Responsible Machines is developing an AI platform that is modeled around how the brain processes information. This automation platform is designed to enable robots to learn, speak, make decisions and exhibit general intelligence.


Autonomous Learning Machine

In order to create ‘Strong AI’, we need to look no further than the cognitive processes of the human brain. We will see that processes involving anticipation, prediction, reasoning and abstraction are merely a combination of processes; and these can be mimicked by the machine, in order to behave just like a human. However, today’s […]

Handling Visual Parameters

The post articulates how Visual Learning works at a high level within the RM2 Platform. The Visual learning feature in RM2 is integrated into the unified architecture where visual object detection and learning are integrated to achieve real-time detection and behavior prediction in a given environment. In order to accurately detect objects and learn from […]

Embedding Language Processing

Introduction The post provides an overview of how the RM2 Network employs unsupervised learning to process Natural Language using reference visual inputs along with the object label, just as humans do. We believe that in order to deliver effective machine-human communication, we need to integrate visual cues with language that will provide the ability to learn, […]


Digital Immortality

This is in continuation with the digital immortality post published here. Summarizing the previous post, we stated that “it might be possible to achieve longevity, irrespective of the target machine we chose to live in, provided that we learn how to extract data holistically from the source machine (brain) and develop a package to restore […]

How far is AI from being intelligent like humans?

Although there has been good progress in AI development, a fundamentally different approach may be necessary to achieve true artificial general intelligence (AGI). This is apparent, given that current approaches do not take the best advantage of data organization (the logical model) and instead rely on heuristic techniques when attempting to make machines behave like […]

Self Learning Avatars

In early computing,  an avatar was a graphical representation of the user or the user’s alter ego or character. Examples were an icon or figure representing a particular person in a video game, Internet forum, etc. Now within the scope of AI, Avatars can be looked at as virtual embodiment of humans, which are driven […]

Minimalism (computing)

In computing, the term minimalism refers to the application of minimalist philosophies and principles in the design and use of hardware and software. Minimalism, in this sense, means designing systems that use the least hardware and software resources possible. You could compare this with the functioning of the human brain, which exhibits intelligence using the least […]

Machine Reasoning and Abstraction

To begin, we recommend watching a brilliant video produced by DARPA (below), which cuts through all of the AI hype clutter to clearly articulate how demonstrated machine intelligence has evolved along with its shortfalls. In summarizing AI capabilities, we may observe that perception and learning capabilities matured during the second wave of development. The hard reasoning that […]

Unsupervised Learning With Minimalism

A demonstration of Unsupervised AI might be when a robot can think and act responsibly within a given environment, akin to what humans would typically do. In order for machines to replicate human intelligence they require two critical elements, as do humans; time and data. A human exhibits intelligence by first collecting/absorbing data over a period […]

Providing Robots with Declarative Memories formed by a combination of Semantic and Episodic Memories