I wrote posts about IBM, HP. Apple, Facebook etc.
The most relevant posts related to Open AI are the posts about Google and Microsoft.
It is possible to compare the AI Revolution to two previous revolutions.
The first is the Industrial Revolution.
The second is the Internet.
Bubble
Comparing current AI market to the Internet of the beginning of this century may be useful.
I remember the dot-com bubble.
A Seed Venture Capital rejected my proposal to extend the Scalability and Robustness of Microsoft's Windows operating system.
The reason for rejecting it was "It is not pure Internet solution" i.e. it is applicable to Web Server but also applicable to internal Data Center systems.
Currently AI is the Hype stage of Gartner's Hype Cycle.
Probably, the current AI bubble is not very different from the dot-com bubble.
Organizations spend a lot of money on AI initiatives and products, but only few of them deploy AI solutions which provide Value justifying the expanses.
The sixth wave of AI
The book "The Shortest History of AI - The Six Essential Ideas that Animate it" was written by Toby Walsh.
According to the book, the previous five waves of AI fail to accomplish their promises.
Huge sum of money was spend without enough value provided.
For example, the wave of Expert Systems started in the eighties of the previous century.
A lot of money was spend and a temporary success was replaced by disappointment after discovering inherent limitations.
Leading expert systems companies such as Teknowledge, Intellicorp and Carnegie group are not traded anymore.
Will Open AI Survive until 2036?
Currently, there are many severe threats to Open AI.
The probability that it survive until 2036 is not high.
In the following paragraphs I dwell upon some of the major threats.
Threat 1: The Sixth Wave will fail
Five AI waves did not fulfil their promise. Nobody can be sure if the current wave's fate will be different.
Most of the Leading Vendors of previous waves are no more significant vendors.
Threat 2: Currently AI is in the Hype stage of Gartner hype cycle
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| Gartner hype Cycle. source: English Wikipedia |
- Created: 27 December 2007 by Jeremykemp at English Wikipedia
- CC BY-SA 3.0
The left side of the graph is Hype.
Leading Vendors during the Hype phase are not necessarily leaders After disillusionment.
Netscape Web browser was the dominant Web browser in the mid of the 1990s with 90% of the market but lost to Microsoft's Internet Explorer. In 2006 his market share was less than 1%.
Threat 3: Lack of Revenues
ChatGPT is a generative artificial intelligence chatbot.
Its dominance in the retail sector does not provide enough revenues.
The expanses are huge expanses: Data Centers, Electricity, expensive Nvidia Graphic Processors etc.
The revenues are far from justifying the expanses.
The Organizational Market is potentially significantly larger revenues source.
Unfortunately for Open AI, Anthropic Claude is leading that market.
Open AI attempts to create additional revenues sources include the following:
1. Advertisement
The results of Advertisement deployment would be gathering more personal information and using it for adapting the advertisement to users profiles.
Another result would be less natural interaction of the AI software and the user.
The third result would be enhanced Security threats.
2. Content for Adults
Content for Adults stands for paid Erotic discussions of a human being with a virtual entity created by the Chat Bot.
I doubt if these sources would provide sufficient revenues.
4. Competition
A large and a profitable vendor which earn a lot of money from other business lines.
Google Gemini 3.5 is a good product.
Google builds its own GPUs for internal use.
Google GPUs capabilities are almost similar to Nvidia's GPUS capabilities.
Using its own GPUS instead Nvidia's GPUs could reduce the expanses significantly.
Google is aiming at integrating its AI solutions with its popular platform and other products.
Anthropic
Anthropic is a leader in the Organizational market and the leader of code creating.
Nvidia
Nvidia is a monopoly of AI GPUs.
GPUs' prices are expensive. Data Centers of Generative AI products deployment consumes a large amount of GPUs.
Nvidia's revenues are enormous.
Jensen Huang NVidia's CEO said the company intends to provide full GEN AI solution including GPUs and Software.
Currently it is experimenting its GEN AI product based on Open Claw.
Nvidia could be a very strong competitor.
It is possible to compare Open AI to Netscape of the first browsers days and Nvidia or Google to Microsoft of that period.
5. Model Threats
The first phase of neural Networks was based on model called Perceptrons developed by Frank Rosenblatt.
The first Neural networks phase failed.
Marvin Minsky and Seymour Papert proved that Frank Rosenblatt's model includes inherent limitation and therefore is inadequate AI model.
Unfortunately, the current Generative AI model has serious inherent limitation.
This limitation causes Hallucinations i.e. answers unrelated to the question a human being asked.
The Chatbot do not understand what Human Being is asking. Instead of understanding it makes Probabilistic decision.
misunderstandings occurs and the result is Hallucinations.
The inherent limitation is similar to the inherent limitation of a Speller Correction Application.
The Speller Correction Application is simple.
The Gen AI Chatbots are more sophisticated.
The current Generative AI tools are based on training the product on large amount of data in order to reduce Hallucinations probability.
A new version of CharGPT is based on more data than the previous version.
The first versions used prepared training data.
Unfortunately, current versions use Internet data for training.
Data Quality is low.
There are people and organizations deliberately injecting contaminated Data, e.g. the Russian Government and the Iranian regime.
There are already startups trying to use other models which are not based on training data.
Among the startups there are startups created by Yann André Le Cun and Mira Murati.
If a better model will become Mainstream model then Open AI is at Risk of non-survival same as some of the Leaders of previous AI waves.
The Bottom Line
The probability that OpenAI will not be a significant player in AI on 2036 is high.
Any 10 years prediction could be wrong.
The longer the prediction time is the probability of correct prediction is smaller.
The probability that OpenAI will not be a significant player or even will not Survive in 2036is higher than the probability that 50% of the workers will lose their jobs until 2036.
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