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Increase in AI utilisation helps us learn about human brain function

AI allows for a simulation of neural networks reminiscent of neural networks found in the human brain.

Humanity has made significant strides to push the boundaries of developing new technologies. From the invention of smartphones and other intelligent devices to the development of cloud-based apps and cybersecurity software, it seems there are limitless possibilities.

However, if there is one great leap for mankind in the tech industry, it is their progress in the artificial intelligence (AI) industry. Today, many people enjoy the convenience of AI technology in the form of digital voice assistants and automation tools that handle repetitive business processes. 

Over the years, AI has become increasingly visible in consumers’ daily lives and has improved many industries. AI technologies are almost everywhere, from recommendation algorithms that provide product suggestions on e-commerce platforms to AI assistants like Siri and Alexa.

Aside from artificial intelligence becoming increasingly prevalent in the daily lives of consumers today, it has also been evolving at an unprecedentedly rapid pace. Its evolution has drawn the interest of experts in the fields of human brain function and deep learning.

The utilisation of deep learning algorithms in artificial intelligence has become the object of fascination for these experts. It’s mainly because it allows for a simulation of neural networks reminiscent of neural networks found in the human brain.

Incorporating deep learning algorithms into artificial intelligence opens new possibilities for understanding human brain function to develop more effective AI programs. This article will delve into what you need to know about deep learning and human brain function and how it relates to using artificial intelligence.

That includes the current applications of AI technology and how deep learning has been used to analyse brain images and identify patterns. It will also cover how deep learning algorithms open new avenues for neuroscience research and the future of AI technology.

Practical applications of AI technology in multiple industries

While artificial intelligence has been a scientific and academic discipline since 1951, AI technology has gained significant traction recently. As mentioned, AI technology has seen an unprecedented surge in investment, research, and applications for businesses and consumers.

Studies conducted by Grand View Research predict that the worldwide AI market size will skyrocket to 1,811.8 billion dollars by 2030. That is a significant leap upward in market size compared to the 2022 projections of 136.6 billion dollars with a 38.1% CAGR. AI applications promise to yield better results for businesses and improvements in the human experience.

American cognitive scientist and computer scientist John McCarthy first coined artificial intelligence in 1956. McCarthy defines artificial intelligence as “the engineering and science of creating intelligent machines.” 

McCarthy’s definition of artificial intelligence refers to computers or computer-controlled machines to perform tasks typically associated with human beings. This has resulted in artificial intelligence demonstrating characteristics such as discovering meaning and learning from experience or reason.

Today, developments in artificial intelligence technology have made significant strides every decade and are now a viable resource in many industries. Here are the top five most common examples of industries that utilise artificial intelligence in their business operations.

1. The e-commerce and retail industry

E-commerce and retail platforms are arguably the best space in which the application of artificial intelligence is most observable to most end-users. Since it is a competitive space, retail companies always seek ideas to identify consumer behavior patterns.

They can then adjust their strategies to align with these patterns and gain a competitive advantage. These strategies typically include boosting their page content and promoting products through discounts or social proof.

Businesses that want to stay abreast of emerging technologies may have writers create content for them, but they also use AI writing tools to help with keyword research or develop ideas. Some even use AI to fact-check some of the statements or statistics they include in their posts.

If you are wondering where AI technology plays a role in e-commerce and retail platforms, you do not need to look that deep into it. The product recommendations on platforms like Amazon, Shopify, and Facebook Marketplace are excellent examples of real-time utilisation of artificial intelligence.

In the simplest explanation, product recommendation systems are complex AI algorithms that determine which products each user will likely buy due to many factors. These factors include the end-users search, view, and purchase history. There are even cases where Google or Facebook may contribute to product recommendations across platforms based on your search history on the respective platforms.

There is also a significant increase in artificial intelligence applications and text analytics software for enhancing the customer experience and improving market research. A great example is the many AI-powered chatbots available on e-commerce platforms, which are programmed to provide instant responses to a wide array of typical customer queries.

2. The financial and banking services industry

In recent years, the banking and financial services industry has undergone massive changes thanks to the onset of artificial intelligence applications. This is because the use cases of artificial intelligence are numerous in these industries.

In many examples, intelligent software robots programmed to process loan applications in less than seconds are now replacing human agents. Additionally, robo-financial advisors can recommend the right investment decisions to customers by sifting through numerous levels of data in milliseconds.

These robo-advisors can analyse users’ emails, social media activity, and other personal information. Their purpose for analysing this data is to identify the companies and sectors aligned with their long-term objectives and needs.

AI-based chatbots are also being deployed into the insurance industry to boost the customer experience and build insurance products and plans based on customer data. Additionally, the utilisation of AI-based software significantly reduces the processing time for claims. This helps both the customers and the insurance companies.

Another critical application of artificial intelligence in the finance industry is fraud detection. Fraud detection refers to activities that prevent the acquisition of money or property through false pretenses.

A typical example is when Mastercard utilises AI-based decision intelligence technology for detecting fraudulent transactions. The AI program can detect these fraudulent transactions by meticulously analysing many data points.

3. The healthcare industry

Technology giants such as IBM, Microsoft, Apple, and Google have provided contributions that hold significant importance for the healthcare industry. Thanks to these contributions, artificial intelligence plays an integral role in many healthcare services.

These services include medication management, medical imaging, robotic surgery, and drug discovery, to name a few. However, one of the most important of these services is data mining. It’s because it identifies patterns to accurately diagnose and treat medical conditions.

