The No-Code industry aims to build software solutions that enable non-technical people to create software that previously could only be written by skilled programmers.
The industry is varied, with the most successful tools being website builders, while app builders failed to take off. However, another No Code niche gaining popularity is that of No Code AI tools.
How AI Is Changing the World
AI is changing the world and how businesses operate. Google Translate allows you to communicate worldwide, self-driving Tesla cars promise to make highways safer, and the recently launched ChatGPT promises to become a helpful chatbot.
While the different areas where AI is challenging the status quo appear varied and disconnected, in essence, it is doing the same thing – enabling the automation of tasks that previously were impossible to automate because they required human intelligence.
For businesses, automation creates efficiency and lowers costs. Businesses looking to remain competitive and scale in the coming future must look at how artificial intelligence and how can improve their operations. But, not all businesses can afford to hire software engineers to develop AI systems.
What is Artificial Intelligence?
Artificial Intelligence is hard to define because the boundary between what may be considered intelligent and non-intelligent behavior is blurry.
Popular publications define AI as follows:
Google says it is a set of technologies that enable computers to perform a variety of advanced functions, including the ability to see, understand and translate spoken and written language, analyze data, make recommendations, and more.
Oracle defines it as systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect.
BuiltIn defines it as a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.
I like to think of Artificial Intelligence as an alternative to explicit programming. In explicit programming, the programmer is responsible for telling the computer how to compute the output given some general input.
However, with AI, the computer can analyze data and infer the method for producing output given the input by looking for trends in the data.
What is No Code AI?
Traditionally, AI systems have been developed by software engineers and data scientists using programming languages such as Python. This meant that the only people who could leverage AI to build systems for their businesses were highly technical engineers.
No Code AI aims to democratize this by abstracting AI models so they can be developed without the need to code. This will enable non-technical people to create AI systems for their businesses and compete with bigger companies.
Different platforms on the market offer users the chance to develop systems in a simpler way.
The AI platforms offer different feature sets at different prices. As a result, they may not necessarily be competing for products but will have different use cases.
No Code AI Platforms
Let’s explore the leading platforms:
MonkeyLearn is an AI-powered text analysis tool. It can be used to analyze text to categorize it into different groups, extract intent from comments and perform sentiment analysis.
- It is easy and straightforward to use.
- Integrates well with other tools like Zapier, Google Sheets, custom APIs, and CSV files.
- It allows you to create and train your models to classify text.
It is simple and easy to use and integrates well with other no-code integration tools like Zapier. You can also connect directly to the platform via the API. After which, you can use prebuilt classifiers or train your own models to classify text.
Pricing for the tool starts at $299/month.
MakeML is a MacOS-based Machine Learning platform. While the application is available for Mac, you can train MakeML to create models that detect and track objects in pictures and videos.
In addition, they have a dataset store for sourcing the data you need to train your models. They also have extensive tutorials for learning how to use the platform and build sample apps.
- The pricing of MakeML is comparatively lower compared to most other No code AI platforms. This makes it a great starting point that does not require much financial outlay.
- The website has additional support resources to help you get started ad guide you when you get stuck.
- They have a dataset store where you can source data that you need to train your models without needing to collect the data yourself. The data is also cleaned to make it ideal for training.
They have a free tier; the cheapest premium plan is $4.53 per month.
Obviously.ai is an easy-to-use platform for building predictive models. In addition, it can also be used for regression and working with time-series data.
Obviously.ai supports multiple algorithms for training, but it automatically picks the best one based on accuracy. Best of all, it often completes training models in less than a minute.
- It is incredibly fast.
- It is well-resourced, with tutorials showing you how to use the platform.
- It tries your data against different algorithms and picks the best-performing one, meaning you get the best algorithm without knowing which one is used.
- It provides a REST API and web-based interface to make your predictions after the model is trained.
It has a free plan with limited features and premium plans, with the lowest starting at $399 per month.
Importance of No Code AI Platforms
NoCode AI is important to businesses as it enables them to use AI to automate processes and, as a result, do more with less work. Common use cases for AI in business include:
- Creating chatbots based on sentiment can recommend self-help resources to users. This enables businesses to provide customer support without the need to employ customer support personnel.
- AI can be used to predict fraud in e-commerce and thus can flag suspicious transactions.
- AI-based product recommendations for upselling and cross-selling products to increase sales.
- You can predict customer churn and preemptively send promotions to keep the customers from leaving.
- Automated product classification from images can help make it easier to populate product pages with data.
- Instead of sending emails to your entire mailing list, using past behavior, you can predict which customers on your mailing list are likely to convert and buy products and focus your marketing on them.
Ultimately, No Code AI enables businesses to make more intelligent, data-driven decisions while making sense of complex business situations.
Relationship Between No Code AI and Machine Learning
Most situations we encounter can be modeled mathematically as a relationship between inputs and outputs. Some situations are simple because the relationship between the inputs and outputs is well-understood and, therefore, can be programmed.
However, in some situations, the relationship is not well-understood. We may know the factors that influence the output and their rough effect, but not the exact mathematical relationship.
In Machine Learning, the computer tries to find an approximate mathematical relationship between the inputs and the outputs. Approximate because it predicts outputs given inputs with accuracy reasonable enough to be used practically.
Machine Learning is one of the most important branches of Artificial Intelligence and, by extension, No Code AI. All No Code AI tools use Machine Learning. Machine Learning can be used to learn and predict why customers churn.
It can be used to classify product reviews to identify which team should read the review as feedback. It can be used to train chatbots on the most appropriate responses to take when giving feedback.
Benefits of No Code AI
- No Code AI enables businesses to harness the power of AI without the learning curve.
- The workflow can be streamlined and integrated to pipe data easily.
- Managed datasets make it easier to add new data and retrain the model continuously.
- It allows using a serverless platform, making it easier to scale.
- They often come with options to train models using GPUs in the cloud, allowing greater collaboration as there is one shared platform for all team members.
Now, let’s explore the drawbacks of No Code AI.
Drawbacks of No Code AI
- Most platforms are expensive.
- It is hard to build a custom model and use custom parameters.
- Rate limiting for predictions and training also limits the usage.
Next, check out some of the best resources to learn No Code AI.
The No-Code Guide to Artificial Intelligence and Machine Learning
This book introduces you to AI and gives you a rudimentary understanding without getting you deep into the weeds of programming.
|The No-Code Guide to Artificial Intelligence and Machine Learning: What to Think About AI Today||$13.99||Buy on Amazon|
The book will help you understand the differences between machine learning, AI, deep learning, and neural networks.
Introduction to No Code/ Low Code Course
In the Introduction to No Code/Low Code by Duke University, you will learn how to apply machine learning engineering principles to real-world projects using cloud computing and data engineering concepts.
You will develop machine learning applications using software development best practices and learn to use AutoML for more efficient problem-solving.
AI for Marketing (No Code)
The AI For Marketing (No-Code) course by Udemy covers using artificial intelligence in marketing.
It includes building machine learning models without code to predict churn, sales, and marketing mix, segmenting customers and building clustering models for personalization, and using computer vision and natural language processing to predict consumer preferences.
AI is useful to most businesses, and No Code makes AI more accessible to non-technical business managers. However, the price of some of these AI platforms is restrictive. Therefore, businesses should ensure that they evaluate whether it is worth the cost.
Also, the simplicity of these platforms comes at a cost. The models and processes are not as customizable and configurable as those written in the code. Despite all this, for an emerging industry, the No Code AI landscape is surprisingly rich and will likely grow soon.
Next, you can check out low Code and no code machine learning platforms.