Artificial intelligence systems integration
Part of a series on |
Artificial intelligence |
---|
The core idea of artificial intelligence systems integration is making individual
Most
Integration focus
The focus on systems' integration, especially with regard to modular approaches, derive from the fact that most intelligences of significant scales are composed of a multitude of processes and/or utilize multi-modal input and output. For example, a humanoid-type of intelligence would preferably have to be able to talk using speech synthesis, hear using speech recognition, understand using a logical (or some other undefined) mechanism, and so forth. In order to produce artificially intelligent software of broader intelligence, integration of these modalities is necessary.
Challenges and solutions
Collaboration is an integral part of
The outcome of this in A.I. is a large set of "solution islands": A.I. research has produced numerous isolated software components and mechanisms that deal with various parts of intelligence separately. To take some examples:
- Speech synthesis
- FreeTTS from CMU
- Speech recognition
- Sphinx from CMU
- Logical reasoning
- OpenCycorp
- MIT
- Open
With the increased popularity of the free software movement, a lot of the software being created, including A.I. systems, is available for public exploit. The next natural step is to merge these individual software components into coherent, intelligent systems of a broader nature. As a multitude of components (that often serve the same purpose) have already been created by the community, the most accessible way of integration is giving each of these components an easy way to communicate with each other. By doing so, each component by itself becomes a module, which can then be tried in various settings and configurations of larger architectures. Some challenging and limitations of using A.I. software is the uncontrolled fatal errors. For example, serious and fatal errors have been discovered in very precise fields such as human oncology, as in an article published in the journal Oral Oncology Reports entitled “When AI goes wrong: Fatal errors in oncological research reviewing assistance".[1] The article pointed out a grave error in artificial intelligence based on GBT in the field of biophysics.
Many online communities for A.I. developers exist where tutorials, examples, and forums aim at helping both beginners and experts build intelligent systems. However, few communities have succeeded in making a certain standard, or a code of conduct popular to allow the large collection of miscellaneous systems to be integrated with any ease.
Methodologies
Constructionist design methodology
The
Examples
- ASIMO, Honda's humanoid robot, and QRIO, Sony's version of a humanoid robot.
- Cog, M.I.T. humanoid robot project under the direction of Rodney Brooks.
- AIBO, Sony's robot dog, integrates vision, hearing and motorskills.
- TOPIO, TOSY's humanoid robot can play ping-pong with human
See also
- symbolic AI & that of Computational intelligence.
- Neurosymbolic AI
- Humanoid robots utilize systems integration intensely.
- Constructionist design methodology
- Cognitive architectures
References
- ISSN 2772-9060.
Notes
- Constructionist Design Methodology, published in A.I. magazine
- MissionEngine: Multi-system integration using Python in the Tactical Language Project