Mindmap Unified cognitive profile

Rakesh Paul (U13161) Rakesh.Paul@ust-global.com

Abstract Current Artificial Intelligence applications utilizes data generated by users to build generalized machine learning models. However, each human brain is unique and has matured over the years through experience. This uniqueness is not captured by most of the models. Further these models are confined to companies that builds them. But we need a single endpoint that captures different user interaction and build a cognitive profile from those events. Mindmap attempts to address this problem. Mindmap can be extended not just to humans but to any smart device. This means that we have a cognitive space encompassing man and machine.

Advantages of Mindmap

1. Every human and device can have a unique Mindmap profile.

2. Mindmap API will enable devices and applications to send events pertaining to a device and human or between devices. These events get processed and stored in a structured way to build and enhance cognitive profile of both the user and the device.

3. The will allow devices to identify, recollect, share and make more natural interactions with humans and other devices

Introduction The latest buzz word in the town is AI (Artificial Intelligence). Companies are investing heavily in building AI infrastructures and capabilities to become more efficient. Further, latest Machine Learning techniques like deep learning requires specific hardware to build efficient systems. The key fuel that is driving AI now is the huge amount of data being generated via different mediums. To build efficient artificially intelligent system requires huge volumes of data and right hardware systems. Small to medium size services and product companies may find it difficult to invest heavily on AI like some other products companies do.

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However, these small to medium scale companies possess a more valuable entity that can accelerate building AI systems, their employees. Mindmap is an attempt to build AI systems leveraging the capabilities of man and machines owned by companies. Mindmap, focuses on crowdsourcing building blocks of AI systems. Mindmap concepts can be extended to other business domains.

Components

1. Cognitive Profiles

Every machine and human that makes up the Mindmap cognitive space, has profile. For a hardware device, cognitive profile stores information like the hardware specifications, operating systems etc. Humans can define what needs to be there in their cognitive profiles. The could provide information regarding the area of interests, their expertise, the role and tasks they are interested to handle etc. These properties will be utilized to distribute tasks and responsibilities when Mindmap is in the execution mode.

2. Master Algorithms

Master algorithms are application services that focuses on a single problem. They query the cognitive space to identify right profiles that can carry out its execution. Let us consider preprocessing, a critical step for any machine learning problem. Master algorithms are implemented using code pipelines implemented as micro services where each service feed the next one in the pipeline. A very common preprocessing step for textual analysis is stopword (word like the, a, they, then…) removal. For the

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preprocessing problem, the master algorithm contains micro services to connect to data sources like databases, twitter streams, Facebook timelines etc, services to split these data into chunks and send it to appropriate devices, services to pass the response back to systems that further processes these data to build machine learning models.

3. Intelligent Agents

Intelligent agents are application programs that enables humans and machines to perform certain cognitive tasks. The tasks may be either directed by the master algorithms or feedback events generated by humans. A sample feedback event might be a user sharing a technical article he just read. Events can carry information like owner, intent, audience etc.

Recently Mozilla released a Web API specification called Flyweb for enabling web pages to publish local-area servers. This specification aims to bring the web's client/server application model to inter-device communication. The web's application architecture enables an application running on a server to dynamically and incrementally send application state and logic to an intermittently connected client. With FlyWeb, both web clients and servers may advertise themselves for local-area consumption over local-area transport protocols such as Bluetooth, Wi-Fi Direct or over a wired/wireless LAN. Clients may discover and connect to servers and vice-versa, servers may discover and connect to locally available web clients. Techniques like Flyweb will enable the master algorithms to identify, distribute and coordinate tasks with agents and vice versa.

Use cases Crowdsourcing

Crowdsourcing is an efficient way to distribute tasks. Crowdsourcing could be used to prepare labeled dataset for supervised learning systems, generate test cases from requirement specifications etc. Let us consider the test case generation problem. Following steps will be to achieve the results.

a. Identifying the right cognitive profiles: This includes selecting the right candidates from the cognitive space, in this case employees who perform testing tasks within the organization. Selection criteria like, domain expertise, experience, test methodologies to filter the possible candidates to participate in the crowdsourcing activity.

b. Setting up the master algorithm: The involves defining the service pipelines to execute the task. This includes defining the micro services like gathering business requirements, sending these requirements to the selected cognitive profiles and processing the responses provided by the agents to generate the final reports. The business requirements gather process may collect the business specifications, split them into smaller

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chunks. Then another micro service will distribute it to testers. The whole idea is to split each problem into smaller independent tasks and distribute it to appropriate agents for processing.

c. Agents: Agents are the ones who goes on and execute the tasks. They are notified about tasks and provided with a window to respond to the tasks.

Implementation Thoughts JSON (JavaScript Object Notation) is a lightweight data-interchange format that could be used to specify input and output data for the micro services. Specification like JMESPath could be used to extract and transform elements from a JSON document to enable communication between micro services. Utilizing JMESPath one could interconnect services to build services pipelines which will act as the master algorithms.

Concepts like Serverless Architectures could be used to build and manage micro services used to define the master algorithms. Flyweb could be used for establishing a web session between two computational endpoints where one endpoint serves as a web client and the other as a web server.

Conclusion

Mindmap outlines a thought process to build cognitive services utilizing the resources available within an organization. Enabling proper cooperation between human and machines will enable organizations to build truly intelligent systems. It is not known right now whether machines could exceed human intelligence. However, machines can provide true intelligence if they work in sync with humans. Mindmap try to achieve this harmony between human and machines.

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Mindmap Infographics