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Table of Contents
 * So What’s New About Generative Tech?
 * What Changed So That Generative Tech Is Happening Now?
 * Advice To Founders Right Now
 * Characteristics Of Generative Tech Products
 * What Will Generative Tech Companies Do?
 * What function does the application serve?
 * Founder Advice
 * What Do Great Generative Tech Founders Look Like?

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GENERATIVE TECH BEGINS


JAMES CURRIER · @JAMESCURRIER · OCT 2022

The biggest change to the Internet since crypto just happened. A whole new world
of applications opened up to Founders in the last 6 months.

We now have high-quality, cheap, fast AI models for generating text, images,
videos, software code, music, voice, 3D models and more – none of which is
copyrighted, and is not plagiarized.

Generative Tech is the next step in software. It’s a new level of human-machine
partnership. It turns deep learning engines into collaborators to generate new
content and ideas nearly like a human would.

Some have called it “Generative AI,” but AI is only half of the equation. AI
models are the enabling base layers of the stack. The top layers will be
thousands of applications. Generative Tech is about what will actually touch us
– what you can do with AI as a partner.

The Generative Tech sector is developing at such a pace that it has already been
validated by real revenues and high valuations, even though we collectively
didn’t have a name for it until a month ago. 18 months after launch, Jasper
apparently reached nearly $100M of revenue and a $1.5B valuation. Open AI, which
powers GPT-3 and other AI models, is rumored to be raising capital at a
valuation of many 10’s of billions. Anthropic, another large model builder, has
raised over $700M.

NFX started investing in the space two years ago and has invested in four
Generative Tech companies so far with more to come.

This week we added Generative Tech as a new investment category on Signal, the
network where investors show Founders what they like to invest in. If you are an
investor or an angel who is focused on this new area, head to Signal and change
your profile so you show up on the list of Generative Tech investors.

Founders: Today, we are encouraging you to create companies in this area now to
catch the best part of the tech adoption cycle. This essay is for you.


SO WHAT’S NEW ABOUT GENERATIVE TECH?

1. A new Internet topology. Until today, the Internet has been characterized by
making database queries to get 1) a stored piece of 2) old content 3) from the
center, out to you on the edge of the network.

Generative Tech changes the topology of the Internet because now 1) unique
pieces of content are 2) generated at the edge of the network 3) in real time by
your action. That’s a major shift, which typically opens up Founder
opportunities.



If Web1 was “read only,” and Web2 is “read-write,” and then Generative Tech is
“read-write-generate” then that makes Web 3 “read-write-generate-own.”
Generative Tech is now happening in parallel to Web3 and moving faster. If
crypto hadn’t happened, we’d probably be calling THIS Web3. But we do have
crypto, so we call this Generative Tech, but other names could be Web3A,
Generative Web or even Generative Internet.



2. Human activities will now change quickly. 1-2 billion knowledge workers will
become faster and better at their jobs. Some will be able to do jobs they
couldn’t do before. New TYPES of jobs will be created. And while some jobs will
be downgraded, threatened, eliminated – and that will cause fear and self doubt
in 10s of millions of workers in the next 36 months – the expansion of people’s
abilities, productivity, and efficiency will vastly outstrip the losses over
all, generating trillions of dollars of value.

For knowledge workers and creatives, going from zero to one in their minds will
never be the same. For instance, writers, students, marketers, coders,
architects, graphic designers, musicians, videographers, sales development reps,
customer service reps, and screenplay writers, who are paid go from zero to
something useful will now be using these tools to generate their first ideas.

Until now, software has been used to refine our initial ideas into something
useful; it was responsible for the second half of the process, if you will, of
going from zero to something useful. But these new generative tools help you
with the first half of the process, taking you from nearly zero to a lot of
initial ideas. And then the old software tools pick up from there and take you
the rest of the way.

Until now, software couldn’t solve the zero to one problem because it worked FOR
us. Generative Tech will work WITH us from the beginning of any project.

Today and for the next few years, this will feel surprising and in many ways
scary. Because those creative moments where you go from zero-to-initial-ideas
has always felt so uniquely human, because it has been so mysterious. The ideas
once thought to come unpredictably only through people’s minds and souls,
emerging from talent, or training, often associated with special people – will
now be generated by something which is not a human, not a co-worker or
collaborator… and something that is not you. This will be disturbing to many
people. However, as with most new human-machine interfaces, we’ll get through
the discomfort and get used to it.

