Could you build an amazing company, with $1 billion?
by A M Howcroft, SWARM CEO
It feels like EVERYBODY is talking about OpenAI and ChatGPT, even your great aunt will want to discuss it with you at the next family BBQ. Having spent some time using the tool, I would agree that it’s very impressive and completely understand why Microsoft are planning on investing $10 billion in the company. As the CEO of an AI software startup, I truly admire what OpenAI have achieved in building and training a large language model that can generate (mostly) high quality human-like text. Many journalists and pundits are saying that while the current version is impressive, ChatGPT 4.0 will be revolutionary, and is rumoured to be released this year. We are exploring the pro edition to extend our platform. I would like to point out one critical aspect of ChatGPT, though, and I will let the system tell you in its own words:
“What many people may not realize is that the development of ChatGPT was made possible by a significant investment of $1 billion. This funding allowed OpenAI to assemble a team of top researchers and engineers, as well as to invest in the necessary hardware and infrastructure to train such a large model.
This raises the question: could other software companies achieve similarly revolutionary advancements with a similar level of investment? The answer is yes.”
Not to toot our own horn, but we have some revolutionary technology at SWARM, that can transform the way organizations and individuals define and solve problems. You can try it for free on our website. The investment to reach this stage has been approximately $8 million, or 125 times less than OpenAI. I’m excited by what we have achieved on that budget and would love to do more. Without doubt, there are many exciting startups in a similar position to us, with ground-breaking technology that could transform industries and lives, which have received from $0 to $50M in funding so far. Why is the scale of funding so critical? Well, let’s ask ChatGPT again:
“Investment in research and development is crucial for any company looking to push the boundaries of technology. With sufficient funding, a company can assemble a top-notch team of experts, invest in state-of-the-art equipment and infrastructure, and conduct the necessary research to develop innovative new products.
In today's fast-paced technology landscape, staying competitive means constantly pushing the boundaries of what is possible. Companies that are able to secure large investments and put them towards research and development will have a significant advantage in the race to create the next big thing.”
I couldn’t agree more - money matters. A lot. One of my primary roles as a CEO is to raise money for my company, so ultimately the founders of OpenAI did a better job in attracting investors than I did - so far ;) If you are wondering how they did that, here’s the ChatGPT answer:
“OpenAI was able to raise $1 billion in funding through a combination of venture capital and private investment. The company was founded in 2015 by a group of high-profile individuals including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever and Wojciech Zaremba. Their involvement helped to attract the attention of venture capital firms and other investors, many of whom were interested in the company's ambitious goals of advancing artificial intelligence in a safe and responsible manner.”
I did wonder how much of this came from the personal wealth of the individuals, so I asked:
“The original founders of OpenAI, including Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, Wojciech Zaremba, and John Schulman, invested a total of $1 billion in the company. This funding came from their personal funds and was used to support the development of the organization's research and technology.”
I see a slight conflict with the previous answer, in that this second paragraph suggests most of the money came from their own pockets and less from venture capital. Anyhow, it’s great if you are a wealthy individual already, but most CEOs are not in that position. Fund-raising is a time-consuming and competitive task, with many firms seeking capital from a limited number of venture sources. This is even more challenging in the current market, which is precariously balanced. The venture firms have raised more capital than ever before but are jittery about market conditions. This is resulting in lower market valuations for companies looking to acquire capital, although on the flipside that’s a major opportunity for venture firms to snap up bargains. Crowd wisdom suggests that good companies will always secure funding, but most venture capitalists will be highly selective in making new investments, preferring to hold back funds to support their existing portfolio. For startups, revenue will become more important than vision, as everyone looks to batten down the hatches and make it through the turbulent economic weather ahead.
SWARM is lucky to be well-funded, with strong and supportive investors. We believe there are break-out opportunities in a recession, and many of the companies we speak with have significant economic headwinds and need to make big savings on operational costs. With our unique approach to rapidly defining and solving operational challenges using AI, this looks like a major opportunity for our customers and ourselves. I can’t help but think, though, how much more we could do with a $1 billion investment! Let’s put some context here. We have three products in our suite:
SWARM Challenge Modeler: Easily define a problem in business language, with templates built by industry experts, or simply build your own Challenge Definition – then share with others
SWARM Solution Engine: Run advanced AI, ML and Operational Research algorithm solutions from sources such as Google, Microsoft, and Gurobi to solve your Challenge Definition
SWARM Operator Dashboard: Manage operational challenges on a day-to-day basis, by interacting with SaaS solutions built in the Solution Engine, for significant time and cost savings.
Once our customer has created a Challenge Definition, there is still some work to be done to collect and clean the data and build a pipeline. There is also some data science effort to match the challenge to a suitable algorithm in the Solution Engine, to test the algo, and fit the model. The Operator Dashboard is generated automatically from the meta-data, but we may add a few customer specific BI reports. Overall, the services required to implement a solution is minimal, perhaps 4-6 weeks elapsed time with 1-2 people. That’s a significant improvement over traditional approaches, but the potential is so much bigger.
The vision: a business user should be able to describe any challenge, in a few hours, and see a working solution instantly – with quantified savings.
That is with no direct data science or IT work required. That may sound like a pipedream, but the steps involved are already described and largely mapped out. It just takes more time and development effort, and therefore money, to achieve. We aren’t replacing the Data Science or IT people either, it is just that their work becomes reusable elements that can be deployed automatically.
Today, solving problems is both an art and a science, requiring specialists, time, and far too often interdepartmental politics that must be overcome, before a solution is deployed. Imagine instead, if solving challenges was as simple as talking to a chatbot. We believe that is the future, and it is coming. How quickly we get there depends on the size of the investment into solutions like SWARM, and other advanced AI technologies. If Elon and his friends are listening and want to solve real-world problems and not simply generate human-like reports, we’re ready to talk. Sorry, what was that ChatGPT?
“Of course, it's not just about the amount of investment, but also about the use of the funds and the vision of the company. OpenAI's success in creating ChatGPT is a testament to the power of significant investment in cutting-edge technology, and serves as a model for other companies looking to make a mark in the tech industry.”
Agreed. We have a vision, and an experienced management team, that believe AI can deliver amazing results in many facets of life. Isn’t it time we started using that power to solve big problems, and make lives better? SWARM optimizes challenges in the agri-food supply chain. We help customers reduce food waste, increase yield, lower transportation costs and carbon outputs to support regenerative-ag. The potential benefits to everyone from accelerating these solutions are enormous. Of course, with more capital, we could tackle additional markets. Healthcare? Water? Space exploration? They all have challenges that need solving, the sooner the better.
So who wants to invest? Even a paltry $200 million could make a difference. We are ready.