This article comes from MIT’s Tech Review and is startling in its implications for what is next in not just computing, but in driving the Singularity Forecast. Will we witness an era where AI rivals human intelligence or even surpasses it?
Perhaps a different form of AI, different form of consciousness from human beings, a synthetic form of intelligence I would maintain, has already emerged.
I wrote about this in my article When the Network Wakes Up. In it, I posed the notion that perhaps the Singularity has already started and we did not notice because we are so human-centric in looking for consciousness and intelligence that is biological, or computational in form, when there is a new A-Life model that is emerging, a mash-up of silicon and biology. Read on.
Artificial intelligence investigators have built a fully silicon scale simulation of the human brain. The artificial neurons operate faster than the organic model, are built to learn and adapt.
The Fast Analog Computing with Emergent Transient States project takes a different approach to other electronic intellect endeavors. Research like the Blue Brain project, run vast software simulations of virtual brains, which allows them to tinker with the conditions and wiring of the brain with the tap of a keyboard. On the downside, you’re running a layer of simulation of a parallel system on top of an utterly sequential computer system, which slows things down.
The FACETS hardware instead builds direct silicon similes of synapses and neural circuits, creating a real hardware brain which can operate in parallel just like the human mind. Sure, it’s more of an American Idol mind at the moment, with only two hundred thousand neurons compared to a hundred billion in your head (a factor of five hundred thousand).
But the FACETS architecture is scalable, and the team already has plans for a billion-synapse super chip – for those of you updating your “end of the human race” calendars, that’s a fifty-thousand-fold increase in one generation. And we all know that computers don’t have new generations more than once or twice a year.
FACETS Artificial Brain
Dr. James Canton’s Response to the White Paper for the National Human Genome Research Institute
From the National Human Genome Research Institute
Developments in DNA sequencing technologies over the past two decades have been a critically important driver of breath-taking advances in our understanding of broad areas of biology and biomedicine, ranging from human disease to microbial ecology, to evolution. During this time, and especially in the past few years, sequencing costs have decreased faster than Moore’s Law and sequencing capacity has increased at an ever-greater pace.
These advances have enabled the landmark accomplishments of genomics – the determination of the genome sequences of the major model organisms used in biomedical research (bacteria, yeast, roundworms, fruit flies and mice) and, ultimately, that of humans.
Building on those fundamental data sets, DNA sequencing has been applied on a large scale to learn more about human variation (e.g., HapMap and 1000 Genomes), the functional composition of genomes (e.g., ENCODE and modENCODE), and the genetic basis of many human diseases and other traits.
In the past few years, a new generation of DNA sequencing platforms based on fundamentally different methodologies has collectively become a ‘disruptive technology’ that will create a new set of research opportunities for the coming decade. The availability of these so-called ‘next-gen’ sequencing technologies (and the already emerging ‘third-generation’ technologies that will closely follow) raises many questions for the research community. NHGRI has identified a number of questions that are pertinent to the future of DNA sequencing and of genomics.
Dr. James Canton’s Response
These are the right questions regarding the future of genome sequencing. There are a number of key convergence drivers impacting genomic sequencing also to consider, such as the future of personalized medicine, consumer genomic informatics, nano-biology and synthetic biology, all should be factored in as well to this strategic planning process.
How and why we collect, manage and mine the data from sequencing is the real value of this effort. We need to explore new ways to leverage off of social networking and research collaborations that will encourage process innovations from beyond the large institutions; we need to inspire a highly innovative era of Sequencing 2.0.
We should consider what the future of the Post-Genomic Society looks like on the other side of the next ten years and then work backwards to consider strategic planning, funding and policy to shape a desired future. If not, we run the risk of genomic developments happening faster then we can anticipate, plan for and control. Too much control in the hands of the large institutions will be no worse then no control over a highly distributed open source model. We need the right balance of players–large and small, all focused on the same objectives.
There will be radical outcomes of an inexpensive, highly pervasive, distributed, genomic sequencing, information infrastructure that will and should, transform health care, medicine and influence human evolution. This impact will be beyond the disruptive innovations we see today, such as the development of a personal predictive health forecast. Society, medicine and policy makers in government are not ready for this extreme future that is coming fast.
Consumers will want to know their Predictive Health Future Outcome. The policy implications of this social, economic and scientific impact will be comprehensive–sequencing is just the first stage of this transformation in either consumer empowerment, or confusion.
The future impact of high scale inexpensive sequencing will likely create a new consumer awareness of the value of personal genomics. How long will I live? What diseases may I be at risk for? What can I do?
Also, the practice of medicine and health care delivery should change to be responsive to this innovation–from early genomic detection to wide distributed data-rich, real-time sequencing. Policies and funding to create new medical education and treatment models that will change the paradigm of health care should be researched now. Sequencing opens transparency, but an imperfect future of predictive and preventive health care in the short term. Managing expectations will be important from a policy perspective.
Future scenarios may be problematic and defeat consumer expectations if the control of genomic info via sequencing is not distributed and controlled with a scientifically sound and rationale plan, given this information today. It is likely that the link between genomic personal data and medicine, i.e. how disease can be prevented or disease treated, will continue to lag our capacity to turn genomic data into treatment.
At the same time, we should expect dramatic and consistent breakthroughs if we make available via a social networking model, access online to a larger collaborative community to pool data, share insights, create tools and conduct the large-scale knowledge management of the outcomes of sequencing the larger population.
The real value of sequencing to address human health issues from forming a National Genomic Sequencing Data Infrastructure project (beyond current efforts Hap Map etc.) to warehouse, mine and conduct research linking drug discovery, prevention, diet to individual health outcomes, is to actually prevent disease and promote health with personalized information. This should be pursued as the ultimate end game. This would be accelerated if a private and public partnership were to incentivize academics, research centers and private sector companies to collaborate beyond the efforts currently available.
Sequencing projects might focus on: Smaller scale projects to offer innovation grants to research the links to develop lifestyle, genomic and cardiovascular disease, early detection links with specific Cancer populations, evidence based medicine with nutra-genomics.
Funding agencies should encourage sequencing innovations towards enhancing human health, more innovative research into drug discovery and genomics, and the creation of centralized collection, and distribution of genomic data with the objective to better understand the much needed transformation of medicine and health care that must be addressed, if we are to enable healthy consumers.
In an era of the aging baby boomers, depopulation, reduced GDP, a multi-trillion dollar health care system, funding agencies must be on the vanguard to drive innovation, collaboration and discovery to direct the future of sequencing to become a viable cost-effective strategy for enhancing the health of Americans.