AI is not a new technology. The first known software that might qualify as AI was a program designed by Christopher Strachey that could play checkers in the 1950s. Video games have featured allies and enemies with increasingly complex decision-making throughout their history. It’s been 28 years since Deep Blue defeated world champion Garry Kasparov in chess and 14 years since Watson defeated Jeopardy! greats Ken Jennings and Brad Rutter. In fact, the question of when AI was created mainly depends on what you consider to qualify as AI.
So why is it that in the 2020s, AI finally became such a huge buzzword and both an opportunity and a threat to businesses?
1. Advancements in Computing Power
One of the biggest reasons AI has surged in recent years is the exponential growth in computing power. The computing power needed to run even a basic AI was experimental, expensive, and proprietary not long ago. Now it’s virtually a guarantee that you know at least one person who uses that kind of computing power to play Fortnite. Thanks to high powered consumer electronics, even small businesses and individuals can access AI tools that were once reserved for governments and tech giants.
2. The Explosion of Data
AI thrives on data. The more information it has, the better it performs. While the internet no longer seems like a new technology, it’s still growing at an incredible pace. The internet contained 64 times the data in 2020 than it did in 2015. Machine learning models, particularly deep learning models, require extensive training data, and now they have more than enough to learn from.
3. Breakthroughs in Machine Learning and the Transformer Model
Of course, research and development on AI models has been key as well. For decades, AI models relied on techniques like recurrent neural networks (RNNs) and convolutional neural networks (CNNs) for processing text and images. However, a major breakthrough came in 2017 with the introduction of the transformer architecture in the paper Attention Is All You Need by Vaswani et al.
Transformers revolutionized natural language processing (NLP) by allowing models to process entire sequences of text in parallel rather than step by step. As a result, AI models became much more adept at considering context clues in a prompt.
4. The Rise of Generative AI
Previous AI applications were largely task-specific, excelling at narrow functions like playing chess or recognizing speech. The 2020s saw the explosion of generative AI, which can create text, images, videos, and even music. Tools like ChatGPT, Midjourney, and Runway have demonstrated AI’s ability to generate human-quality content, opening up new business applications across marketing, design, customer service, and more.
The increase in users interacting with AI means that, in addition to generating yet more data for the AI models to consider, AI has become more present to consumers. Ultimately, when people started wanting to pay to use AI, the research increased.
Once AI became more accessible, companies realized its commercial potential. Tech giants like Google, Microsoft, and OpenAI have invested billions into AI research, leading to rapid improvements. The competition to integrate AI into products and services has pushed innovation forward at an unprecedented rate.
5. Pandemic-Driven Digital Transformation
Of course, every change we’ve seen in the 2020s has been affected in some way by COVID-19. With the increase in things like remote work, Zoom meetings, and ecommerce, a lot of work has gone into making each of those more effective. We’ve been reliant on computers for decades for communication with people outside of our immediate circle, but never before have they been the only way to meet face-to-face with your closest colleagues.
Conclusion: It’s everything
It may be a little unsatisfying to hear that all these big changes in the world are because of… all the big changes in the world, but the reality is that this has been a process that started before I Love Lucy. AI has been evolving for decades, but increases in accessibility and demand have brought it to the forefront of the global discourse. Artificial Intelligence and Machine Learning aren’t just things we think the store is using to track our purchases anymore – we use them too.
As AI continues to evolve, the question is no longer if businesses should adopt AI but how they should do so responsibly and strategically.
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