IBM reveals five life-changing innovations [watch videos]

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Artificial Intelligence, Brain, Machine Learning, AI

IBM has shown off five innovations including superhero vision, medical labs on a chip, and smart sensors for pollution detection that it says have the potential of changing our lives in just five years.

The “IBM 5 in 5” list was released a few days back by the technology giant with this year’s overarching theme being “making the invisible visible”. IBM has said that artificial intelligence (AI), hyperimaging, macroscopes, chip technology, and smart sensors have the potential of bringing about a revolution in almost all walks of life and could impact human lives in a massive way in just five years.

The “IBM 5 in 5” is based on market and societal trends as well as emerging technologies from IBM’s Research labs around the world that can make these transformations possible. IBM says:

  • AI will enable us to tackle mental health issues;
  • Hyperimaging combined with AI will give humans superhero vision;
  • Macroscopes will help us understand Earth’s complexity in infinite detail;
  • Medical labs “on a chip” will serve as health detectives for tracing disease at the nanoscale; and
  • Smart sensors will detect environmental pollution at the speed of light

AI and Mental Health

Mental health issues including diseases of the brain, developmental psychiatric and neurodegenerative diseases, and others are increasingly affecting people around the world and these issues not only increase human suffering but also impact us economically.

Depression, bipolar disease or schizophrenia, are some of the most common forms of mental diseases in the US as well as other countries around the world and as there are no definitive treatments for these conditions, health systems of countries around the world are reeling under pressure of huge costs.

IBM says that brain is a black box that we don’t fully understand, but speech is a key to unlock what’s inside the brain. In just five years, what we say and write will be used as indicators of our mental health and physical wellbeing, IBM says. Patterns in our speech and writing analyzed by new cognitive systems will provide tell-tale signs of early-stage developmental disorders, mental illness and degenerative neurological diseases that can help doctors and patients better predict, monitor and track these conditions.

At IBM, scientists are using transcripts and audio inputs from psychiatric interviews, coupled with machine learning techniques, to find patterns in speech to help clinicians accurately predict and monitor psychosis, schizophrenia, mania and depression. Today, it only takes about 300 words to help clinicians predict the probability of psychosis in a user.

Hyperimaging, AI and superhero vision

Humans can’t see a lot of things – almost 99.9 per cent of the electromagnetic spectrum – with their naked eye and while we have advanced tremendously in terms of building instrument that helps us see things at different wavelengths, there’s not much advancement in the portability front.

IBM says that in just five years, new imaging devices using hyperimaging technology and AI will help us see broadly beyond the domain of visible light by combining multiple bands of the electromagnetic spectrum to reveal valuable insights or potential dangers that would otherwise be unknown or hidden from view. Most importantly, these devices will be portable, affordable and accessible, so superhero vision can be part of our everyday experiences.

IBM scientists are today building a compact hyperimaging platform that “sees” across separate portions of the electromagnetic spectrum in one platform to potentially enable a host of practical and affordable devices and applications.

Such capabilities could help a car see through fog or rain, detect hazardous and hard-to-see road conditions such as black ice, or tell us if there is some object up ahead and its distance and size. Cognitive computing technologies will reason about this data and recognize what might be a tipped over garbage can versus a deer crossing the road, or a pot hole that could result in a flat tire.

Understanding Earth’s complexity in infinite detail

Science has helped us unravel a number of ecosystems and their interconnections and though we understand a lot about Earth today than what we knew a couple of centuries ago, there’s a lot left that we do not understand. Earth’s complexity can be dubbed infinite. Data collection and analysis helps us understand this complexity, but IBM points out while we collect exabytes of data, most of it is unorganized. In fact, an estimated 80 per cent of a data scientist’s time is spent scrubbing data instead of analyzing and understanding what that data is trying to tell us.

In five years, we will use machine learning algorithms and software to help us organize the information about the physical world to help bring the vast and complex data gathered by billions of devices within the range of our vision and understanding. We call this a “macroscope” – but unlike the microscope to see the very small, or the telescope that can see far away, it is a system of software and algorithms to bring all of Earth’s complex data together to analyze it for meaning.

Medical Labs will reside on chips

How to tackle disease? The first thing is that we need to detect whether a person is suffering from a particular disease. Tests are crucial part of this detection process and one of the worst issues if we take into consideration some of the most remote places in the world. Even places that aren’t remote lack labs that could perform the required tests of saliva, tears, blood, urine and sweat.

Existing scientific techniques face challenges for capturing and analyzing these bioparticles, which are thousands of times smaller than the diameter of a strand of human hair.

In the next five years, new medical labs “on a chip” will serve as nanotechnology health detectives – tracing invisible clues in our bodily fluids and letting us know immediately if we have reason to see a doctor. The goal is to shrink down to a single silicon chip all of the processes necessary to analyze a disease that would normally be carried out in a full-scale biochemistry lab.

At IBM Research, scientists are developing lab-on-a-chip nanotechnology that can separate and isolate bioparticles down to 20 nanometers in diameter, a scale that gives access to DNA, viruses, and exosomes. These particles could be analyzed to potentially reveal the presence of disease even before we have symptoms.

Smart Sensors & Environmental Pollution

Most pollutants are invisible to the human eye, until their effects make them impossible to ignore. Methane, for example, is the primary component of natural gas, commonly considered a clean energy source. But if methane leaks into the air before being used, it can warm the Earth’s atmosphere. Methane is estimated to be the second largest contributor to global warming after carbon dioxide (CO2).

In five years, new, affordable sensing technologies deployed near natural gas extraction wells, around storage facilities, and along distribution pipelines will enable the industry to pinpoint invisible leaks in real-time. Networks of IoT sensors wirelessly connected to the cloud will provide continuous monitoring of the vast natural gas infrastructure, allowing leaks to be found in a matter of minutes instead of weeks, reducing pollution and waste and the likelihood of catastrophic events.

Scientists at IBM are tackling this vision, working with natural gas producers such as Southwestern Energy to explore the development of an intelligent methane monitoring system and as part of the ARPA-E Methane Observation Networks with Innovative Technology to Obtain Reductions (MONITOR) program.

At the heart of IBM’s research is silicon photonics, an evolving technology that transfers data by light, allowing computing literally at the speed of light. These chips could be embedded in a network of sensors on the ground or within infrastructure, or even fly on autonomous drones; generating insights that, when combined with real-time wind data, satellite data, and other historical sources, can be used to build complex environmental models to detect the origin and quantity of pollutants as they occur.

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