Next-gen computing for terabase transfer

The single biggest challenge presently facing humanity is the new era of ICT (information and communication technology) required to advance the progress of science and technology. This constitutes more of a grand challenge than do disease, poverty, climate change, etc. because solutions are not immediately clear, and are likely to be more technical than political in nature. The raw capacity in information processing and transfer is required and also the software to drive these processes at higher levels of abstraction to make the information useable and meaningful. The computing and communications industries have been focused on incremental Moore’s Law extensions rather than new paradigms and do not appear to be cognizant of the current needs of science, and particularly the magnitude.

Computational era of science
One trigger for a new ICT era is the shift in the way that science is conducted. The old trial and error lab experimentation has been supplemented with informatics and computational science for characterizing, modeling, simulating, predicting and designing. Life sciences is the most prominent area of science requiring ICT advances, for a variety of purposes including biological process characterization and simulation. Genomics is possibly the field with the most ICT urgency; genomic data is growing at 10x/year vs. Moore’s Law at 1.5x/year for example, however nearly every field of science has progressed to large data sets and computational models.

Alt approaches to AGI

50+ year old attempts at creating AGI have not been successful. It is possible that AGI cannot be generated from current methods and technologies; the wrong tool is being used, sort of like trying to build a 747 with a toothbrush. Electromagnetism, silicon and Von Neumann architectures may not ever have the capacity to achieve AGI even allowing for continued increases in processing, storage and memory and architectural shifts such as parallelism.

Other substrates might work
Getting around the rigidity of Von Neumann, mathematical, logic-based, computational approaches, symbolic approaches and traditional computers, other computational substrates like quantum computing, DNA computing, etc. might work and also those that humans have not yet invented, discovered or exploited for this purpose like light, air, memes and information. There must be other substrates, and other viable approaches that are not constrained by mathematics and logic.

Information as a substrate
Narrowly, the only existing example of general intelligence is the human brain and the basic requirements of AGI are self-replication and self-improvement. Considering self-replication, there are many examples of more effective self-replication than humans, for example, memes, disease and microbes. Considering self-improvement, memes also self-improve more effectively than humans as they are refined through repetition, and have the unbounded ceiling for improvement of true AGI.

Taking advantage of the self-reproducing and self-improving properties and using memes and information as a novel computing substrate might be one way of extending AGI progress.

Information as a substrate could be developed symbiotically with a very broadly applicable new understanding of the laws of physics based on information and entropy as opposed to mass and energy.

Massive info processing needed

Step function improvements in information processing and communications capabilities are needed now and in the future.

Massive amounts of data are becoming increasingly available and currently humanity only has narrowband access to these biomedical, genetic, astronomical, particle accelerator and other data sets.

Large and diverse data sets requiring storage, processing and upload/download will only continue to proliferate. For example, as the web goes 3-D, rapid video, audio and data download and upload are needed, as objects become IP tagged, sensor and RFID networks require instantaneous data collection and summarization.

Scientific philosophers such as Anders Sandberg correctly point to information processing capability as the main limit on any society's growth and development. To attain a new level and not just asymptote out on the current plateau, a re-envisioning of information processing is necessary.

As with energy, some alternatives are being explored at the fringes but there is no real replacement methodology on the horizon. Also as with energy, there may be a dearth of real progress until the present means is more substantially threatened, however this point is coming very soon in information processing as compared with energy.