Ideas of AI pricing/business models
The AI become to a hot topic nowadays, and not only for scientists or for visionaries. More and more industries are started to look to a AI direction and thinking how they can use this new technology for their business.
But what kind of business models we will see in near future, let’s do some looking into a crystal ball.
Infrastructure for AI
AI (Artificial Intellect) and ANN (Artificial Neuron Network) is very resource consuming. So therefore it is understandable that the main need at the moment is right hardware. Existing AI approaches requires a lot of small floating point calculations. It was a little bit surprise for me, but if we look deeper it’s make sense, the most demanding (from resource point of view) are computer graphic who also use floating point calculation to create VR (Virtual Reality).
That’s why the biggest name in game now start to change their position in market. NVIDIA are not only the biggest player in GPU (Graphics processing unit) market, but also build hardware solutions for AI. Even now lot of AI enthusiast use NVIDIA graphics cards to make AI calculation, and i read a topic where author purpose to change NVIDIA slogan from “The Way It’s Meant to be Played” to “the AI computing company”.
So there is a place and requirements for hardware to run AI in data centers or organization private cloud solution. I believe this model will be quite similar to existing models in Data center and hardware market.
Neurons network — price per neuron
Capability of AI mostly lands on size of neuron network. So, the most basic model will provide untrained neurons network, which can be trained and adjusted for specific purpose. This business model is quite similar to IaaS (Infrastructure as a Service) or PaaS (Platform as a Service).
I see two main models:
- package of inner connected neurons — block
- on demand neurons network
Both models provide pricing per neuron. Package model will be invoiced in advance, On demand model provide postpaid.
Client receive API to neuron network according to agreement (like AWS — Amazon Web Service), and there can be added additional conditions (for example: calculation limitation, type of neurons (RNN (Recurrent neurons network) of LSTM (Long Short Term Memory networks)), etc). I can imagine, that for native mobile apps or cars there can be not only Cloud AI services, but also a libraries for using AI autonomously.
Pretrained neuron networks — price per “skill”
This model provide AI to customer with specific skill — for example image recognition. With this basic pretrained skills, customer can apply AI into their process. Benefit of this model is that customer receive some external skill. As a part of process this skill can be improved or adjusted according customer needs by the environment input and feedbacks (for example: AI can recognize persons — we can provide the feedback which persons are unwanted, and instruct AI to issue alerts if such person is recognized).
As a skill trade — you pay per skill and how god this skill is. Lower level skills as a basic object recognition will be cheaper that a face or speech recognition.
Trained neuron network — price per “competency”
Pack of pretrained skills to complete complex tasks. This AI can perform in a much complex environment. The first characteristics we can see in Facebook Chat Bots. In the beginning you get bot with basic skills (text recognition, context awareness) and you can train this bot to perform for example product advertiser or basic support provider.
Price per “rolle”
Pack of competencies to perform role — good example is IBM Watson Office assistant. This kind of AI can replace some of existing roles in organization — and is quit easy to calculate price comparing price for AI vs existing human expenses.
And this will continue, there is lot of activities to find a better way how to perform different tasks. For example: Smacc working on accounting solution. The biggest business names predicting, that in a time of 10 years they will hire a AI as a board member.
This is a scariest moment for lot a people, but do we really have a reason to be scared? In the beginning of the previous century the main shift happen. The invention of washing machine freed lot of women’s time. This shake labor market, because this flooded marked with fresh working hands. More and more women become educated and take a job where in the past been limited to men. In a very short period of time mankind figured out how to employ all. So the main lesson is that the people are very creative creatures and human will figured out how to employ themselves (or others). Some of these role I described below.
Performance based price
This one can be a very interesting marketing/PR opportunity for AI companies. The main idea is similar to existing hiring process. If you are hiring junior, who can perform only a simple tasks, the starting salary will be small. And the similarity continue — the Junior earn some knowledge about Your processes, and become more capable to do more you lift up salary.
So the main idea is — pay by achieved results. This allow companies to pay less when the AI is learning, and pay more, when AI can complete much complex tasks (become an expert or senior specialist).
AI powered services
We already see such services, especially in infrastructure environment. Most of largest IaaS providers using AI to manage their infrastructure and balance usage of it according client’s needs. Another service, wildly used, google translation. Just five weeks ago Google announced major breakthrough in their translation service, and significant improvements in translation using AI.
AI identified algorithms
The power of AI is recognize patterns. The weakness of AI is resource consumption. The highly possible is a scenario, where in the beginning the AI is operate, to identify possible patterns, and later, if the environment does not change a lot, we use reverse engineering to create simple algorithms which can operate effectively enough. This allow us to understand new environment (finding patterns), and if we find the winning algorithm, we can reproduce it cheaper.
This sort of AI already exist — self driving cars use it. Moving forward and shrinking the size of AI devices (or AI capability) we will see lot of that kind of hardware. In CES 2017, the biggest keynote where from Nvidia. And for AI the Nvidia announced a cooperation with Audi and show the “brains” for next generation self driving Audi. The size of this device impressed me — laptop size device, who can analyse surrounding environment and take proper decision.
So it is natural to expect continuous shrinking of AI hardware and this small AI devices will appear in a various daily used equipment.
Hardware for AI
AI by itself are like brain without a body. As a living being we have lot of sensors — eye, ears, nose, hands. All of this “devices” feed our brain with information for analysis and decision-making. The situation with AI is absolutely identical — we need to provide AI with information.
Excellent example of AI powered machine is Boston Dynamic prochect. To achieve that level of flexibility in dynamic environment they use lot of sensors, analyse incoming signals with AI and execute required action. The existing existing interaction between man and machine is lame — we need more flexible solution to provide AI with information and receive data from it — the neuron connection can be a solution, and when we find a way how to iterate in that level, we will see a gigantic jump in technology and possibilities.
As the AI will become more and more popular and widely used there will be a rise of related services. Lets look to some of them.
We can see such services already. If you see the benefit of using pertained neuron networks instead of ANN who works on data flow and identify patterns, you need to train ANN. You can do it for yourself (or a specialist in your organization) or you can order a service who will train your AI to act in accordance with your wishes.
This is not so simple task actually. To train someone you need three things:
- understanding of the process
- test data
So, this can be a really good business in near future, and the biggest players will be those who have a lot of data which can be used to learn.
Those who have not seen serial WesterLand — I recommend. if we are heading to human like AI, the behavior becomes as the most significant characteristic. Like in the beginning of Internet, all of the sites where similar. But not for long, the role of Web Designers arise. And the customers get required individuality in theirs net representation.
Quite interesting possibility in a world full of human like AI. And the main reason, why this role will appear is bad habits. We can look into not so distance past — first chatbots in Facebook. Based on content in a short period of time they become racist. Of curse, organization cannot act that way, and if AI perform an essential role, cannot switch it off. So — we need some sort of doctor for AI, who can analyze AI and “cure” it.
We live in an exciting time, dynamic and full of possibility's. I wish everyone to enjoy it and not be afraid of it. And like a young kid keep your eyes wildly open to see all of this miracles around us.