Why build an AI platform on Blockchain?
To understand why Koios is building an AI ecosystem using blockchain it is important to understand the nature of the AI development industry in today’s market.
The talent pool for Artificial Intelligence, whilst increasing exponentially, is still a relatively small group of highly skilled data scientists, developers and mathematicians. These individuals are coveted in the tech industry and due to the lack of mainstream adoption and distribution channels for their work they have inevitably been monopolised by large technology firms.
The fundamental challenge, as viewed by our founder, is the lack of a medium for AI developers to learn, create, validate, monetize and distribute their creations to a global audience without an intermediary. The development cycle for Artificial
Intelligence requires specific toolsets, large datasets and significant amounts of computing power which is oftentimes difficult for both the budding and advanced developers to access outside the confines of large enterprise organisations,
research bodies and large tech firms.
This in turn led our Founder, Marcus Bowles, to reflect on the industry after speaking to numerous AI developers about the common challenges they experience when trying to create their own content. The key takeaways were:
● Development cycles are often too expensive for an individual to build viable AI models & constructs.
● The ability to monetize AI content to a global audience is difficult, or non-existent.
● Data sets required to build viable models are difficult to find and costly to obtain at scale.
● Repeatable environments in which to build, iterate and test are difficult to manage.
● The types of systems required for AI development are typically only found in research environments and large tech firms like Amazon, Google, Alibaba & Facebook.
Further research led to Koios choosing blockchain as a foundational technology for the entire platform.
Market
What is the opportunity?
All industries across the globe are seeking ways to streamline processes, enhance capability and automate repeatable tasks using artificial intelligence. To get an understanding of the magnitude of the opportunity, a subset of samples are listed:
● Predictive maintenance
● Energy efficiency
● Warranty reserve estimation
● Propensity to buy
● Demand forecasting
● Process optimization
● Telematics
Retail
● Predictive inventory planning
● Recommendation engines
● Upsell and cross-channel marketing
● Market segmentation and targeting
● Customer ROI and lifetime value
Health and Life Sciences
● Alerts and diagnostics from real-time patient data
● Disease identification and risk stratification
● Patient triage optimization
● Proactive health management
● Healthcare provider sentiment analysis
Travel and Hospitality
● Aircraft scheduling
● Dynamic pricing
● Social media Interaction
● Customer complaint resolution
● Traffic congestion
Financial Services
● Risk analytics and regulation
● Customer Segmentation
● Cross-selling and up-selling
● Sales and marketing campaign management
● Credit Evaluation
Energy and Utilities
● Power usage analytics
● Seismic data processing
● Carbon emissions and trading
● Customer-specific pricing
● Smart grid management
● Energy supply optimization
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