It is estimated that AI will drive 95% of all customer interactions by 2025. So it’s no surprise that over the last 12 months, AI has been one of the most discussed topics around the world.
Tools like Runway, Jasper and Midjourney have dominated these conversations and it seems, at least with the introduction of OpenAI's ChatGPT, there is no avoiding artificial intelligence. Companies are feverishly searching for meaningful uses for it - however with so many options and opportunities where do you start? How do you leverage AI to drive growth for your business as well as for time savings via automation, and on top of that, which tools are best suited for your business?
In this talk, Bastian will guide you through the various AI tools you should be considering, the strategies to drive business growth, and supply plenty of practical examples along the way.
Bastian Grimm | Peak Ace AG | @basgr
The Rise of AI
Tools, Strategies & Tips to Drive Growth
June 21st 2023
A bit of a warmup…
Stock Photo or AI?
Which image was created by a machine/AI?
Midjourney V5 has got REALLY good… just wow!
Our all-time favourite AI text-to-image generation tool that's available right now:
Source: https://www.midjourney.com/ & https://pa.ag/3C11Zwo
Back when it all started with DALL-E in April '22
DALL-E was primarily responsible for the fact that "mainstream media" started talking
lots more about AI as a topic in general:
DALL-E & Co are/will be deeply integrated to MS products
Microsoft recognised the potential of OpenAI early on, as they already invested in it
back in 2019. In January 2023, MS invested another $10 billion – just because…
Sources: https://pa.ag/3J6pSGb & https://pa.ag/3ZDKJaT
Both Microsoft Designer and
Image Creator are powered by
DALL-E 2 - the AI art
generator made by OpenAI.
Microsoft invested $1 billion
in OpenAI in 2019 and has an
exclusive license to use.”
Actually, it‘s much more than that: meet MS365 Copilot
This isn't strictly a topic for marketing, but "interacting with AI“ will soon be part of your
daily (work) activities – and you might not even know it:
Sources: https://pa.ag/3ASowLb & https://pa.ag/43z5tC0
Invoking Windows Copilot is easy – the button is front and center on your taskbar –
simple to find and use. Once open, the Windows Copilot side bar stays consistent across
your apps, programs and windows, always available to act as your personal assistant.
Various alternatives, e.g., Dream Studio by stability.ai
Need help and/or inspiration? Try DS Prompt Builder:
Super-simple drag & drop prompt
building based on visual elements to
choose style, lightning, etc.
Creating AI prompts is a key skill for any generative AI
Whoever formulates the best, most creative and most unique AI prompts will create the
best content (and save AI/API credits)
There is a marketplace (promptbase.com), which is
dedicated to trading prompts – use it for inspiration!
Each AI has its strengths and weaknesses…
The challenge: What to use when?
BlueWillow.ai to combine the power of multiple models
such as DALL-E, Stable Diffusion and more
What about real-world
use cases though?
If you need product ads/images fast, try flair.ai
AI-generated product photography using a drag-and-drop approach that allows you to
place product imagery in literally any environment you can think of:
Remove any unwanted object, defect or even people from your picture in seconds
Another very practical use-case:
Scan me, I am a very beautiful QR Code!
General use-cases include building header images (for
blog posts), email & social images, and quick image
modifications for your marketing efforts
What (else) to use it for?
Interesting but equally scary use-case from Osaka Univ.
“We propose a new method based on a diffusion model (DM) to reconstruct images from
human brain activity obtained via functional magnetic resonance imaging (fMRI)”
Reconstructing visual experiences
from human brain activity offers
a unique way to understand how
the brain represents the world,
and to interpret the connection
between computer vision models
and our visual system.
Speaking of scary stuff…
50% of AI researchers believe there’s a
10% or greater chance that
humans will go extinct from our
inability to control AI.
A bit like… catching a flight when 50% of
engineers think there's a 10% chance that
everyone on it will die. Would you get
on the plane?
Voice- & face cloning is already very much possible
Granted, it’s not perfect just yet, but it’ll do the trick. Solutions such as ElevenLabs.io or
frameworks such as DeepFaceLab are available for free/at-minimum cost, to everybody:
Good afternoon, everybody, this is President
Obama speaking! My dear friend Bastian
asked me to say hello.
