Zeeshan Mir Baz has collected the information from this website:https://www.weforum.org/agenda/2015/03/top-10-emerging-technologies-of-2015-2/ in this article
04 Mar 2015
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said that:

Technology is perhaps the greatest agent of change in the modern
world. While never without risk, technological breakthroughs promise
innovative solutions to the most pressing global challenges of our time.
From zero-emission cars fuelled by hydrogen to computer chips modelled
on the human brain, this year’s 10 emerging technologies offer a vivid
glimpse of the power of innovation to improve lives, transform
industries and safeguard our planet.
To compile this list, the World Economic Forum’s Meta-Council on
Emerging Technologies, a panel of 18 experts, draws on the collective
expertise of the Forum’s communities to identify the most important
recent technological trends. By doing so, the Meta-Council aims to raise
awareness of their potential and contribute to closing the gaps in
investment, regulation and public understanding that so often thwart
progress.
The 2015 list is:
1. Fuel cell vehicles
2. Next-generation robotics
3. Recyclable thermoset plastics
4. Precise genetic engineering techniques
5. Additive manufacturing
6. Emergent artificial intelligence
7. Distributed manufacturing
8. ‘Sense and avoid’ drones
9. Neuromorphic technology
10. Digital genome
1. Fuel cell vehicles
Zero-emission cars that run on hydrogen

“Fuel
cell” vehicles have been long promised, as they potentially offer
several major advantages over electric and hydrocarbon-powered vehicles.
However, the technology has only now begun to reach the stage where
automotive companies are planning to launch them for consumers. Initial
prices are likely to be in the range of $70,000, but should come down
significantly as volumes increase within the next couple of years.
Unlike batteries, which must be charged from an external source, fuel
cells generate electricity directly, using fuels such as hydrogen or
natural gas. In practice, fuel cells and batteries are combined, with
the fuel cell generating electricity and the batteries storing this
energy until demanded by the motors that drive the vehicle. Fuel cell
vehicles are therefore hybrids, and will likely also deploy regenerative
braking – a key capability for maximizing efficiency and range.
Unlike battery-powered electric vehicles, fuel cell vehicles behave
as any conventionally fuelled vehicle. With a long cruising range – up
to 650 km per tank (the fuel is usually compressed hydrogen gas) – a
hydrogen fuel refill only takes about three minutes. Hydrogen is
clean-burning, producing only water vapour as waste, so fuel cell
vehicles burning hydrogen will be zero-emission, an important factor
given the need to reduce air pollution.
There are a number of ways to produce hydrogen without generating
carbon emissions. Most obviously, renewable sources of electricity from
wind and solar sources can be used to electrolyse water – though the
overall energy efficiency of this process is likely to be quite low.
Hydrogen can also be split from water in high-temperature nuclear
reactors or generated from fossil fuels such as coal or natural gas,
with the resulting CO2 captured and sequestered rather than released
into the atmosphere.
As well as the production of cheap hydrogen on a large scale, a
significant challenge is the lack of a hydrogen distribution
infrastructure that would be needed to parallel and eventually replace
petrol and diesel filling stations. Long distance transport of hydrogen,
even in a compressed state, is not considered economically feasible
today. However, innovative hydrogen storage techniques, such as organic
liquid carriers that do not require high-pressure storage, will soon
lower the cost of long-distance transport and ease the risks associated
with gas storage and inadvertent release.
Mass-market fuel cell vehicles are an attractive prospect, because
they will offer the range and fuelling convenience of today’s diesel and
petrol-powered vehicles while providing the benefits of sustainability
in personal transportation. Achieving these benefits will, however,
require the reliable and economical production of hydrogen from entirely
low-carbon sources, and its distribution to a growing fleet of vehicles
(expected to number in the many millions within a decade).
2. Next-generation robotics
Rolling away from the production line

The popular imagination has long foreseen a world where robots take over all manner of everyday tasks.
This robotic future has stubbornly refused to materialize, however,
with robots still limited to factory assembly lines and other controlled
tasks. Although heavily used (in the automotive industry, for instance)
these robots are large and dangerous to human co-workers; they have to
be separated by safety cages.
Advances in robotics technology are making human-machine
collaboration an everyday reality. Better and cheaper sensors make a
robot more able to understand and respond to its environment. Robot
bodies are becoming more adaptive and flexible, with designers taking
inspiration from the extraordinary flexibility and dexterity of complex
biological structures, such as the human hand. And robots are becoming
more connected, benefiting from the cloud-computing revolution by being
able to access instructions and information remotely, rather than having
to be programmed as a fully autonomous unit.
The new age of robotics takes these machines away from the big
manufacturing assembly lines, and into a wide variety of tasks. Using
GPS technology, just like smartphones, robots are beginning to be used
in precision agriculture for weed control and harvesting. In Japan,
robots are being trialled in nursing roles: they help patients out of
bed and support stroke victims in regaining control of their limbs.
Smaller and more dextrous robots, such as Dexter Bot, Baxter and LBR
iiwa, are designed to be easily programmable and to handle manufacturing
tasks that are laborious or uncomfortable for human workers.
Indeed, robots are ideal for tasks that are too repetitive or
dangerous for humans to undertake, and can work 24 hours a day at a
lower cost than human workers. In reality, new-generation robotic
machines are likely to collaborate with humans rather than replace them.
Even considering advances in design and artificial intelligence, human
involvement and oversight will remain essential.
There remains the risk that robots may displace human workers from
jobs, although previous generations of automation have tended to lead to
higher productivity and growth with benefits throughout the economy.
Decades-old fears of networked robots running out of control may become
more salient with next generation robotics linked into the web – but
more likely familiarisation as people employ domestic robots to do
household chores will reduce fears rather than fan them. And new
research into social robots – that know how to collaborate and build
working alliances with humans – means that a future where robots and
humans work together, each to do what it does best – is a strong
likelihood. Nevertheless, however, the next generation of robotics poses
novel questions for fields from philosophy to anthropology about the
human relationship to machines.
3. Recyclable thermoset plastics
A new kind of plastic to cut landfill waste

