Before blockchains came to the fore, the favorite technology of the business world was artificial intelligence. Thanks to the deep artificial neural networks that became popular in the 2010s, models such as object recognition, translation, speech-to-text, and text-to-speech produced satisfactory results.
The success of deep neural networks has resulted in machine learning models dominating the field of artificial intelligence. Artificial intelligence is now primarily a combination of handwritten code by programmers and machine learning models. Therefore, I will use the terms artificial intelligence and machine learning interchangeably in this article.
Artificial Intelligence(AI) In The Web2 Era
Big technology companies have won enthusiasts' admiration by implementing machine learning models in the 2010s. For example, Facebook was able to recognize and tag faces in pictures and present content that users might be interested in.
Google was the undisputed star of that period in AI. Since its main area of activity was related to data and algorithms, it actively used artificial intelligence in all its services. For example, a developed machine learning model overcame Gmail's spam e-mail problem. The speech-to-text models used made it possible to write by speaking. An even more important development was that the google translate service reached a satisfactory level in the mid-2010s. On the other hand, the navigation service provided through Google Maps eliminated the trouble of finding a way.
Web2 companies didn't just use AI to improve their various services. Targeted advertisements powered by machine learning models were the basis of the Web2 business model. Users were also satisfied with the digital services they received for free.
AI and Blockchains
In 2017, I was working on AI when blockchains started occupying the business world's agenda. In finance, similar to the technology sector, the main application area of machine learning models was marketing. We used machine learning models to recommend products to customers that might interest them. Machine learning was also used for credit scoring, fraud detection, and algorithmic trading.
While waiting for the next revolution to come from artificial intelligence, blockchains suddenly appeared. Could it be possible to use blockchains together with artificial intelligence? In 2018, there were two blockchain projects for this purpose in the crypto market: Singularity.net and Deepbrainchain.
Singularity.net is positioned as a marketplace for artificial intelligence models. This initiative has a mission to help create Artificial General Intelligence, which has a human-level cognitive ability.
Deepbrainchain, on the other hand, set out to be a marketplace to provide the processing power required for deep AI networks. It has accomplished its mission in the past four years, but it is impossible to say that the project's coin has performed well.
AI Use Cases of Web3 Era
Over the years, we had a better understanding of blockchains. We now know that blockchains solve the problem of trust in the digital environment. Concerns about data security and the competitive advantage of owning customer data preceded collaboration in artificial intelligence in the Web2 era. However, when the data is anonymized and made public, benefits may arise that those who own it cannot even imagine.
Today, only technology companies that have become a monopoly benefit from user data. However, thanks to blockchain technology, individuals can become the owner of their data. They can have opportunities such as preventing the use of their data or sharing the income obtained from their data.
Creating artificial intelligence models such as object recognition and translation has ceased to be a task that even medium-sized companies, let alone individuals, can handle. Processing a mountain of data through devices with very powerful GPUs is necessary to produce a successful model. Blockchain networks can aggregate the data and processing power required for such models. Each primary model can be represented by a token, enabling stakeholders to generate revenue.
In recent years, sounds, images, and texts produced through generative models have started to occupy the agenda of technology enthusiasts. People, music, items, and landscapes made through generative models can be traded in NFT format. Around a particular school of generative art, artists may collaborate to create a fictional universe.
The main models of the data produced in the crypto world will be related to trading. Trading bots will begin to use the information they learn from the data as well as handwritten commands. People interested in algorithmic trading can collaborate by organizing around a particular token.
Characters controlled by computers in computer games can be seen as early examples of AI agents. Using such characters in play-to-earn games will increase the attractiveness of the games.
Conclusion
We can access crypto projects on artificial intelligence through Coingecko, Coinmarketcap, and Messari. In a separate article, I will review the projects I have chosen among the projects labeled as artificial intelligence in all three sources.
AI has enormous economic potential. Unlocking this potential requires broad participation and cooperation. Crypto networks can help unlock that potential on a well-established financial foundation.
Thank you for reading.
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