In the next 10 years, we will expect software to collaborate with us. It will be
the new normal.

Steve Jobs said in 1980 that the Apple personal computer was a bicycle for the
human mind. You might say that Generative Tech is a rocketship for the human
mind. The makers of these AI models might say they are actual minds. No doubt
they will get there. We’ve been talking about the inevitability of
software-based minds since the 50s. The first example of the dawn of this era we
felt as a culture was in 1997 when IBM’s Deep Blue beat Kasparov in chess. The
next big leap was when AlphaGo definitively beat Lee Sedol in the game of Go in
2016.

Starting in 2022, Generative Tech is going to have an impact on billions of
workers where they live.

This is a very different level. This is the skillful creation of new things.


WHAT CHANGED SO THAT GENERATIVE TECH IS HAPPENING NOW?

The recent availability of open-source alternatives to proprietary generative AI
models from Open AI is what caused it to tip wide open in the last 6 months. In
short, Eleuther.ai’s GPT-NeoX-20B, launched Feb 2022, is the open source
alternative to OpenAI’s GPT-3 for text generation. StabilityAI’s Stable
Diffusion, launched August 2022, is the open source alternative to OpenAI’s
DALL-E 2 for images and videos. Both have been game changers on price, quality
and ease of access. The cost to generate images has dropped 100X in the last 2
months. (Stability announced a $100M raise three days ago). The friction to
generate output from these models through web and mobile has become “about 10X
easier” in the last 6 months.

Quality generated text, images, code, speech, etc is rapidly reaching human
quality. Many feel we’re passing the Turing Test in several of these content
categories already. It’s hard to measure, but you know the quality when you see
it. As the 2021 Stanford University AI index noted, AI, for some constrained
applications, has moved to a “sufficiently high standard that humans have a hard
time telling the difference between synthetic and non-synthetic putouts.” We are
headed toward “generative everything.”

Because of all these changes, the amount of experimentation has “about 20X’d in
the last two months.” This accelerates the number of applications providing
value and introduces even more people to the community.

It’s an old story in technology: the barriers go down, and boom…Cambrian
explosion. We are in the early innings, but Generative Tech is a thing now. Here
we go.

And we believe it’s going to happen faster than most people think. Unlike
self-driving cars, Generative Tech doesn’t face regulation and doesn’t need to
be perfect to avoid killing people. Unlike VR, it’s already useful, needs no new
hardware, and is getting better rapidly.

As a Founder, you can trust that the cost and quality of nearly every type of
content is good enough today to get your company going: text, images, code,
speech, 3D, video. Certainly, by the time you have your team together and seed
money raised, it will be there. Don’t overthink it. (To show how fast it’s
moving, here’s a 20 minute Podcast.ai of Steve Jobs talking with Joe Rogan. The
voices and the script were all generated by AI.)

Where we are today is just an on ramp. It’s now possible that most of our
software and human-computer interfaces will be significantly augmented in the
next 5 years after 14 years of near stasis. That opens up seams of opportunity
for Founders.


ADVICE TO FOUNDERS RIGHT NOW

To catch this wave as a Founder, you need to move this week, this month – not in
the next 6 months or the next 3 years. Unless you’re on a rocketship already, in
the fast moving water, I would pause what you’re doing and consider focusing on
this.

We’ve already invested in 4 companies in this area over the last two years, and
we are aiming to make more investments in the next 12 months.

Latitude in games. We invested early 2021. Entirely new gaming experiences will
be possible with Generative Tech. Not just adding conversation to your NPCs in
old games, but brand new types of games like AI Dungeon. With their new Voyage
gaming platform, Latitude is leading. They have been at the core of Generative
Tech for 3 years and are now working with AI21 Labs to further integrate Natural
Language Processing into their platform.

Darrow, in legal. A legal claim mining service that uses an AI model to generate
new leads by detecting harmful events. It compiles the details into new legal
cases for law firms. Rather than finding old cases, it generates specific new
ones based on general prompts.

The.com in automatic website development. The.com is a generative platform for
coding and launching 100’s and 1000’s of websites from simple database calls and
lightweight prompts. Instead of you pressing a button to put up a new website,
if a user of yours interacts with your company which changes a record to your
database (which can happen 10,000’s per day), the system automatically generates
changes to websites or creates a new website. On the spectrum between automation
and pure AI, their old product was more on the automation end, but the company
has been moving along the spectrum toward AI (it’s also a good example of
generation at the edge of the network, in real time).

