This is James Currier, General Partner at NFAX as investors and builders were optimistic about the future of AI. One experiment among many we've done is we've trained AI avatars of our own voices to read out the essays we write. So this is my real voice you're hearing, but This is now my AI voice. I've been created by NFX to provide essay readouts moving forward as you'll hear. I am still a pale imitation of the real James Currier, but I'll get better over time.
And if you have suggestions for me, please let us know. This week's article is called generative tech begins and was first released in October of 2023 as our first essay focused on the subject of generative AI. Let's get started. Generative tech is the next step in software. It's a new level of human machine partnership Pete turns deep learning engines into collaborators to generate new content and ideas nearly like a human would.
We now have high quality, cheap, fast AI models for generating text images, videos, software code, music, voice, 3 d models, and more, none of which is copyrighted and is not plagiarized. Some have called it generative AI. But AI is only half of the equation. AI models for 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, NFX started investing in the space 2 years ago and has invested in 18 generative tech companies so far with more to come 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. If you are an investor or an angel who is focused on this new area, had to signal and change your profile so you show up on the list of generative tech investors.
So what's new about generative tech? Embry Wants, a new internet topology until today. The internet has been characterized by making database queries to get stored piece of old content from the center out to you on the edge of the network. Generative tech changes the topology of the internet because now unique pieces of content are generated edge of the network in real time by your action.
That's a major shift, which typically opens up founder opportunities if web 1 was read only and web 2 is read right. And then generative tech is read write generate then that makes web 3 read write generate on. Generative tech is now happening in parallel to web 3 and moving faster. As crypto hadn't happened, we'd probably be calling this web 3, but we do have crypto. So we call this generative tech, but other names could be web 3a generative Beller even generative internet.
Number 2, human activities will now change quickly. 1 to 2,000,000,000 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 tens of millions of workers in the next 36 months, the expansion of people's abilities, productivity, and efficiency will vastly outstrip the losses overall generating trillions of dollars of value for knowledge workers and creatives. Going from 0 to 1 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 0 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 0 to something useful, but these new generative tools help you with the first half of the process taking you from nearly 0 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 0 to one problem because it worked for us. Generative tech will work with us from the beginning of any projects today.
And for the next few years, this will feel surprising and in many ways, scary because those creative moments where you go from 0 to initial ideas has always felt so uniquely human because it has been so mysterious. The idea is once thought to come unpredictably only through people's minds and souls emerging from talent or training Morgan associated with special people will now be generated by something which is not a human not a coworker or collaborator dot dot dot and something that is not you.
This will be disturbing the 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 rocket ship for the human mind. The makers of these AI models might say they are actual minds. No doubt they will get this.
We've been talking about the inevitability of software based mind since the 50 seconds. A first example of the dawn of this era we felt as a culture was in 1997 when IBM's deep blue beat Casperavances. The neck big leap was when alphago definitively beat Lee settle on the game of Go and Treda 16, 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.
So what changed so that generative tech is happening now? The recent availability of open source alternatives to proprietary generative AI models from OpenAI is what caused it to tip wide open in the last six months. In short, Aluther dot i's Pete Neo X 20B. Launched in February 2022 is the open source alternative to open i's GPT 3 for text generation. Stability eye stable diffusion. Launched August 2022 is the open source alternative to open eyes Dolly 2 for images and videos.
Both have been game changers on price, quality, and ease of access. The cost to generate images has dropped 100 x in the last two months. The friction to generate output from these models through web and mobile has become about 10 x easier in the last 6 months. Quality generated text. Images, code, speech, etcetera 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 application, has moved to a sufficiently high standard that humans have a hard time telling the difference between synthetic and non synthetic pewdas. We are headed toward generative everything, because of all these changes. The amount of experimentation has grown 20 times larger in the last 2 months.
This accelerates applications providing value and introduces even more people to the community. It's an old story in technology. The barriers go down and boom. Morgan 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 Pete. 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, 3 d video, certainly. By the time you have your team together and seed money raised, it will be there. Don't overthink it. 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. 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 rocket ship already. In the fast moving water, I would pause what you're doing and consider focusing on this.
We've already invested in 18 generative AI companies over the last 2 years. And we are aiming to make more investments in the next 12 months when a new sector opens up like this. Founders can typically find low hanging fruit more easily than in areas that are better under in this more competitive. So get in there. Here's what we suggest to founders in order to start a new company to do new things and create new markets.
Start new companies that redo old businesses with this technology at the core, not just as a feature, add generative tech features to your existing product to differentiate it. Characteristics of generative tech products. Generative tech products have 2 layers. The bottom layer is an AI model that is capable generating novel output based on inputs that are unique to the user, like Openized DALL E or GPT 3, to make generalized versions of these can take 100 of millions.
