Together, healthcare clinics have the ability to collaborate on improving patient diagnosis protocols and accuracy without having to share the underlying data. To get around these roadblocks, Fetch.AI combines two paradigm-shifting technologies: the immutable, secure and confidential nature of the blockchain and the company’s own pioneering machine learning protocol. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) Rules contain privacy, security, and breach notification requirements that apply to individually identifiable health information created, received, maintained, or transmitted by health care providers who engage in certain electronic transactions, health transactions, health plans, health care clearinghouses, and their business associates. Not only that, healthcare providers are governed by strict privacy laws. But the principal vulnerability is that the entire process occurs in isolated, centralized cocoons. Under a traditional protocol of medical care, a patient enters a hospital or clinical care facility to seek a diagnosis, which later guides further courses of action. Its technical paper explains:įetch creates a huge population of digital data analysts and sales agents who can work together, alone, or with human or corporate masters to reduce the cost of delivering complex solutions in our daily lives.Īnd this profound rethink of technology has delivered compelling use cases, particularly in healthcare. What makes Fetch.AI stand out is its unique innovation that replaces human actors with AEAs. While this sounds utterly fantastical, the blockchain’s inherently decentralized platform can integrate intelligence into several transactions of economic value, not just the exchange of money. Under a blockchain-based self-adaptive smart ledger ecosystem, Fetch.AI fosters an environment whereby AEAs can learn and perform functions as either representatives of human actors or acting on their own behalf. At the core of this groundbreaking technology is the autonomous economic agent, or AEA. As I alluded to above, these machines lack the economic incentive to do anything.Īnd that’s what makes Fetch.AI so remarkable. Yes, machines have the ability to “talk” to each other but require human input to do so. This is one of the biggest issues of innovations regarding the Internet of Things. Otherwise, the AI platform will just sit there. Second, and most obviously, a human operator must provide the initial input or the catalyst. In order for the program to truly “learn,” a human programmer must artificially expand the system and the ruling protocol.
First, the AI interface is limited to the pre-defined system. However, this mechanism has two glaring problems.
Should a particular matrix be expanded significantly, binary logic-based programs can be incredibly useful. Within a pre-defined system, “intelligent” programs will respond to various condition under an “if this, then that” protocol. Prior to the blockchain, several AI programs incorporated binary logic-based architectures. Leveraging the extraordinary power of the blockchain, Fetch.AI has finally uncovered the key to a truly legitimate artificial intelligence platform: incentive. However, these AI-based protocols have found themselves lacking due to requiring human management to be effective.īut a new venture called Fetch.AI (Crypto: FET) promises to shift this paradigm forever. Yes, we’re moving at a rapid clip, with multiple autonomous platforms promising operational integration between man and machine. Unfortunately, prior AI innovations have lacked the fundamental catalyst of true independence to be holistically practical. Utilizing the massive capabilities of advancing computerized technologies, it’s theoretically possible to replicate various human operations, resulting in greater economic efficiencies as well as safer oversights of expanding population centers. Since the dawn of the computer age, programmers and developers have long envisioned an era of artificial intelligence. Combining machine learning and the blockchain, Fetch.AI aims to deliver best-case health outcomes for medical patients
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