De-age the face
Replace the head
AI-powered face-swapping tech caused $622k fraud
In China, AI-powered face-swapping was used to impersonate a friend of a victim
during a live video call and receive a transfer of 4.3 million Yuan:
AI-generated image caused a brief stock market dip
A fake image showing an explosion near the Pentagon was shared by multiple verified
Twitter accounts last Monday, causing confusion and a brief dip in the stock market:
So, just imagine what’s out there
that we don‘t have access to…
What did I bring for you today?
A bit of theory Must-have tools Real-world use cases Future outlook
AI vs. Search
Some more theory first
A timeline of AI and
Larger data sets = more innovations in NLP
For example, MUM uses a text-to-text Transfer Transformer (T5) trained on the Colossal
Clean Crawled Corpus (C4), which is significantly larger than BERT's training data
Basis: Web crawl (220 TB)
with approx. 3 billion
with approx. 56 million
From a marketing standpoint it's easy to say
that MUM is 10 times smarter than BERT…
Megatron-Turing NLG (Microsoft & Nvidia): 530 billion
Pathways Language Model 2 (Google): 540 billion
WuDao 2.0 (Beijing Academy of AI): 1.5 trillion
There are many more...
But: OpenAI estimates diminishing returns on scaling size
“I think we’re at the end of the era where it’s going to be these, like, giant, giant models,”
Altman told an audience at MIT, “We’ll make them better in other ways.”
Newly built from the ground up with true multimodality, high
efficiency in using external tools/APIs, memory capabilities, etc.
Google is working on a brand-
new model: Gemini
Quality vs. quantity: Breaking down training data sources
“A Comprehensive Analysis of Datasets Used to Train GPT-1, GPT-2, GPT-3, GPT-NeoX-
20B, Megatron-11B, MT-NLG, […]“
Can you really trust the info in those training data sets?
The idea: to precisely time malicious modifications just before a snapshot for inclusion
in a web-scale dataset, aka “Frontrunning data poisoning”:
If an attacker can precisely time
malicious modifications just prior
to a snapshot for inclusion […],
they can front-run the collection
procedure. […] Even if a content
moderator detects and reverts
malicious modifications after-the-fact,
the attacker’s malicious content
will persist […]
Problems & challenges with (large) language models
”Training a single BERT base model (without parameter tuning) on GPUs was estimated
to require as much energy as a trans-American flight.” [Source: Mozilla]
The quality of the results
improves as the size of the
LLMs increases. Gains are
incremental, while costs
Biased training data
If biased data is used, the
system will likely show the
same bias when making
decisions in practice.
Training a large transformer
model produces 5,680%
more carbon emissions than
one human per year.
Large language models
are usually trained once
and used over long
periods of time.
A more hands-on “bias example” from Amazon
The company developed an AI to help scale recruiting – which didn’t work so well…
Amazon’s computer models were trained
to vet applicants by observing patterns in
resumes submitted to the company over a
10-year period. Most came from men, a
reflection of male dominance across the
In effect, Amazon’s system taught itself
that male candidates were preferable.
It penalised resumes that included the
word “women’s” and downgraded
graduates of two all-women’s colleges.
Have I scared you enough to not
blindly trust anything AI by now?
Next up: Tools
– yup… there is!
If you prefer searching, this
might be of help:
Be very, very mindful of the data
you put into any of those tools.
Overview of AI-based content generation tools
Depending on your needs and desired outcome, I am sure you’ll find one you like:
Use-cases for Jasper, for example, include helping you
write sales copy for outreach emails or content (drafts) for
a blog post, etc.
What to use it for?
Never publish without
checking your output first!
Expect to check and edit content before it goes live!
"As an AI language model" query reveals just some of the
many issues (e.g., lack of quality control, fakes, etc.)
