- Startup Rabbithole
- Here’s how to win the AI-Data Revolution
Here’s how to win the AI-Data Revolution
The AI-Data Era is Here.
As we have seen so far, all of the top LLMs have started building outwards. They are building out integrations and plugins that will allow them to expand their the reach to the entire internet. LLMs will impact a multitude of industries and functional areas. They are becoming more powerful day by day.
The AI-Data relationship will be the strongest force in technology in the coming decades. We can call this the AI Automation Ecoystem, which is revolutionizing every company’s relationship with data and AI.
The future of work will be disrupted by this framework.
Every company, startup or enterprise, needs to know what is happening here. Let us dive into how the AI-Data Era will impact every company’s strategy moving forward.
Product and business strategy will change forever. Here’s what’s new. 👇
Data is King — why data is more powerful than AI 🚀
Data will empower non-AI companies to be just as valuable as AI companies in the AI-Data Era. Why? ⬇️
LLMs are trained on data. Bard, ChatGPT, and other models are trained on private data that their creators have access to — as well as public data that they can find.
The reason why Google was able to make a big splash and show that Bard is just as capable as ChatGPT is because of data.
Companies with access to private data will be the winners of the AI-Data Era. Private datasets need to be built and grown over time. Thousands, if not millions, of users or events need to happen in order for a data set to truly be valuable.
This is why BloombergGPT is such a important model to come out. It is trained on Bloomberg’s private financial datasets. The competitive advantage that Bloomberg has over other companies is its financial data that it has harvested and grown over decades.
Many companies, just like Bloomberg, will be able to create their own moats solely by building unique and diverse datasets.
AI Models are only as good as the datasets they have access to 🧠
As mentioned before, models need to be trained on data. Why are AI models dependent on data? ⬇️
AI models will 100% revolutionize the future of work.
However, for most startups and emerging companies, you need to focus on your data first. Find the right problem to solve for, solve it well, and build the best solution out there.
The best solution will get you the best data over time. Typically, once you have found product-market fit or product-market fit at scale, you will have a great dataset.
Building and investing into developing AI models need to be built in conjunction with great data.
Yes, there will be several cases where specific AI models and applications will have long-term implications. These AI models will truly revolutionize how things are done. The future of work will be defined not only by how startups build their own AI models but also by how they continue growing their private datasets.
For most companies: data comes first, AI comes second. Every company will need to work with AI, but not every company needs to become an AI company immediately.
Every company needs to become a data company first, and then slowly over time, as they build their datasets, they can continue to experiment and move towards AI. Again, this is all highly dependent on the niche that your company is in and what the company is focused on.
Startups need focus on developing private datasets ASAP🦄
Private datasets are the key to success for emerging companies. The competitive moat that startups can build over time is building a private dataset.
This comes through solving a challenging problem and providing a unique solution. How do you “win” in AI? ⬇️
️There is no clear answer right now. Everything is changing by the moment.
But there is one constant: great solutions to challenging problems will always win. Build a startup as you normally would, experiment with AI, and grow your datasets over time.
Yes, you may also be building an AI startup — you may find an existing private dataset that works for you, or the product you build is what will give you a great dataset. It is important to remember that great startups that will be built in the 2020s and 2030s may also not be solely focused on AI.
Outside of Generative AI, there will be so many startups solving challenging and exciting problems. There will be great startups in climate change, agriculture, energy, healthcare, and many more areas.
The startups that are not explicitly “AI” startups will also win. Those who innovate on top of LLMs such as Bard, ChatGPT, LLaMa, and more will all also be very successful. If you build a great extension to AI models, you will be part of a great AI Automation Ecosystem.
The plugins that extend the reach of these LLMs will win as a result of network effects. Some of the greatest upcoming startups may well end up being the ones that gather the most unique and useful data.
The AI Model Battle is not over yet: we don’t know who will win 🤔
If you are following the news, you may know one thing — there is something new in AI coming out every week. But who is “winning” in AI? ⬇️
You can say OpenAI, Google, Microsoft, Meta, and many others are winning in AI.
Consumers are also winning in AI because it is revolutionizing a lot of processes that streamline and make things easier for them.
The Open LLM Leaderboard will give you the latest on who has the best models that have been released.
Note: this will slowly change week by week and significantly month by month, as well as over the next year.
How do you and your business “win” in AI?🎁
First, you need to keep experimenting with all of these tools and stay up to date with everything that happens. Especially if you are in an industry that will be impacted by AI, you need to be aware. How else can you “win” though? ⬇️
The most important problems you need to solve, however, are those your customers have. Solve those problems well by building seamless solutions.
AI will eventually help you with that, but for now, your business needs to figure it out.
If you want to “win” in AI, your data is everything. Not only that, how you use data will determine who succeeds and who does not.
In order to win in AI, you do not need to be an AI company. You need build datasets or find datasets first.
You also need to build a great business: solve problems well, focus on growth, aim for profitability, and have slow compounding progress over many years.
Once you do that, through AI or not, you will be a successful company.
Focus on the basics, move fast, and experiment with innovation. If you do these, you will be a great business.