You can also start developing algorithms for neural networks. In addition, now more and more companies need large volumes of monotonous content. In this regard, more and more copywriting vacancies for neural network training are appearing on HH.ru and other job search services. However, it is important to learn how to correctly write technical specifications for AI. Today, the best results are shown by programs written in English, where the tasks for the neural network are clearly articulated.
How to sell texts written by AI
The simplest task for artificial intelligence is collecting information and structuring it. Therefore, AI quite easily composes a variety of simple texts: from leads and headlines to selling articles.
IMPORTANT! Neural networks do not know how to admit that they are wrong. They just make up an answer if they can’t find the facts. In addition, most neural networks are limited to information from 2021, so they cannot generate information about current events.
Most often, articles written by a neural network are ordered by web studios, marketing and SEO agencies. Also, text content is required by entrepreneurs who sell on marketplaces or in online stores. Such clients need unique texts for product cards. You can search for customers directly or through freelance exchanges. If we talk about the latter, then it is worth taking a closer look at the following resources:
- Upwork: One of the largest and most well-known platforms, offering a wide range of job categories from web development to content writing.
- Freelancer: A diverse marketplace for freelance jobs, including software development, writing, marketing, and design.
- Fiverr: Known for its unique structure, where freelancers offer specific services or “gigs” starting at five dollars.
- Toptal: A more exclusive platform focusing on connecting top-tier freelancers with large companies and clients.
- Guru: Offers a range of freelance jobs, notable for its robust project management tools.
- PeoplePerHour: Popular in Europe, this platform connects clients with freelance workers for hourly or project-based work.
- 99designs: Ideal for designers, this platform is for graphic design work, including logos, web design, and more.
- Aquent: Specializes in marketing and creative industries, offering both freelance and temporary staffing solutions.
- FlexJobs: Known for its remote and flexible job offerings, including freelance opportunities.
- Behance: Operated by Adobe, it’s more of a portfolio site but also offers job listings, mostly in the creative fields like graphic design and photography.
IMPORTANT! When working with AI, always double-check the facts in the text that is written by the neural network. Even a request to provide links to sources does not guarantee that the facts will not be distorted.
To generate text, you will need to compose an industrial text. When writing it, consider the following points:
- The purpose and purpose of the text: first you need to understand what you want the finished product to look like. This is necessary to ensure that the generated texts meet your requirements.
- Language and style: You should specify the language in which the text should be generated and the preferred writing style.
- Keywords and phrases: using keys helps the neural network understand what text you want to end up with.
- Detail: for example, you generate text in the style of Lewis Carroll. It is very important to use details that are characteristic of his writing. Otherwise, the neural network will not be able to create text that meets your requirements.
Neural networks: creating illustrations
Artificial intelligence can generate not only commercial texts, but also pictures that meet customer requirements. This is an excellent solution when you need to create a large number of illustrations on a small budget.
IMPORTANT! It is difficult for neural networks to work with human images. Typical problems are incorrect transition from head to neck, distorted facial expressions and implausible fingers.
There are enough services on the Internet for generating images: Midjourney, Stable Diffusion, Craiyon, Kandinsky. But to get a suitable image here, as when working with text generation, you need to create a promo. For this it is important to consider:
- Purpose and task: where the image will be used. For example, if in the site interface, then you need to indicate this.
- Type and format: what the image should be. For example, photography, art, etc.
- Limitations: it is necessary to specify what the neural network should not use.
- Result: to get a high-quality picture, you need to write down detailed instructions: colors, poses, etc.
Creating programs using neural networks
The development of scripts and full-fledged programs is another popular area for making money on AI. Many specialists want to automate part of their work processes, so the target audience for this format is quite wide.
ATTENTION! Most neural networks are limited to 2021 data. This does not allow the use of modern libraries and leads to errors in code generation.
To prepare the program code, you will also need to create an industrial process. The following requirements apply to it:
- The purpose and purpose of the code: it is worth breaking a large task into several small ones, then the code will be easier to generate.
- Programming language: the language in which the code should be written.
- Limitations: Necessary for the program to work as you require. For example, I used a strictly allocated amount of memory. As a rule, after creating a program code, it is necessary to optimize it. Therefore, you will need knowledge of the basics of development.
How to create your own neural network and make money from it
To create a neural network, you need to understand mathematics, statistics, and programming in Python or R. You also need to understand how machine learning libraries, such as TensorFlow or PyTorch, work. Training neural networks requires a lot of information, so chatbots and image generators are easier to work with in a large team. This way you will have enough data for initial training. The ideal solution for novice programmers would be to use existing neural networks and adapt them to their tasks.
ATTENTION! Most neural networks do not allow the generation results to be used in the commercial sector. Read the license agreement carefully to avoid getting sued.
Conclusion
Artificial intelligence and neural networks are powerful working tools that are gaining popularity among entrepreneurs. Their use helps businesses solve many problems and reduce costs. In addition, the use of neural networks allows you to automate a number of routine tasks. For example, to implement new functionality on the site, you will no longer need to contact third-party developers.
Answers to frequently asked questions
Q: How to test a business idea for making money using a neural network?
Ans: Conduct market research and determine which group of people are most interested in your product or service. Research the needs and problems of your audience that you can solve using AI and neural networks. Then develop and release a test product. Analyze feedback from potential customers and improve your product. After this, you can proceed to analyzing the results and launching the project.
Q: How to implement your business idea to make money using a neural network?
Ans: Find a suitable neural network to implement your idea. Today there are several hundred projects that solve a variety of problems.
Q: Is there any risk in the business idea of making money through AI?
Ans: This area is still under active development and can be unpredictable. For example, there may be problems with the confidentiality of user data. However, if you develop a strategy correctly and use AI wisely, then your project has every chance of becoming profitable and successful. It is also important to consider legal restrictions and security rules when working with user data.