The AI frenzy shows no signs of slowing. The Chinese-developed large language model (LLM), ‘Deepseek’, has dominated headlines, causing turmoil for stock prices in the West.
This ongoing revolution in AI reminds me of the personal computing revolution that took place when I was a student. The AI revolution is similar but on an even larger scale.
The public excitement surrounding AI is understandable. It’s easier for us to prioritise something that we can see, feel, and experience. Nevertheless, the use of generative AI such as Deepseek and ChatGPT is just one of many significant breakthroughs currently taking place. Other emerging technologies, including Artificial General Intelligence (AGI) and quantum computing, offer even more profound potential for society.
AI as we know it today is not without merit. It can solve complex problems, perform repetitive tasks more efficiently, and act as an almost limitless learning tool. But, it has also taken on a near mythical quality in the public psyche, as if it represents the pinnacle of technological evolution. This hype brings risks: disillusionment when AI fails to meet expectations, and worse, an innovation bottleneck as funding is channelled into it at the expense of other potentially more significant breakthroughs.
AI’s limitations
Despite its benefits, AI in its current form is actually quite limited. What we call AI today is essentially narrow AI: systems designed to perform specific tasks. ChatGPT, Deepseek, Grok and others are great illustrators of this – brilliant at regurgitating and remixing vast datasets but incapable of true reasoning or independent thought.
AGI, the acronym for artificial general intelligence, represents a theoretical leap that could dwarf large language models. If achieved, these machines would be capable of learning, understanding, and applying knowledge across a far wider range of tasks – in essence, mimicking the cognitive capacity of humans.
The implications of AGI are huge. It could revolutionise not just industries but the fabric of society, creating systems that think and innovate independently. The race is already underway – led by the US, with China in close pursuit. Europe, meanwhile, is watching from the sidelines.
Thanks to Nvidia’s pioneering development work, we are edging closer to the computational firepower needed for AGI.
Despite its potential, AGI research remains underfunded and underexplored compared to the deluge of resources flowing towards its more marketable but limited cousin, ‘narrow AI’. This is partly because AGI’s potential is tougher to quantify and its timeline more speculative.
No airtime
While AI’s LLM front monopolises attention, other high-potential fields struggle for airtime.
Advanced biotech offers opportunities to transform healthcare through personalised medicine, CRISPR-based gene editing, and organ regeneration. Quantum computing, set to crack problems that today’s most powerful supercomputers can’t touch, is suffering a similar hindrance – from molecular modelling for drug discovery to optimising logistics at an unfathomable scale.
These fields, alongside AGI, share a common problem: the lack of mainstream attention and funding compared to AI. Marketability is undoubtedly a factor. Chatbots and image generators are tangible, easy to grasp, and embedded in daily life.
They have also become symbols of technological progress, fueling a feedback loop where more attention leads to more investment, generating more hype. Technologies that offer dividends today are understandably seen as more valuable than those that promise the chance of greater dividends tomorrow. However, without a willingness to take that chance, we risk getting stuck in a loop by pouring resources into refining today’s models instead of building tomorrow’s game-changers.
None of this is to say that AI isn’t significant – it is. But we can’t afford to put all our eggs in one technological basket. Governments, investors, and technologists need to widen their lens. Funding should follow breakthroughs, not just targeted at the most visible – and accessible – technologies. The media, too, has a role to play in expanding the conversation beyond the latest AI arms race.
AI alone will not shape our future. Our rate of technological progress will rest upon progress being made across multiple areas of technological innovation, each contributing in its unique way. If we focus only on what’s trending, we risk losing sight of even greater opportunities. In the words of John Sculley, former CEO of Apple: “The future belongs to those who see possibilities before they become obvious.”