IBM reveals five innovations that will help change our lives within five years

IBM unveiled the annual “IBM 5 in 5” (#ibm5in5) – a list of ground-breaking scientific innovations with the potential to change the way people work, live, and interact during the next five years.

 “The scientific community has a wonderful tradition of creating instruments to help us see the world in entirely new ways. For example, the microscope helped us see objects too small for the naked eye and the thermometer helped us understand temperature of the Earth and human body,” said Dario Gil, vice president of science & solutions at IBM Research. “With advances in artificial intelligence and nanotechnology, we aim to invent a new generation of scientific instruments that will make the complex invisible systems in our world today visible over the next five years.”

Innovation in this area could enable us to dramatically improve farming, enhance energy efficiency, spot harmful pollution before it’s too late, and prevent premature physical and mental health decline as examples. IBM’s global team of scientists and researchers is steadily bringing these inventions from the realm of our labs to the real world.

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. Here are the five scientific instruments that will make the invisible visible in the next 5 years:

With AI, our words will open a window into our mental health

If the brain is a black box that we don’t fully understand, then speech is a key to unlock it. In five years, what we say and write will be used as indicators of our mental health and physical wellbeing.

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.²

Hyperimaging and AI will give us superhero vision

In 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.

Macroscopes will help us understand Earth’s complexity in infinite detail

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.

By aggregating, organizing and analyzing data on climate, soil conditions, water levels and their relationship to irrigation practices, for example, a new generation of farmers will have insights that help them determine the right crop choices, where to plant them and how to produce optimal yields while conserving precious water supplies.

In 2012, IBM Research began investigating this concept at Gallo Winery, integrating irrigation, soil and weather data with satellite images and other sensor data to predict the specific irrigation needed to produce an optimal grape yield and quality. In the future, macroscope technologies will help us scale this concept to anywhere in the world.

Medical labs “on a chip” will serve as health detectives for tracing disease at the nanoscale

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 will detect environmental pollution at the speed of light

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.