Artificial Intelligence is increasingly becoming a driving force in today’s world, revolutionizing diverse industries and ushering in a new era of technological advancements. This rapidly advancing domain holds immense potential, not just as a tool for innovation, but also as a significant contributor to global economic growth.

AI’s presence knows no bounds, from our smart home assistants to personalized movie recommendations, from systems that compose original music in various styles to the chatbots that suggest the perfect clothing size for you on the e-commerce website. From streamlining business processes to providing rich analytics for improved decision-making, AI’s influence is far-reaching.

Public attention was captivated in November last year when OpenAI launched ChatGPT, an advanced AI chatbot capable of engaging in conversations, providing explanations on complex subjects, generating programming code, and even surpassing university-level law exams. Nvidia CEO, Jensen Huang, calls ChatGPT the ‘iPhone Moment’ for AI. The product is undeniably a groundbreaking innovation marking a pivotal moment for the entire AI industry, paving the way for widespread adoption across a diverse range of end-user applications.

Microsoft and Google have since unveiled their aspirations for AI-powered search. Microsoft solidified its longstanding partnership with OpenAI, committing to a substantial “multiyear, multibillion dollar investment” to integrate ChatGPT technology into Bing search. Meanwhile, Google introduced its highly anticipated Bard chat bot to the general public.

AI products are revolutionizing the generation of models in text, image, video, and voice formats, yielding fantastic results. However, achieving this rapid progress has necessitated numerous development steps and substantial efforts from the global IT industry.

Growth does not come without a price, and it is essential to consider the vital resources needed to power the exponential surge in AI adoption that we are currently witnessing.

In the development of the AI sector, key resources we consider essential include robust data centers, state-of-the-art hardware equipment, reliable energy sources, and comprehensive regulatory frameworks.

Specialized Hardware

AI workloads need specialized processors to efficiently handle complex algorithms and big data. While GPUs dramatically accelerate AI and are typically 20x more energy efficient than CPUs, training sophisticated models still requires a significant amount of energy.

An estimate by New Street Research revealed that Bing’s search, powered by the OpenAI-based ChatGPT model, may need over 20,000 8-GPU servers to provide quick responses to user queries. This could result in a staggering infrastructure cost of approximately $4 billion for Microsoft’s feature. Considering the massive scale of Google, the GPU expenditure alone could reach $80 billion.

These figures underline why companies need to invest in computing power when integrating AI models into their business. This is one of the reasons why we, at Scalo Technologies, are optimistic about the cloud computing and high-performance computing sectors.

Expanding Data Centers

Artificial Intelligence workloads increase power usage and density in data centers, as they demand more energy-intensive computations than traditional workloads. The increased power demand strains existing data center infrastructure, as high-power densification levels require unique engineering approaches to address the substantial heat production.

As computing speed lags the increasing demands of AI, utilizing more computing units becomes necessary. This spotlights the importance of interconnects within data centers for parallel processing. Strong connectivity between computing devices, storage, and memory is also crucial due to the high-speed data access and transfer rates required by AI workloads.

There are also existing issues within the data center supply chain that affect manufacturing items such as cooling equipment, power generators and other equipment.

More Energy Power

Another problem is the availability of scalable areas and electricity access. European DCs, for instance, tend to cluster around major financial centers such as  Frankfurt, London, Amsterdam, and Paris (FLAP markets). However, expansion in these urban locations is limited due to space, cost, and energy constraints.

In a 2021 research paper, it was revealed that GPT-3, an all-encompassing AI program capable of generating language and serving various purposes, consumed 1.287 gigawatt hours during training. To put this into perspective, that’s approximately the amount of electricity consumed by 120 average US homes in a year.

According to Google’s findings, artificial intelligence accounted for 10 to 15% of the company’s total electricity consumption. This implies that Google’s AI alone consumes approximately 2.3 terawatt hours each year, equivalent to the electricity consumed by all the households in a city comparable in size to Atlanta, US.

Call for a Regulation

As AI’s potential continues to grow, the risk of its misuse in areas such as bias, misinformation, and fraud also increases, highlighting the urgent need for governments to quickly implement suitable and balanced regulations for this technology.

Creating a governance model to fully utilize AI’s potential, while safeguarding users and maintaining legality, is a significant challenge. Machine learning systems, with their potential application in millions of scenarios, resist simple classification and pose multifarious issues for regulators.

Given wide-ranging application of Artificial Intelligence, there’s a pressing need for common principles and regulations. These guidelines should address key areas such as data privacy, algorithmic transparency, accountability, and fairness. They are essential to ensure that AI technologies are used ethically, responsibly, and do not inadvertently harm individuals or communities.

Various entities, including governments, international organizations, and tech companies, have started to recognize these needs. The European Union has proposed regulations that set a legal framework for AI, focusing on transparency and accountability. Similarly, tech companies like Google and Microsoft have established their own AI principles, emphasizing aspects like fairness, inclusivity, transparency, and accountability.

Striking a balance between regulatory oversight and fostering an environment for the development of advanced AI-based products is crucial for a technology that is still in its growth phase, and continually evolving through constant innovation.

Conclusion

While the challenges are substantial and will demand concerted efforts across various sectors of the economy, as well as swift, intelligent decisions from government, we remain confident in our ability to navigate the majority of current and future obstacles. AI is poised to continue its transformative impact on how we live.

Nick Bostrom, philosopher at the University of Oxford, suggest that just as humans outcompeted and nearly eradicated gorillas, AI will surpass human development and ultimately dominate. We, however, believe that AI will work alongside humans to address the world’s most pressing issues.

Scalo Technologies is committed to fostering AI innovation by investing available resources into the development of new AI-based products. We see a future where AI aids humanity, rather than replaces it.