One example is the application of the AI tool known as IBM Watson. This tool can derive the context and meaning of structured and unstructured information sets that may be crucial to treatment plan selection.

After deriving the meaning and context of the data sets, it can analyse a patient’s medical record to discover potential treatments. Simply put, the IBM Watson AI tool functions like a human physician.

Other platforms like Artificial Intelligence for Drug Discover or AIDD are AI systems developed by a biopharma company called NuMedii. Essentially, AIDD leverages the use of AI and big data to detect the link between drugs and diseases at the systems level.

4. The transportation and logistics industry

Another industry on the verge of an AI software revolution is the transportation and logistics sector. Using predictive analytics and machine learning has changed supply chain management and made it a seamless process.

Most warehouses in North America today use AI software for packaging and sorting the products stored in them with more efficiency and precision. Additionally, AI algorithms are increasingly utilised to search for the fastest shipment routes and assist last-mile delivery.

The transportation industry will feel the massive impact of AI technology, with self-driving cars on the verge of becoming the next big thing. Despite still being in the research and trial stages worldwide, AI-based self-driving vehicles have the potential to replace manual driving to make roads safer.

The current companies at the forefront of AI use research for self-driving car technology are Uber, Volvo, Volkswagen, and Tesla. This research is also on its way to leveraging AI solutions to optimise and improve public transport for routing, scheduling, and traffic light management.

5. The gaming and entertainment industry

If you look into the entertainment industry, AI and automation technology greatly help broadcasters and program producers. This is because it can identify which programs to recommend to streaming service providers like Netflix, Disney+, and Amazon Prime Video users.

These streaming companies use AI-based recommendation systems to improve customer satisfaction through a more personalised user experience.  

The film industry uses AI to enhance digital movie effects to hasten the pre and post-production processes and reduce costs. For example, Natural Language Processing or NLP is a viable tool for structuring scripts for storyboarding while data is utilised to organise an optimal filming schedule.

In the music industry, major companies like Spotify and Apple use AI to recognise customer interaction patterns to provide appropriate music recommendations to users. Additionally, AI-powered accompaniment technology allows machines to compose music in real-time that responds to musicians during live performances.

Lastly, this list would not be complete without mentioning the gaming industry. Developers in the gaming industry are arguably the first and best when it comes to AI adoption and development in their games.

To say the impact of AI technology was profound in the overall player experience is an understatement. After all, what makes a good game aside from storyline, visuals, and gameplay are the beloved unsung heroes known as the NPCs.

A non-playable character or an NPC is essentially one of many bots that play characters that drive any video game’s overall story, mechanics, and difficulty. Most gamers today argue that without these bots, there would be no world-building, story, or game.

Understanding deep learning

The section above highlights the increase in AI utilisation across many sectors. Now, it’s time to learn more about deep learning and how it correlates with using artificial intelligence.

Within machine learning is a subset known as deep learning. It entails training artificial neural networks through learning from large, complicated data sets. By design, deep learning models automatically identify features and patterns in data without having explicit programming for it.

In typical deep learning systems, the input data goes through multiple interconnected node layers called artificial neurons. Each artificial neuron processes a subset of information and then transfers it to the next layer for further refinement. The final layer is responsible for providing the output used by the system to make classifications and predictions.

Deep learning is best suited for tasks like autonomous driving, natural language processing, and speech and image recognition, where the data input is complex and high-dimensional. Deep learning systems have achieved impressive results in many fields, including natural language processes, game playing, and computer vision.

How do human brain function and deep learning correlate? 

The human brain’s structure and function serve as the inspiration for the design of deep learning models. Their most significant similarity is that they rely heavily on neural networks to process new and old information.

The human brain comprises billions of neurons with complex connections to form networks. These neural networks transmit and process information through the brain, enabling humans to reason, perceive, and act according to what they comprehend.

Similarly, deep learning models are a composition of artificial neuron layers that interlock into a network. Each artificial neuron obtains input from the other neurons to run computations before transferring output to the next layer. This transfer enables the model to represent and learn complex relationships and patterns in data.

However, deep learning models and the human brain also have their share of differences between them. A prime example is how deep learning models are usually feedforward networks, meaning the data flows through the network in one direction.

In contrast, the human brain is massively interconnected and can process data in multiple directions. Additionally, the methods used in how deep learning models learn from information differ from how the human brain learns.

Deep learning models are conditioned to use a mathematical algorithm called backpropagation, which adjusts the weights between neurons based on prediction errors. On the other hand, the human brain relies on various learning mechanisms, including synaptic plasticity and Hebbian learning.

Despite the glaring differences, deep learning models have proven powerful tools for solving complex problems across various domains. Through mimicking human brain structures and functions, deep learning models can represent and learn patterns in information in ways similar to human brain processes.

The next chapter of deep learning and human brain function through AI

To say that AI utilisation is the next big step for advancing deep learning and human brain function is an understatement. Utilising AI technology contributes to scientific knowledge advancements, human health improvements, human capability enhancements, and complex problem solutions.

In a nutshell, the convergence of neuroscience and AI can potentially transform many aspects of human life, from education and healthcare to entertainment and industry. By taking advantage of the strength of both fields, humanity can accelerate human progress and develop new technologies.

Zoran Markovic

Zoran Markovic is a reporter at Breakthrough.

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