Sources: https://pa.ag/3nuowxU & https://pa.ag/3ALso0B
beatoven.ai: Create customisable royalty free music
Beatoven.ai uses AI music generation to compose unique mood-based music to suit
every part of your creative piece, e.g., video (can be drag and dropped while creating):
More AI audio & music tools
Krisp AI: Removes background voices,
noises and echo from all your calls
Cleanvoice AI: Removes filler sounds,
stuttering and mouth sounds from
podcasts or audio recordings
Podcastle AI: Studio-quality recording,
editing, and seamless exporting –
in a single web platform
soundraw.io: Royalty-free music,
AI generated based on mood,
genre and length.
Descript.com: To write, record,
transcribe and edit video and
Soundbite AI: Turn new and existing
audio and video content into ready-to-
edit social media posts, and summaries.
Want to boost personalised interactions with customers?
Maverick records once but automatically personalises for all, enabling videos at scale.
The Peak Ace team used MURF.ai for a cost-effective
localisation of video ads assets:
Transcribe original script and
localise into desired language
Input your localised copy
and export script
Decide on the voice and style
you'd like to use
Add the new script to your video and
adjust until it sounds perfect
New FR version
Our task/challenge: A client wanted to use a video in different
regions but didn’t have local employees to voice the scripts.
Other video AI solutions worth checking out:
Gen-2 by Runway in particular looks crazy cool:
Just look at how it transfers the style of any image or prompt to every frame of a video:
Source Video Generated Video
Compose AI: A Chrome extension to make you fast(er)
A free Chrome extension to automate your writing
MailMaestro: Bringing OpenAI LLMs directly to Outlook
Generate custom emails and responses based on short prompts; create one click email
thread summaries including action points for the receiver:
Create more, better LinkedIn content with AI using Taplio
Establishing a personal brand on LinkedIn is a key pillar of growth. Stop wasting endless
hours writing your next post and get fresh ideas using Taplio’s content inspiration layer:
ExcelFormulaBot: turn your problem into a formula
Transform your text instructions into Excel formulas in seconds
(yep, I know: ChatGPT can do that as well…)
Otter.ai for automated meeting notes & summaries
Your meeting assistant that records audio, writes notes, automatically captures slides,
and generates summaries:
Word of advice (and caution, again):
It's super practical but getting consent to
record is important – especially since some
services can automatically send meeting
summaries by email afterwards! Also, I am
not a lawyer.
Akkio.com: Grow faster with No-Code ML
Create custom ML models in minutes without a technical background:
Things Peak Ace has done with Akkio and their models:
Sales forecasting –
e.g., understanding when
customers are likely to buy.
Churn prediction –
e.g., finding out which
customers are likely to
Lead scoring –
e.g., understanding which
sources generate the highest
ChatGPT is currently using OpenAI’s GPT-4 model
Including capabilities for browsing (Bing) as well as plug-in usage
What makes a good prompt and how do you structure it?
Some tips to create better and more efficient prompts for ChatGPT (h/t Mike King):
Role: Who is ChatGPT creating as?
Context: What is the situation it is creating for?
Instructions: What specifically do you want it to do?
Format: How do you want it to return its response?
Examples: Samples of the output that you expect for pre-tuning.
Constraints: What should ChatGPT not do?
ChatGPT combined with AIPRM (prompt mgmt. plug-in)
Access a curated selection of ChatGPT prompts specifically designed for SEOs,
marketers, sales, support, copywriting and more :
ChatGPT browsing mode using Bing search:
Essentially, OpenAI uses Bing search to enrich output based on automatically generated
queries taken from the original ChatGPT prompt:
ChatGPT plug-ins for more productivity/efficiency
e.g., LinkReader allows direct interaction with PDFs, Word documents, etc.
Direct integrations into LLMs through
plug-ins are going to significantly
change the web’s ecosystem
The new kid (concept) in town: Auto-GPT
“The main feature is the ability to use ChatGPT to independently create prompts to plan
how to complete a task and then create more prompts for finishing that task.”
If the AI agent finds itself unable to complete the task, it will create new prompts to
figure out how to proceed. [… ] Auto-GPT is self-prompting, removing the need for
creative and detailed prompts. All it needs is a set of goals for a task to complete.