To make more narrow versions can be less than 10,000,000 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 Dolly 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. Tierra 3, memory lines 0 to 1 and 0 to 10. Generative tech begins with solving a 0 to 1 problem. The most successful companies will eventually provide 0 to 10 solutions or put differently products that serve the complete needs of the user. 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 Sol, a choose your own adventure, 70 seconds inspired sci fi film, uses a combination of generative tech tools to rapidly generate videos.
Write scripts, and generate character voices. Number 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, ecommerce providers. Netflix and Spotify, I'll wanna serve you curated products you're most likely to like from their central databases. Facebook, TikTok, and the New York James 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 ask for it or triggered it through some other action or simply by your presence. This is happening in the music space boomy, Amper, sound draw, and others are a company using AI to generate full length, original songs, and seconds. Boomi also gives creators the tools to share and monetize those creations. An example of a generative tech layered with SaaS tools.
Critically, boonies 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, etcetera. Number 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 second life where 2 characters enter a house together.
The house could generate something entirely new that 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 1 or more base layer AI models with AI model businesses? If you are founders who build AI and ML models, Go through the same list about 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 Pete 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 2 years. Remember, data network effects are typically asymptotic. If she can make them real time or hyper local, they are more durable.
Metro Netals, another way to land on a great generative tech IDs to think about how that business might work operationally. How can it have network effects where every new user adds value to every other user? How can it embed itself in a business or someone's life? So they don't wanna stop using it in the long run.
This is Jasper's job in 2023 to figure out where there are hyper local data sets for your AI model that you can own and maintain your data network effects despite competition coming in later. Where can you plug into existing workflows or a browser or an app? What function does the application serve 3 quick functions that are clearly working today? There will be more over time. Number 1's initial ideas collaborator is Beller solve the 0 to 1 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 0 to 1 is the first big step. Beller bird's 4 plan generation engine is a good example. It creates the first draft of a remodel. So are companies that generate a copy or first drafts of code based on plain language Pete. Companies like Copy.ai or Copismith.
A company like Jasper dot ai shows us how this path eventually leads to 0 to 10 solutions Jasper dot ai provides specialized writing and image capabilities across disciplines. It's a one stop shop for your firm's writing needs in all 4 minutes. 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.
Number 2, coaching and 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.
Number 3, uniqueness at scale, uniqueness and scalability have historically been incompatible concepts. Truly unique things can exist on mass 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. N fxbackthe.com allows you to generate 100 of new websites all within one spreadsheet. These are cookie cutter copies.
They're beautifully designed and unique to the needs of each user. An example from the biology world is in silicone medicine. In silicone medicine employs 3 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 combined with generative tech 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 delay. 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 in 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. Webb 3 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 you have to move very, very fast.
Believe this we matter. 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 plus social networks with the same five features when Facebook launched.
Social networking was already consensus, but Facebook 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 and generative tech. If you're building a generative tech business for enterprises, to grow fast, be prepared to be a plug into existing systems. Don't try to replace workflows or replace existing software systems. To be defensible.
In bedding customers existing workflows and software, you're seeing Jasper announced they want to be the browser plugin that gives all knowledge workers access to all the underlying AI models text, images, etcetera, they won't take it all, of course, but their plug in approach is correct on both counts, easy to implement, and embedding in workflows. Another good enterprise example is tab 9, which mimics GitHub Copilot code generator. It doesn't replace the programmer's code editor.
It just sits on top for fast growth. What Tab 9 did for defensibility is to build hyper local data network effects for each company that serves around their exact code base, which locks those customers into Tab 9. 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 SMB. Likely going to be in between something brand new and something that plugs in, speed bumps, regenerative tech. There are still questions of issues of copyright and safety, and I know firsthand how real those Currier. Founders should be concerned with not making weapons of mass social destruction Currier 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 furred brow on the sidelines, founder challenges, the biggest business risk at this stage of the market cycle is that founders don't move fast enough into the seams opening in the Morgan, and these technologies will simply become features and augmentations of the larger company's businesses. If you are Figma or Salesforce, you are scrambling to add such features as a Pete.
If you are Snapchat, James, etcetera 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 October of 2022. This window will close in months, not years.
Flint your area, find your scene, either technical, distribution, customer focus, geography focus, etcetera, and hit it hard, then give NFX a call for your seed capital. We invest 1 to $4,000,000, and we can help. Thanks for listening to this week's essay readout of generative tech begins. As a reminder, this is still an AI imitation of James Currier speaking. We are having fun experimenting with new tools but would love to hear your feedback. Email us at qed@nfx.com.
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