An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of a dataset for machine learning by an AI entity. Datasets can be very expensive to purchase, as, depending on both the proper selection of the elements and the homogeneity of the data contained within, constructing and maintaining the integrity of a dataset is difficult. Blockchain as a highly secure storage medium presents a technological quantum leap in maintaining data integrity. Furthermore, blockchain’s immutability constructs a fruitful environment for creating high quality, permanent and growing datasets for deep learning. The combination of AI and blockchain could impact fields like Internet of things (IoT), identity, financial markets, civil governance, smart cities, small communities, supply chains, personalized medicine and other fields, and thereby deliver benefits to many people.

Classical double entry accounting has provided the foundation for accounting within the firm for many centuries. The digitally signed receipt, an innovation from financial cryptography, gives rise to exactly duplicated entries for each of 3 parties or roles, the outcome of which we call triple entry accounting. This presents a challenge to double entry bookkeeping by expanding the use of accounting from inside firms to activity between the firms. When applied to digital cash and digital assets, the approach of negotiating a single signed receipt between parties lowers costs by delivering reliable data to support stronger accounting, and makes much stronger governance possible in a way that positively impacts on the future needs of corporate and public accounting. By turning the opinions of firm owners into facts agreed between firms, triple entry bookkeeping creates the bulletproof accounting layer to support aggressive uses and adversarial users such as are found in the Bitcoin system of transactions.

Most Artificial Intelligence (AI) implementations so far are based on the exploration of how the human brain is designed. Nevertheless, while significant progress is shown on specialized tasks, creating an Artificial General Intelligence (AGI) remains elusive. This manuscript proposes that instead of asking how the brain is constructed, the main question should be how it was evolved. Since neurons can be understood as intelligent agents, intelligence can be thought of as a construct of multiple agents working and evolving together as a society, within a long-term memory and evolution context. More concretely, we suggest placing Multiple Neighborhood Cellular Automata (MNCA) on a blockchain with an interaction protocol and incentives to create an AGI. Given that such a model could become a “strong” AI, we present the conjecture that this infrastructure is possible to simulate the properties of cognition as an emergent phenomenon.