Tailorbird in PropTech. Tailorbird uses deep learning to build new floor plans
for homeowners looking to perform renovations. These plans are generated from
photos and plans taken from the web, and integrated with remote 3D measurements
to generate many new visions for the space. These generated plans are great
starting points, they also reduce time and cost associated with remodels.

When a new sector opens up like this, Founders can typically find low hanging
fruit more easily than in areas that are better understood and thus more
competitive. So get in there.

Here’s what we suggest to Founders, in order:

    
 1. Start a new company to do new things and create new markets (like Darrow,
    Jasper and Latitude did)
    
 2. Start new companies that redo old businesses with this technology at the
    core, not just as a feature. For instance The.com and Tailorbird, or CRM’s,
    customer service software, etc.
    
 3. Add Generative Tech features to your existing product to differentiate it.
    


CHARACTERISTICS OF GENERATIVE TECH PRODUCTS

Generative tech products have two layers.

The bottom layer is an AI model. That is capable of generating novel output
based on inputs that are unique to the user, like OpenAI’s DALL-E, or GPT-3. To
make generalized versions of these can take $100m’s. To make more narrow
versions can be less than $10m and the price is dropping very fast. Open source
versions are already starting to be viable.

The top layer is an application. This is where you can build network effects and
embedding effects to produce durable businesses.



This stack will lower the technical barriers associated with certain fields. You
don’t have to be an architect to generate drawings of a house remodel. You don’t
have to be an illustrator to tell DALL-E what to draw. This is what allows
Generative Tech to unlock new companies and projects.

These emergent companies have certain core characteristics that help place them
on the Generative Tech continuum. Here are 3.


1. ZERO TO ONE → ZERO TO TEN

Generative Tech begins with solving a zero to one problem. The most successful
companies will eventually provide zero to ten solutions, or, put differently,
products that serve the complete needs of the user, and are uniquely animated by
AI models.

You can imagine a version of Latitude’s AI Dungeon that combines the images and
videos to match the text for complete gameplay experiences. Or allows you to
create a persistent online persona using images or sounds generated with AI.

We already see examples of generative AI projects that provide near-finished
products. Projects like SALT, a choose-your-own adventure, 70s-inspired sci-fi
film, uses a combination of Generative Tech tools to rapidly generate videos
(Stable Diffusion, MidJourney, DALL-E), write scripts (GPT-3), and generate
character voices (Murf, Synthesia).


2. REPLACE CURATION WITH CREATION

Generative Tech is personalization in a way we have never experienced it before.

For 20 years, we have been chasing personalization through curation. E-commerce
providers, Netflix and Spotify all want to serve you curated products you’re
most likely to like from their central databases. FB, TikTok and The New York
Times have experimented with curating your experience of their content.

This is a very limited approach to personalization because it is based on
calling existing data. We have been trying to retrofit people’s preferences into
our existing offerings, rather than generating new things that are best suited
to them.

Generative Tech replaces curation with creation. Generative Tech is not a more
sophisticated database call. It can be trained by that database, but its core
function is to generate something new on the edge of the network.

Generative tech skillfully creates novel output. The content, images, or
experiences served to you will not have existed until you asked for it, or
triggered it through some other action or simply by your presence.

This is happening in the music space. Boomy, Amper, Aiva, Ecrett, SoundDraw and
others are a company using AI to generate full-length, original songs in
seconds. Boomy also gives creators the tools to share and monetize those
creations, an example of a Generative Tech layered with SaaS tools. Critically,
Boomy’s AI generates instant music that fits anything from a mood to a genre.
That music has never been heard before YOU decided to create it.

In a pre-Generative Tech world, you might select a playlist for a road trip
curated by someone else. In a post-Generative Tech world, you will generate
entirely new songs that fit your occasion, mood, blood pressure, heart rate,
location, and who you’re with, etc.


3. LOW-FRICTION INTERFACES

Perhaps the biggest breakthrough right now is how easy the Generative Tech tools
are to use. So much heavy lifting is done by the AI models. Friction is removed
from the creative process. DALL-E and Stable Diffusion require only simple text
prompts to generate stunning artwork in 30 seconds.

