The 6 Best Programming Languages for Artificial Intelligence

Artificial Intelligence (AI) is seeing wicked adoption rates in 2023, so much so that the most successful companies in the world are finding unique ways to integrate it. Take Facebook for example, they’ve innovated and re-branded into Meta to show their intentions of branching beyond a social media platform. While services like Skype, once a mere video call platform, have now integrated chatbots that can be used just as you would Chat GPT.

On the back end, software engineers are using AI tools to enhance the coding process, but this raises the question; who’s building the platforms that do the building? Now, AI tools are in no way suggesting that software engineers will be out of jobs anytime soon; rather, it’s a step in the direction of enhanced results from developers since programming can now be done more efficiently. 

Who’s Interested in Using AI Extensions?

Integrating AI into your platform can be done on any size scale using tools like Chatbots, Machine Learning, process automation, etc. What’s important to know is that for a platform to measure the effectiveness of artificial intelligence solutions, the main place to pay attention to is customer satisfaction. Recent research is suggesting that AI improves customer retention by nearly 70% and that those who are most interested are aged between 18-24.

How to Make It Work for You

The future of AI technology is unfathomable right now because it’s still too new with so much left to discover. 

While the future of AI technology is still unfathomable due to its novelty, programming is the backbone of anything digital, making mastering AI a top priority for software engineers. With that being said, here are the 6 best programming languages that help software engineers create seamless AI platforms:

1) Python

There is no debate when it comes to AI development that Python is a necessity. It’s an interpreted language which means that programming can be executed on the fly without needing to be compiled. 

The important role that machine learning plays in AI performance should be noted. Machine learning trains the system to act a certain way and is a key subset of AI. During AI integration, this makes development happen fast and machine learning algorithms can be tested quickly. 

2) Java 

Java is a language that can be used in just about any platform to handle the server side (behind the scenes) of the operation. Software developers will resort to using Java when building AI solutions, specifically when they’re trying to build a multi-faceted application or incorporate machine learning algorithms. 

Outside of AI, there is a strong case for Java being a more efficient option for certain tasks than Python since it’s compiled. However, software development is contextual. For instance, if a FinTech was implementing software for data analysis, Python would be the better option. 

3) Julia

This language is fairly new in the programming world with a small community of software developers utilizing it already. Though it’s not as widely used as other languages, it has earned its position among the best options for AI programming languages.

The main draw to Julia for software developers is its performance and speed which is said to be greater than Python due to its compiled nature. Oftentimes, Julia is used for data analysis which is why it’s commonly compared to Python.

4) R

R is a language with one primary role in AI development; number crunching. Data is significant and difficult to handle during software development, which means that to arrange it efficiently, you’ll need some math skills. This means that R will come in handy during machine learning development.

With that being said, here are some of the best R packages for Machine Learning development:

• CARAT: Useful for training integration and predicting models. 

• Gmodels: Provides tools for fitting models.

• Nnet: Perfect for AI as its purpose is to replicate how the human mind functions. 

• Tidyr: As the name implies, this package is used to tidy up data. Specifically by observing rows, inserting variables in columns, and value in cells.

5) Lisp

Any seasoned software developer with experience in AI will tell you this is one of the oldest languages still used in software development.  The name is an abbreviation for “list processing” which makes the language a great option when working with complex data structures. 

A few features under the hood of Lisp include:

• Program modification (into data)

• Rapid prototyping

• Creating dynamic objects

• Collecting garbage

• Running programs based on data structures

The program remains highly sought after because it’s highly flexible and easily able to express the programmers’ intent.  

6) C++

This language is known, like many of the other languages we’ve listed, for its speed and interoperability with machine learning and neural networks. As anyone would guess, developing an AI application is highly complex and data-intensive which makes having languages that are quick, reliable, and efficient a necessity for software engineers. 

When it comes to AI, C++ is going to be able to handle a lot of low-level programming which translates directly to a programmer's ability to manage the production of AI models. 

Choosing a Programming Language

Tech stacks are chosen based on several factors that every project entails. First, what resources are available? What kind of budget is the team working with? What is the timeline, talent expertise, hardware and infrastructure involved, etc? Considering the languages we’ve looked into in this article, some strong tech stack choices would include:

• PyTorch: Supports Python, C++, and CUDA.

• OpenCV: Supports  C++, Python, MATLAB and Java.

• TensorFlow: Supports Python, C++, and Javascript

• Keras: Supports Python

This gives a sense of how software developers would structure the infrastructure for an AI platform and also demonstrates that languages complement each other to build something great. 

The Takeaway

Software development services are highly adaptable which is what makes them so sought after by businesses of all sizes. If you’re trying to find the best programming solutions for your business, you’ll need to evaluate the long-term goals driving that desire. 

AI is just another step in the direction of inevitable change that industries are undergoing as a response to the advancement in consumer interests and the technological resources available to accommodate them. If you think your business deserves these enhancements to respond to the changes in your industry, don’t hesitate— get started.

