24.03 Liontrust Global Innovation Report - The Rise of AI 04.24 - Flipbook - Page 35
from Adobe’s stock catalogue and the public domain, meaning
all images are safe for commercial use with no IP infringement
concerns. With that peace of mind, we used Adobe’s online
Photoshop application to embark on a creative mission: send the
Global Innovation team to outer space.
The final image, which you can see on the previous page, is
far from perfect, but it is a giant leap from what we could have
achieved without Firefly’s AI assistance.
What did we learn about Firefly? Firstly, the time savings are real:
tasks that would have taken hours – such as mastering various tools,
sourcing and uploading content, assembling the final image, and
colour correction – were accomplished in less than a lunch break
thanks to Firefly’s AI assistance. Secondly, it was easy to achieve
quality: tools were not only intuitive and required minimal technical
skill, but also produced high-quality images. The precision of AI
tools like ‘select object’ ensured clean and accurate details (no
jagged edges or missing ears), while the text-to-image generation
simply required written prompts to create images that were fully
contextually appropriate (heads fit in space suits, everything was
on-theme). Lastly, these tools fostered creativity: Firefly’s generative
image capabilities allowed us to overcome creative blocks,
offering the flexibility to either guide the AI with detailed prompts or
explore new ideas with more open-ended suggestions. This blend
of efficiency, simplicity, and creativity not only saved time but also
made the creative process more accessible and enjoyable.
These elements help bring to life how Adobe’s Firefly AI model can
boost productivity while also democratising the creative process. Its
intuitive design, ease of use, and overall efficiency not only save
time but also lower barriers to entry, making creative endeavours
more accessible to a wider audience. This is a boon for consumers
and a strategic win for Adobe: improved productivity leads to
increased user engagement and retention.
Managements’ formal quantitative guidance on future revenues and
earnings weighs heavily in analysts and investors’ expectations for
companies. When it comes to the overall economy, investors and
economists obsess over the US Federal Reserve Federal Open
Market Committee (FOMC) members’ dot plots (the committee’s
expectations on interest rates over time) and other such metrics from
the Fed and other major central banks.
The tyranny of numbers is well illustrated by a story the late, great
Nobel Prize winning economist Kenneth Arrow used to tell about
his first ever job as a weather forecaster in the US Air Force
during World War II. After a while, Arrow determined that his
forecasts were not much better than pulling predictions out of a
hat and wrote to his superiors asking to be relieved of the duty. He
received the following reply: “The Commanding General is well
aware that the forecasts are no good. However, they are required
for planning purposes.”
Indeed, numbers are usually at their best when they are supported
and enriched by qualitative detail and colour. How well are the
newest products being received by early adopting customers? How
is the order book shaping up? Where are the snags in supply
chains, are they improving or getting worse? Are customers feeling
the pinch? Are they trading up or trading down?
Enter LLMs, which are not just about processing vast amounts of
data. They excel in understanding and interpreting language. This
means they can analyse qualitative information with a degree of
nuance and insight previously unattainable and hold the promise of
finally putting due weight on the detail and the colour with forecasts.
Furthermore, the beauty of LLMs is that they are simple to use.
Certainly, we found that building a basic version of a forecasting
model that incorporates qualitative information is achievable with
less than an hour’s work.
Meanwhile, democratising technology in this fashion expands Adobe’s
user base beyond professional designers, opening up new markets for
growth. The tangible impact of Firefly is already evident: over three
billion images have been generated since its beta launch in March, with
a remarkable 90% of Firefly web app users being newcomers to Adobe
products. This statistic not only highlights the customer value creation of
these AI tools in general, but also underscores AI’s role in driving a new
wave of growth for companies such as Adobe in the years ahead.
We are bottom-up investors and spend most of our time
researching individual companies. Nevertheless, an accurate
and balanced view on the economy is very helpful. To illustrate
our point, we took the US Federal Reserve’s FOMC minutes
(which contain the committee’s detailed discussion and debate on
economic conditions and the outlook) and fed them into an LLM
(Open AI’s ChatGPT-4) to build a simple model to use to forecast
US economic growth.
Animal Spirits: using LLMs to forecast the economy
“Not everything that counts can be counted. And not everything
that can be counted really counts”, Albert Einstein is believed to
have said. Indeed, in this industry of investing in which we ply our
trade, numbers rule. And no more so than in the immensely difficult,
usually hated, but often unavoidable task of making forecasts.
In terms of the specifications, we took each set of December
meeting minutes (the committee meets eight times a year) from the
past 30 years and asked ChatGPT to score the FMOC’s outlook
for economic growth over the year ahead on a scale of 0 to 10
based on their broad qualitative discussion of macroeconomic
conditions.
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