24.03 Liontrust Global Innovation Report - The Rise of AI 04.24 - Flipbook - Page 17
GENERATIVE AI –
LATE 2010s TO PRESENT
The most recent revolution in AI has been
the rise of generative AI, enabled by the
development of the Transformer model in
2017. This model, introduced in a paper titled
“Attention Is All You Need” by researchers
at Google, was a breakthrough in handling
natural language. It led to the creation of large
language models, such as Open AI’s GPT
(Generative Pretrained Transformer), with an
unprecedented ability to generate informative,
coherent and contextually dependent text.
RESURGENCE –
1990s TO EARLY 2000s
The 1990s and early 2000s witnessed a
resurgence in AI, driven by strong progress in
computing power and scientific developments
in the statistical field of machine learning.
This era saw the development of algorithms
capable of learning from data, shifting
the methodological focus of research from
mathematical rule-based approaches to more
empirical data-driven approaches. The victory
of IBM’s Deep Blue over chess grand master
Garry Kasparov in 1997 was a memorable
milestone, symbolising the potential of AI.
These generative models have already been
applied in a variety of fields, from creating
realistic images and text to aiding drug
discovery. Their ability to learn from huge
datasets and generate new content has
opened up vast new frontiers, which leads us
to the present juncture.
RESURGENCE
1990s 2000s
DEEP LEARNING
G E N E R AT I V E A I
2010s
2020s
THE RISE OF DEEP
LEARNING – 2010s
A turning point in AI history came with the
development of deep learning techniques,
particularly the deployment of neural networks,
which allowed for much richer non-linear
predictions than simple linear regressionbased approaches. This was epitomised by
the success of AlexNet in 2012, a seminal
model that dramatically improved the
performance of image recognition.
These advancements led to the emerging use
of AI in the economy, from internet search to
GPS route planning, both led by Google,
to recommender systems pioneered in
social network feeds such as Facebook and
Instagram. The key to these successes was the
ability of deep learning systems to learn and
predict using huge amounts of data.
The rise of AI: Technology and Innovation Report - 17