Often the generation will be automatic. It will happen just by you showing up.
You could imagine a version of SecondLife where two characters enter a house
together, the house could generate something entirely new that fits both users’
personalities like art objects, experiences, music, and characters. Or if you
sell something it automatically generates an NFT. Or, you could imagine displays
of your life that pull from your photos, videos, texts and music. And they’ll be
GOOD.

These will be the next level of human-machine collaboration. It’s a partnership
where you get to be surprised and inspired.


WHAT WILL GENERATIVE TECH COMPANIES DO?

Let’s break down where the next great Generative Tech idea will come from – and
why it can come from you.

For your brainstorming, think: What if I marry one or more base layer AI models
with…



Potential Applications:

Avatars, Photo sharing, Video streaming, Legal services, Angel and VC investing,
Stock picking, Investment banking, Investment advice, News, Sports,
Architecture, Interior design, Home design, Selling real estate, Landscaping,
Event planning, Payments, Loans, Credit cards, Sales, Marketing, Advertising,
Copywriting, Screenwriting, Social networking, Dating networks, C2C
Marketplaces, B2B Marketplaces, Website development, Website design, Software
programming, Developer tools, Security, Growth tools, Business Intelligence,
Invoicing, Spreadsheeting, Recruiting, Jobs boards, Art, Video games, Metaverse,
Music distribution, Influencer networks, Product design, Teaching, Learning,
Homework, Tutoring, Translating, Community management, Brand management,
Customer loyalty, Lead generation, Pharmaceuticals, NFTs, Astrology, Fitness &
Exercise, Watching TV.

Applications of Generative Tech



--------------------------------------------------------------------------------

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AI MODEL BUSINESSES

If you are Founders who build AI and ML models, go through the same list above
and see if you can create the AI model for that specific area. If you have
access to unique data, if you’re the first to see an application area, you can
get a leg up by having the best model for a time in a specific area.

That advantage may not last and more general models might eat into your data
advantage, or competitors selling an inferior – but still useful – model more
cheaply, as has happened to the general models already in the last two years.
Remember, data network effects are typically asymptotic. If you can make them
real-time or hyper local, they are more durable.
Mental Models
Another way to land on a great Generative Tech idea is to think about how that
business might work operationally.

    
 1. How can it have network effects where every new user adds value to every
    other user?
    
 2. How can it embed itself in a business or someone’s life so they don’t want
    to stop using it in the long run? This is Jasper’s job in 2023 to figure
    out.
    
 3. Where are there hyper local data sets for your AI model that you can own and
    maintain your data network effects despite competition coming in later?
    
 4. Where can you plug in to existing workflows, or a browser, or an app?
    


WHAT FUNCTION DOES THE APPLICATION SERVE?

Three quick functions that are clearly working today. There will be more over
time.


1. INITIAL IDEAS COLLABORATOR

This helps solve the zero-to-one problem. These companies generate rough drafts
or completed projects, and incorporate traditional SaaS tools to help perfect
those drafts. Over time, we expect these companies to move toward creating
finished products, but moving from zero to one is the first big step.

Tailorbird’s floor plan generation engine is a good example. It creates the
first draft of a remodel. So are companies that generate ad copy or first drafts
of code based on plain language inputs: companies like Copy.ai or Copysmith.

A company like jasper.ai, shows us how this path eventually leads to zero-to-ten
solutions. Jasper.ai provides specialized writing and image capabilities across
disciplines (copy, email, social etc). It’s a one-stop shop for your firm’s
writing needs in all formats. They are now in the process of trying to embed
that in a company so they can’t take it out, like an enterprise SaaS company
does.

These products get the ball rolling on complex tasks, and let humans take it
from there.




2. COACHING/TAILORED FEEDBACK

We learn through a process of trial and error. But we learn faster with a coach.
We expect Generative Tech to analyze our performance, generate advice, or
incorporate tools that allow us to hone our craft. Many of these applications
might make some people feel uncomfortable at first. But they will challenge us
to grow with the help of an AI collaborator. This is going to be the new normal.


3. UNIQUENESS AT SCALE

Uniqueness and scalability have historically been incompatible concepts. Truly
unique things can’t exist en masse without losing their bespoke qualities.
Generative Tech changes this. The generative engine is capable of providing a
new output for every new user or every problem, at scale.

NFX-backed The.com allows you to generate hundreds of new websites all within
one spreadsheet. These aren’t cookie cutter copies, they’re beautifully
designed, and unique to the needs of each user.