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to Fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

What Software Engineering in Finance is Like in 2023

We talk a lot about software development in the financial world, and for good reason— this is a hot-button topic that needs attention. Financial services are data intensive and heavily rely on the analysis and interpretation of that data. This can include (but is not limited to) interest rates, stocks, income/cash flow statements, and balance sheets. 

It can be a lot to take in when looking at how IT brings innovation to an organization; in this article, we’re going to break it down simply. We will look at why software engineering is so important in the financial industry and some examples of what businesses should look out for to ensure they have the best possible team leading their digital transformation journey.

Every financial firm will have its unique requirements, the software is just there to help keep everything functioning seamlessly. Development teams working for financial service providers need to be aware of this, by recognizing the unique requirements of the industry and remembering they are there to provide solutions…

Why would we say that? Software developers know what to do for FinTech companies right? 

Software development for financial firms is high pressure since the business is naturally extremely high pressure, which means that there’s just about no room for error in any utilized IT systems. 

When errors do arise it can be extremely detrimental, in the United States alone, faults from IT systems take out $150 billion from the economy annually. 

This is intimidating for both software developers and the companies who invest in their services, but it is why reliability, credibility, and transparency are such important aspects when it comes to choosing a software development team.

The Best Software Engineering in Finance Looks Like…

Finance and banking are among the top 5 industries demanding software engineers according to industry reports, with entry-level salaries starting at over $110,000. In addition, more than 95% of financial companies deem it “critical” to have solid software engineers in order to sustain the company long-term.

The job of a software engineer is strictly to examine, make predictions, and come up with comprehensive software solutions based on the variables they’ve examined. As a software engineer working for a financial service provider, the projects in scope may include:

• Process automation

• Mobile app development

• Technology integration (Such as Blockchain or Crypto)

• Verification software

• Cybersecurity

• Embedded finance

**If you don’t recognize some of the topics, check out our previous blogs on them**

When a financial service provider hires a software development team, they’re not looking for someone to put a bandaid on their current processes, they want innovative solutions and digital transformation to make their services stand out in the most competitive market in the world. 

Digital transformation, like anything else in running a business, will look different for everyone. 

However, with experienced software engineers, you can find the future that looks exactly like the vision of success you’ve always wanted. This may include (but again, is certainly not limited to):

1. Cloud computing: This is one of the most prevalent trends in software development as a whole for its ability to store and access data. For a banking/finance company, this is everything to their users and it leads us to the next point.

2. Mobile Banking Services: Let’s not forget, two-thirds of the American population alone use mobile banking for their day-to-day needs. In 2023, mobile banking is a nonnegotiable for young consumers especially, which tells you everything you need to know about where the industry is headed. 

3. AI: By now, Artificial Intelligence has entered normal dialogue though it’s caught some people by surprise. For the financial industry, it’s brought many great benefits when it comes to:

   • Repetitive task automation

   • Minimizing errors

   • Aiding in the decision-making process

4. Cybersecurity: The major threats financial firms have to consider when implementing software systems in 2023 include: 

2,200 - The estimated number of attempted cyberattacks each day.

$9.4 million - The average loss financial firms saw from ransomware attacks in 2022. 

Cybersecurity is a necessity in an age where FinTech service providers are at the pinnacle of banking. Companies need to protect their assets and data which is why when software programmers today build systems to protect service providers, they must remember they can mitigate a breach before it is attempted. 

Each of these aspects leads to a well-rounded platform that users will feel comfortable relying on. More than that, it’s something that can be sustained long-term which makes it better for companies who want to scale their operation. 

Where Custom Software Makes Scaling Easy

When you invest in custom software, it’s not a temporary fix— rather, it’s a foundation being implemented that when it continuously undergoes innovation can take a company from a startup to a large-scale enterprise. 

For instance, a custom mobile app could help a FinTech startup grow its user base by reaching new users, while customized cybersecurity measures can protect against potential threats as the company scales. It’s the little things like this that make a big difference long term.

The Takeaway

Software engineering is where the majority of the heavy lifting happens since execution is based on the analysis done during this time. To maximize the results a company sees from software development, prioritizing the planning stage is a crucial step. Lay everything out on the table; current pain points, long-term goals, market research, etc. Putting this in the hands of the right software development team will guarantee the best possible outcome. 

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.

How Experts Use APIs and Microservices During Software Development

API development and Microservices are often confused with each other. This is a big misconception and a potential conceptual block during software development since they actually work together to boost the performance of a platform. 

Why is this important to know? The answer is simple: it will help you make better decisions when designing and developing your software application. Without that information, companies can expect some very challenging and expensive mistakes to say the least…

In case you’re unfamiliar with the terms “API” or “Microservice”, let’s break it down:

What is an API? (Application Programming Interface)

An API is essentially a toolbox full of routines and protocols that developers use when building software applications. There are several benefits they offer, but the key one is that they allow users to interact with software systems by exchanging and communicating information. 