Automation at scale through OpenAI’s APIs
Give it a try using the OpenAI Playground for building/testing your own apps:
Google Ads script: RSA generation based on API calls
Leverage OpenAI’s API to use the maximum number of responsive search ads assets
and, in turn, boost your paid search campaigns:
Source: https://pa.ag/40GipUM & https://pa.ag/3phXv1B
Another interesting idea:
The "new Bing" – Microsoft going all-in on AI in search
Bings’ integration of OpenAI’s LLM into its search engine kicked-off a whole series of
changes for search in general (some changes are still to come):
It’s still early days, but initial ad integrations are available
How will targeting work? What’s the model? How about bidding? So many questions …
Naturally, Google has something brewing as well…
Meet Google Bard (which is not officially available in Europe just yet…)
Just use a VPN service of your
liking and set your IP origin to
the US, or Switzerland even.
Search Generative Experience;
supercharging search with generative AI
Google‘s Search Generative Experience (SGE)
Join the waitlist (if you’re not already on it): g.co/Labs (US proxy needed)
Your marketing team needs to be thinking about
adapting their SEO strategy, as obtaining organic traffic
is likely to get much more difficult in the future.
Why should you care?
Organic search results will change, but so will ad creation
and the integration of ads into the search results.
Google to introduce
generative AI for ads as well
So, where are AI & LLMs
headed in the future?
Amazon entered the game with impressive initial results
Amazon has released a new language model that outperforms GPT-3.5 on ScienceQA
by 16 percentage points, or with 75.1% to 91.6% accuracy
Amazon researchers came
up with Multimodal-CoT,
which combines visual
features in a separate
training framework, to
reduce the effects of these
And their own on-site search is most probably next:
Language models using APIs for even better results
This paper shows that LMs can teach themselves to use external tools via simple APIs
Toolformer: A model
trained to decide which
APIs to call, when to call
them, what arguments to
pass, and how to best
incorporate the results into
future token prediction.
With one significant goal in mind:
Models will generate their
own training data
Because today’s LLMs make stuff up
Models will fact-check
What if a model could use only the most relevant subset
of its parameters to answer a query vs. running through
every single one of its parameters instead?
Massive sparse expert models?
MS introduced Kosmos-1, their first multimodal model
Kosmos-1 can reportedly analyse images for content, solve visual puzzles, perform
visual text recognition, pass visual IQ tests & understand natural language instructions:
True multimodality is going to be
a significant step in AI evolution!
Planning for Artificial General Intelligence and beyond
“As our systems get closer to AGI, we are becoming increasingly cautious with the
creation and deployment of our models.”
The first AGI will be just a point along the
continuum of intelligence. We think it’s likely
that progress will continue from there […] If this
is true, the world could become extremely
different from how it is today, and the risks
could be extraordinary.
A misaligned super intelligent AGI could cause
grievous harm to the world; an autocratic
regime with a decisive superintelligence lead
could do that too.
The best part of this OpenAI post though?
Successfully transitioning to a world with
superintelligence is perhaps the most important—
and hopeful, and scary—project in human history.
Success is far from guaranteed, and the stakes
(boundless downside and boundless upside) will
hopefully unite all of us.
Meanwhile: World’s first AI-flown fighter jet can dogfight
In a joint project between DARPA and the US Air Force, a special aircraft called the X-62
Vista became the first tactical aircraft to be piloted by AI:
The jet was under the
control of one of four
different AI algorithms
at any given time during
the tests. […] This included
dogfighting in simulated
combat missions, as well as
takeoffs and landings
Are we really ready for this?
How do we put this together and how do we think about
implementing AI to grow our business? Some ideas:
Automation = efficiency, the
more menial tasks you
automate, the more time you
and your team have to tackle
the bigger picture & creative
items. Don’t forget individual
tasks such as emails or
Budgets are tight. Leveraging
AI tools for content, ad or
image creation and other tasks
to tackle areas that usually
require additional resources
result in cost savings across
multiple areas of a business.
Utilise tools like Akkio
to understand the areas of
opportunity within your
existing business. Identify top
prospects to target and
go after to drive high
Peak Ace: Delivering Digital Experiences