An example from the biology world is Insilico Medicine. Insilico Medicine
employs three AI-powered products that work together. One identifies new targets
for drugs, while another generates new candidate molecules from scratch.
Finally, the last engine predicts the outcome of clinical trials based on
previous work. This is an elegant example of an analytical AI approach
(identifying targets, and analyzing trial outcomes) combined with Generative
Tech (generating novel molecular structures).

It’s similar to how snowflakes are generated in nature – millions fall during
every storm, each totally unlike the one before it. But imagine that each one of
those snowflakes could generate revenue for a business, cure a disease, or spark
delight.


FOUNDER ADVICE


GENERATIVE TECH WILL HAVE UNUSUAL MARKET DYNAMICS BECAUSE IT’S ALREADY CONSENSUS

Typically, major tech shifts roll out slowly. Many people were still skeptical
of the Internet until 2003, so those of us who believed had less competition.
SaaS was gaining consensus from 1997 to 2005. Apple didn’t open their iOS
platform to outside developers for 18 months after launch. Web3 has been rolling
out for 10 years.

But everyone is on board with Generative Tech. The VCs get it. The Founders get
it. The incumbents get it. And it’s clear that the game is now on.

What that means for Founders is 1) you have to move very, very fast. Boldness
will matter. 2) You have to pick your idea very carefully. What you decide to
build, who your target customer is, and what your distribution channels will
matter a lot. There are patterns for what ideas work. You can go after a
horizontal or a vertical, a particular data type or geography. There are many
choices in the Generative Tech sector today.

As an example, there were 50+ social networks with the same 5 features when
Facebook launched. Social networking was already “consensus.” But FB started
with college students at Harvard and that turned out to be the right place to
focus. You will have to make a similar focused choice in this consensus market.


HOW TO BE FAST GROWING AND DEFENSIBLE IN GENERATIVE TECH

If you’re building a Generative Tech business for enterprises, to grow fast, be
prepared to be a plug-in to existing systems. Don’t try to replace workflows or
replace existing software systems. To be defensible, embed in customers’
existing workflows and software. You’re seeing Jasper announce they want to be
the browser plugin that gives all knowledge workers access to all the underlying
AI models of text, images, etc. They won’t take it all, of course, but their
plugin approach is correct on both counts: easy to implement and embedding in
workflows.

Another good enterprise example is Tabnine, which mimics GitHub’s CoPilot code
generator. It doesn’t replace the programmers’ code editor, it just sits on top
for fast growth. What Tabnine did for defensibility is to build hyper-local data
network effects for each company it serves around their exact code base, which
locks those customers into Tabnine. Combining the embedding of the workflow with
a protectable data moat is a good combination for durability.

If you’re building B2C, it’s more open-ended. Consumers love novelty, and are
willing to adopt new behaviors faster. Just make sure to move fast and get a
network effect.

If you are building for SMBs, it’s likely going to be in between something brand
new and something that plugs in.


SPEED BUMPS

In Generative Tech, there are still questions of issues of copyright and safety,
and I know first hand how real those are. Further, Founders should be concerned
with NOT making weapons of mass social destruction. Further still, as Founders
of an important company, you need to be a steward of society and not just your
shareholders.

But great Founders step into the risks and solve the challenges quickly. Don’t
let those concerns slow you down. Better to be thoughtful and good and also
early on the field – to be the one figuring it out – rather than left behind,
wringing your hands with a furrowed brow on the sidelines.


FOUNDER CHALLENGES

The biggest business risk at this stage of the market cycle (early) is that
Founders don’t move fast enough into the seams opening in the market, and these
technologies will simply become features and augmentations of the larger
companies’ businesses. If you are Figma or SalesForce, you are scrambling to add
such features ASAP. If you are SnapChat, same. Etc.

As a Founder, you need to pick your lane very carefully. As we discussed above.
You want to find the fast moving water.


WHAT DO GREAT GENERATIVE TECH FOUNDERS LOOK LIKE?

They look like you. This area is so new, and moving so fast, you can have an
advantage in your chosen area in a few months… for now.

It’s Oct 2022. This window will close in months. Find your area, find your seam
– either technical, distribution, customer focus, geography focus, etc and hit
it hard. Then give NFX a call for your seed capital. We invest $1-$4M, and we
can help.

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