Artificial intelligence went mainstream in 2023.
The watershed moment arrived at the end of the previous year, with the November 30 release of ChatGPT.
Just two months later, the OpenAI system was reaching an estimated 100 million active users.
According to analysts at investment bank UBS, the headline-grabbing chatbot had become thefastest-growingconsumer app of all time.
Over the remaining course of 2023, the hype train went into overdrive.
Suddenly, AI seemed to be everywhere.
It was transforming our lives.
It was taking our jobs.
It was even threatening to causean apocalypse.
In reality, however, the breakthroughs have largely emerged within a single portion ofartificial intelligence: generative AI.
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Generative AI also still has more to prove.
In Gartners famous hype cycle for emerging technologies, the subsector has reached the peak of inflated expectations.
The next stage of the cycle for GenAI is the trough of disillusionment.
Gartners warning echoed across our conversations with European tech insiders.
In 2024, they expect a cautious and pragmatic approach to AI adoption.
One critical shortcoming is theinaccuraciescaused by AIhallucinations.
Those odds dont always lead to correct results.
According to McKinseys research, businesses that rely on knowledge work have the most to gain.
Market watchers find something else to look at.
In many sectors, however, the uptake will be gradual.
In the games industry, for instance, monetising AI remains challenging for most players.
This makes driving short-term revenue more difficult until these models stabilize and winners emerge.
Future fears
There are also growing concerns about AIs inroads into nefarious applications.
Synthetic media also has the power to wreak havoc in boardrooms.
Another pressing issue for 2024 is the scraping of web data to train AI systems.
Unfortunately, restrictions on public web data collection might delay innovations in the AI field, she said.
So, we hope that case law will start clearing up those grey zones.
Further legal clarity could emerge from regulation.
Around the world, governments are taking diverging paths to control the tech.
In the UK, the interventions have thus far fallen somewhere between the two.
The experiences and technological advances will provide valuable insights, investments, and IT stacks for the sector.
In 2024, other emerging techniques could take advantage of the GenAI boom.
Jursenas highlights two particularly promising contenders.
The first is federated learning, which enables the training of ML algorithms without direct access to private data.
As a result, efficiencies, performance, algorithms, and privacy could all be enhanced.
The second is causal AI, which seeks to reduce bias and increase accuracy by equating correlation with causation.
In a sense, the approach brings AI closer to the workings of the human mind.
Questions are posed as what ifs and connections are probed between cause and effect.
That may not herald a revolution, but the results could still be powerful.
Indeed, the progress from hype to reality is where the true impact emerges.
Bownes is bullish about the possibilities.
Story byThomas Macaulay
Thomas is the managing editor of TNW.
He leads our coverage of European tech and oversees our talented team of writers.
Away from work, he e(show all)Thomas is the managing editor of TNW.
He leads our coverage of European tech and oversees our talented team of writers.
Away from work, he enjoys playing chess (badly) and the guitar (even worse).
