The digitization of the modern world has led to an unprecedented amount of data consistently being shared between users. Custom software development, data scientists, and computer science professionals have had to rise to the occasion and find creative solutions to the endless streams of data. They’ve grown into software architecture pioneers and, as a result, have cultivated transformative new digital structures for SEO services and machine learning.
Improving Custom Software Development: Machine Learning vs. Artificial Intelligence
The growing data world has called for quick solutions: SEO services, data analytics, and 2 of the most impactful adaptations: artificial intelligence and machine learning. These terms are often conflated; however, there are a few notable differences before we dive deeper into custom software development and machine learning.
Artificial Intelligence (AI)
AI is a branch of computer science that has several novel applications and complex software architecture. As a discipline, its primary objective is to build “smart machines” that possess the capabilities to perform tasks that humans would ordinarily need to complete. The goal is to create an artificial intelligence that matches that of human intelligence.
Within the AI field, there are multiple subsets to study and that are currently being developed. These AI subsets can be broken down into 2 overarching categories: weak AI and strong AI. Weak AI may also be referred to as “narrow AI” or “artificial narrow intelligence (ANI).”
Weak AI
Narrow AI is an AI that is programmed, trained, and designed for a very specific set of tasks. The focus of their creation is to assist with ordinary life functions and offer assistance in smaller ways. This type of AI is what makes up the bulk of the AIs you have most likely personally experienced or heard of. Despite the name “weak AI,” it actually enables the creation and continuance of several well-known applications. Take Siri and Alexa for example– both of these virtual assistants are made possible through the power of Narrow AI.
Strong AI
Strong AI, on the other hand, is comprised of AGI (Artificial General Intelligence) and Artificial Super Intelligence (ASI).
AGI: A theoretical form of AI. AGI works towards machines harboring intelligence that matches those of humans. This means AIs with a self-aware consciousness with the skillset to solve problems on their own, learn new skills and concepts, and make plans for the future.
ASI: Commonly referred to as “superintelligence.” ASI aims beyond simply matching human intelligence. ASI would surpass the abilities of the human brain. These systems would be more intelligent and have more capabilities than humans. ASI is still completely theoretical; however, custom software development and computer science scholars are consistently working on research. The end goal of ASI is to create an AI that can understand emotion, experience, and problems. The machine would also develop its own emotions, beliefs, and desires. No actual examples of ASI exist. When thinking of this form of AI, you should consider science fiction AIs.
Machine Learning
A branch of AI, machine learning focuses on how algorithms and data can potentially imitate how humans learn. Consistent studies and research hope to improve AI accuracy in these respects. It’s an important aspect of data science that uses statistical methodologies to train algorithms for advanced predictions and classifications.
Machine learning can help identify business questions that are most relevant for success and also assist in finding solutions. It helps uncover several insights during data mining projects that trigger a chain of business and application decisions– positively impacting growth metrics.
How Does Machine Learning Work?
Machine learning works by exploring data to identify patterns with precision and speed. Tasks that have the ability to be completed through data-defined patterns or rules can also be made automated with the help of machine learning. For custom software development companies and others alike, this is a huge accomplishment. Business owners can automate certain SEO services, complete bookkeeping, review resumes, and deal with customer service calls all through the help of machine learning.
There are 2 types of machine learning techniques to keep in mind: supervised and unsupervised.
Supervised Machine Learning
This type of machine learning allows for data collection and production from a previous machine learning deployment. The computer is presented with a training set, a compilation of data points. This method mirrors the way humans learn.
Unsupervised Machine Learning
This type of machine learning involves either the clustering or dimensionality reduction of unlabeled datasets. The computer attempts to derive a pattern or structure to the data without human intervention.
These techniques can be broken down into 3 simple steps:
- ML algorithm uses input data (labeled or unlabeled) to make estimations about data patterns.
- ML algorithm uses an error function to evaluate the model’s predictions. The error function cross-references previous examples of the model to assess accuracy.
- If the current model is a worse fit to the data than previous models, the weights are adjusted to reduce discrepancies. This will continue until a threshold of accuracy is met.
The Future of Custom Software Development
Artificial intelligence is cultivating an entirely new software architecture for developers to explore and adapt to. As AI improves, so does the development industry, and the benefits continue to grow.
Software development projects are a huge undertaking, but artificial intelligence is able to alleviate the brunt of the work. AI has the ability to run tests to automatically manage software quality and performance. Beyond that, it can actually help write certain code! Computers can complete these tasks faster and more accurately than their human counterparts, leaving more time for developers to focus on other pressing issues. AI can handle the repetitive processes and streamline them for more company efficiency. Ultimately, this will make it easier to scale businesses.
Speaking of business benefits- AI can be trained to make decisions based on success and failure rates regarding certain products and features. When it comes to deciding which investments to make, AI can evaluate the best plan of action for you based on previous success, failure, and risk. Minimal risks mean reduced costs since there will be no biases or errors involved.
Software developers can review and fix errors that the AI has flagged for them, which is a cost-effective solution to one of the most time-consuming tasks for developers. In a sense, AI may single-handedly be a panacea to many headaches that custom software development companies face on a daily basis. For more insight into the software development community, keep up with the 245TECH blog.