Specifically, a developer would use an API to integrate certain functions and services into an application rather than creating one from ground zero. 

What are Microservices?

On the other hand, microservices are collections of independent services that are then used to design and operate the software with the help of APIs. Each microservice communicates with the other using APIs and offers unique benefits and capabilities that are highly beneficial to the platform.

For example, think of the shopping cart feature in an e-commerce store. When you add an item to your cart, the front-end application sends a request to the shopping cart microservice. The microservice then updates the cart and sends back a response to the front-end application that your item has been added.

By breaking down the functionality of the shopping cart into its own microservice, it becomes easier to scale and maintain the application as a whole. 

In addition, software developers use microservices so they can take a more Agile or DevOps-focused approach which in turn leads to an architecture that provides greater flexibility and scalability.

APIs + Microservices = ???

While it's true that microservices and APIs fall under the same umbrella in the broad scope of custom software development, each has its duties that make them super useful to one another. For instance, APIs are specifically designed to feed functions and data to different applications whereas microservices handle organizing the application's internal architecture. 

Ultimately, what you will have in this case is an application with various features for users to interact with (thanks to your API development) and then the microservices will handle what’s going on behind the scenes which is what allows the application to function so smoothly.

Differences and Similarities

By now you know that microservices need APIs to materialize an application, but then what makes it fair for us to say they are their own entities?

The interconnectedness of microservices depends on APIs to communicate which one could argue makes them perform in unison. However, APIs act as the link that enables different components of the tech stack to interact seamlessly, which, when working for a large-scale enterprise, is often a non-negotiable for their platform. 

Whether you’re a software developer or not doesn’t matter, this is information everyone in a business should know. With that being said, here are 4 differences and 4 similarities you’ll find when examining APIs and Microservices:

Differences:

• APIs enable communication between different software applications, while microservices form the application.

• APIs give life to a platform (by providing functions and services to various applications) while microservices keep it standing. 

• APIs can be used in a wide variety of contexts and architectures, while microservices are specifically designed to be used in more of a decentralized architecture.

• APIs tend to be more lightweight and simple than microservices, which can be difficult and require more resources to function properly.

Similarities:

• Both APIs and microservices are used in custom software development.

• APIs and microservices both rely on communication between various software components.

• APIs and microservices work together to create a seamless and high-performing software application.

• Both APIs and microservices improve flexibility, scalability, and agility during software development.

FinTech Example

When it comes to custom software development, knowing what tools to use and when to use them is probably the greatest possible advantage that development teams can have. However, to do this effectively, the team needs tunnel vision on the end goal. 

When it comes to APIs and microservices, the two work together to do many things, for example, if a FinTech company was building a payment processor, these are some of the tasks the tools would perform:

• Communicating with banks

• Database analysis

• Keeping the database up to date

• Scheduling recurring tasks

• The transaction process

• Generating PDFs for invoices

• Sending emails

What you see here are the tasks that the payment processor would rely on using API and microservice integration. Note that while each function works autonomously, they rely on APIs to communicate with each other. 

APIs can be used to activate a variety of tasks which is critical, but alone, they would not be able to fully operate the payment processor. Since the platform will need functions such as initiating charges, establishing customer profiles, generating invoices, subscribing to services, processing returns, and managing inventory, the processor would need the 6 microservices to do so.

What it Means to Have a High Functioning Software

While the process of building a sophisticated software architecture/system is complex, it is one of the most rewarding things any business can do in 2023. Why’s that? It is estimated that around 30% of business is done online in the United States alone. Without capitalizing on that, it means companies are only going to be able to achieve a maximum of 70% of their potential revenue gains. 

Consumers connect with online services that make their lives easier. A solid IT infrastructure is critical for making those services accessible. More importantly, it helps performance by:

• Minimizing downtime

• Preventing errors

• Preventing bugs

• Boosts data and traffic capacity

• Enhances security

What Have We Learned?

So does your software architecture need to look just like a FinTech payment processor would? Of course not! Custom software development is just that: custom. This makes what you learned in this article about APIs and Microservices just another set of tools to add to your arsenal during your digital transformation journey. Curious about how this could benefit your company? Reach out to book a free 30-minute discovery meeting with one of our lead software experts to talk about how you can apply custom software to your business.

Written By Ben Brown

—

ISU Corp is an award-winning software development company, with over 17 years of experience in multiple industries, providing cost-effective custom software development, technology management, and IT outsourcing.

Our unique owners’ mindset reduces development costs and fast-tracks timelines. We help craft the specifications of your project based on your company's needs, to produce the best ROI. Find out why startups, all the way to fortune 500 companies like General Electric, Heinz, and many others have trusted us with their projects. Contact us here.