The Evolution from Antiquated Code to Cloud Computing: Is there a Role For AI? [GeoWire Weekly No. 122]

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The digital landscape has undergone a seismic shift in the past few decades, transitioning from traditional, monolithic software development practices to the modern, agile, and infinitely scalable solutions offered by cloud computing.

This immense sea of legacy code highlights the challenges and opportunities in transitioning to cloud computing, an endeavor that demands innovative approaches and technologies, including the potential, yet debated, role of Artificial Intelligence (AI) – a discussion point elucidated upon by industry expert and COO of a COBOL modernization company, Bonnie Castello, with whom we spoke in mid-January during an Expert Insight Skull Session chat we hosted.

In all, we have a great deal to learn about the companies in which we invest, and it was quite serendipitous that her knowledge was extremely applicable to a former GeoInvesting Model Portfolio holding, Wavedancer, Inc. (NASDAQ:WAVD), an IT infrastructure company focused on the very things she’s been tackling for the majority of her professional career. Her insights helped us gain more clarity into the action of the WAVD CEO to sell its code modernization segment for what we believe is a low-ball price…a situation we’re very angry about (We cover this in our in-depth report here).

The Skull Session has motivated us to consider more calls like this so we can interact with experts that can offer insights into aspects of their respective industries that you’ll likely not get anywhere else.

As a matter of fact, if you haven’t yet, you can listen to our Expert Insight Twitter spaces event  with Joe Hamblin to learn about the cloud communication space, as it relates to stocks in our portfolios.

As we learned from Bonnie Castello, the evolution to more modern code reflects not just a change in technology, but a fundamental shift in how we approach problem-solving, innovation, and global connectivity. 

Some of her insights also reinforced our opinion that WAVD should explore different strategic options than the one that the Board has put on the table.

Still, with all advances made in technology, the staggering volume of 800 billion lines of outdated COBOL code in use today not only healthily eclipses the number of stars in the Milky Way Galaxy, but also underscores the monumental effort required to modernize IT infrastructure of government agencies and financial institutions, where the majority of COBOL lives.

In the early days of computing, software was often developed for specific, isolated tasks. Programs were written in languages like COBOL and Fortran, which, while revolutionary at the time, are often considered antiquated by today’s standards. These pieces of software were typically deployed on-premises, requiring substantial physical infrastructure and maintenance. The code was hard to update and scale, leading to inefficiencies and increased costs.

The Shift to the Cloud

The advent of cloud computing marked a dramatic shift in this paradigm. Pioneered by companies like Amazon with its Amazon Web Services (AWS) launched in 2006, followed by Google Cloud Platform and Microsoft Azure, the cloud offered a new promise: on-demand access to computing resources, scalability, and the ability to innovate faster than ever before. 

This transition wasn’t just technological; it was cultural, pushing developers and companies to think differently about how they build and deploy applications.

Case Studies of Transition

Netflix: One of the most cited examples of a successful transition to the cloud is Netflix. Initially, Netflix’s infrastructure could not keep up with its rapid growth in user base and streaming demand.

The decision to move from traditional data centers to Amazon Web Services (AWS) starting around 2008 allowed Netflix to scale massively and efficiently.

By 2016, Netflix had completed its migration to the cloud, showcasing the cloud’s ability to support massive scale and global availability. (Source: Netflix Tech Blog)

Capital One: In the financial sector, Capital One’s journey to the cloud is noteworthy. Starting in 2014, Capital One embarked on a mission to transform itself from a traditional bank into a technology-driven institution.

By adopting AWS, Capital One could innovate faster, reduce operational costs, and ensure higher levels of security than its previous on-premises solutions could offer. This move underscored the cloud’s role not just in tech-centric companies but across all sectors. (Source: AWS reinvent Keynote)

The Benefits of Cloud Computing

The transition to the cloud offers numerous benefits, some of which include:

• Scalability: Cloud services can scale resources up or down based on demand, making them ideal for businesses that experience fluctuations in usage.
• Cost-Effectiveness: With pay-as-you-go pricing models, companies can optimize their spending on IT resources.
• Innovation: The cloud provides a platform for rapid development and deployment of applications, enabling businesses to bring innovative solutions to market faster.
• Global Reach: Cloud providers operate massive, global networks, allowing applications to serve users with low latency across the world.

The move from antiquated code to cloud computing is not just a technological upgrade; it represents a fundamental shift in how businesses operate and compete in the digital age.

This evolution towards cloud computing has democratized access to technology, enabling startups to leverage the same resources as established companies and innovate at an unprecedented pace.

As we move forward, the cloud will continue to be a key driver of digital transformation, pushing the boundaries of what is possible in the tech landscape.

Integrating AI in Upgrading Old Code Infrastructure to the Cloud: A Perspective

As we delve deeper into the nuances of transitioning from outdated codebases to modern cloud infrastructures, the potential role of Artificial Intelligence (AI) in this transformative journey becomes a topic of significant interest and debate.

Bonnie Castello, an industry expert that we interviewed on January 22, 2024, offered a nuanced view that merits consideration.

The Skepticism Around AI’s Role

Castello, also the COO of Forecross Corp (OOTC:FRXX), presents a cautious perspective on the integration of AI in the process of upgrading old code infrastructures.

Despite the advancements in AI technologies, she points out a fundamental mismatch between the nature of programming language translation and the capabilities where AI excels.

The example of IBM Watson X, with its ambitious project to translate between 1,700 programming languages, including from COBOL to Java, showcases the technological abilities and potential AI holds.

Yet, Castello argues that the structured and formal nature of programming languages may not fully leverage the vast computational and interpretative power of AI.

The Complexity of Programming Languages vs. AI’s Strengths

Programming languages, with their rigid syntax and limited expressions, might not present the kind of challenge that AI thrives on. AI systems perform best in scenarios where there are thousands of possible interpretations for each data point, allowing for complex analysis and decision-making processes

In contrast, the task of translating code from one language to another, while technically demanding, does not necessarily benefit from the kind of deep, iterative analysis where AI outperforms other technologies.

The Role of AI: Beyond Simple Translation

However, dismissing AI’s role in modernizing legacy systems might be premature. While direct code translation might seem like an oversimplified application for AI’s capabilities, there are broader contexts that AI can significantly impact.

AI can assist in identifying inefficiencies within code, suggest optimizations, and even predict potential integration issues when migrating to cloud environments. These capabilities extend beyond mere language translation, tapping into AI’s strength in pattern recognition and predictive analysis.

The Marketing vs. Utility Debate

Castello also touches upon an interesting aspect of the AI discussion: the difference between technological achievements and their practical, marketable value. The ability to automatically convert COBOL to Java is not just a technical milestone but also a strong marketing message that highlights the possibilities AI can offer.

This duality suggests that while the practical impact of AI in certain areas may be limited, its role in driving technological awareness and ambition should not be underestimated.

A Balanced View on AI’s Potential

While Bonnie Castello’s insights point to a cautious approach towards overestimating AI’s role in translating and upgrading old codebases to the cloud, they also open up a broader discussion on the potential applications of AI in this domain

AI might not replace the need for human expertise in directly translating programming languages anytime soon, but its role in facilitating a smoother, more efficient transition to cloud-based infrastructures through optimization, prediction, and analysis is undeniable.

As we continue to explore the capabilities of AI, it becomes clear that its true value lies not in singular tasks but in its ability to augment and enhance the broader technological ecosystem.

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