Plastics are divided into thermoplastics and thermoset plastics. The
former can be heated and shaped many times, and are ubiquitous in the
modern world, comprising everything from children’s toys to lavatory
seats. Because they can be melted down and reshaped, thermoplastics are
generally recyclable. Thermoset plastics however can only be heated and
shaped once, after which molecular changes mean that they are “cured”,
retaining their shape and strength even when subject to intense heat and
pressure.
Due to this durability, thermoset plastics are a vital part of our
modern world, and are used in everything from mobile phones and circuit
boards to the aerospace industry. But the same characteristics that have
made them essential in modern manufacturing also make them impossible
to recycle. As a result, most thermoset polymers end up as landfill.
Given the ultimate objective of sustainability, there has long been a
pressing need for recyclability in thermoset plastics.
In 2014 critical advances were made in this area, with the publication of a landmark paper in the journal
Science
announcing the discovery of new classes of thermosetting polymers that
are recyclable. Called poly(hexahydrotriazine)s, or PHTs, these can be
dissolved in strong acid, breaking apart the polymer chains into
component monomers that can then be reassembled into new products. Like
traditional unrecyclable thermosets, these new structures are rigid,
resistant to heat and tough, with the same potential applications as
their unrecyclable forerunners.
Although no recycling is 100% efficient, this innovation – if widely
deployed – should speed up the move towards a circular economy with a
big reduction in landfill waste from plastics. We expect recyclable
thermoset polymers to replace unrecyclable thermosets within five years,
and to be ubiquitous in newly manufactured goods by 2025.
4. Precise genetic-engineering techniques
A breakthrough offers better crops with less controversy
Conventional genetic engineering has long caused controversy.
However, new techniques are emerging that allow us to directly “edit”
the genetic code of plants to make them, for example, more nutritious or
better able to cope with a changing climate.
Currently, the genetic engineering of crops relies on the bacterium
agrobacterium tumefaciens
to transfer desired DNA into the target genome. The technique is proven
and reliable, and despite widespread public fears, there is a consensus
in the scientific community that genetically modifying organisms using
this technique is no more risky than modifying them using conventional
breeding. However, while
agrobacterium is useful, more precise and varied genome-editing techniques have been developed in recent years.
These include ZFNs, TALENS and, more recently, the CRISPR-Cas9
system, which evolved in bacteria as a defence mechanism against
viruses. CRISPR-Cas9 system uses an RNA molecule to target DNA, cutting
to a known, user-selected sequence in the target genome. This can
disable an unwanted gene or modify it in a way that is functionally
indistinguishable from a natural mutation. Using “homologous
recombination”, CRISPR can also be used to insert new DNA sequences, or
even whole genes, into the genome in a precise way.
Another aspect of genetic engineering that appears poised for a major
advance is the use of RNA interference (RNAi) in crops. RNAi is
effective against viruses and fungal pathogens, and can also protect
plants against insect pests, reducing the need for chemical pesticides.
Viral genes have been used to protect papaya plants against the ringspot
virus, for example, with no sign of resistance evolving in over a
decade of use in Hawaii. RNAi may also benefit major staple-food crops,
protecting wheat against stem rust, rice against blast, potato against
blight and banana against fusarium wilt.
Many of these innovations will be particularly beneficial to smaller
farmers in developing countries. As such, genetic engineering may become
less controversial, as people recognize its effectiveness at boosting
the incomes and improving the diets of millions of people. In addition,
more precise genome editing may allay public fears, especially if the
resulting plant or animal is not considered transgenic because no
foreign genetic material is introduced.
Taken together, these techniques promise to advance agricultural
sustainability by reducing input use in multiple areas, from water and
land to fertilizer, while also helping crops to adapt to climate change.
5. Additive manufacturing
The future of making things, from printable organs to intelligent clothes

As
the name suggests, additive manufacturing is the opposite of
subtractive manufacturing. The latter is how manufacturing has
traditionally been done: starting with a larger piece of material (wood,
metal, stone, etc), layers are removed, or subtracted, to leave the
desired shape. Additive manufacturing instead starts with loose
material, either liquid or powder, and then builds it into a
three-dimensional shape using a digital template.
3D products can be highly customized to the end user, unlike
mass-produced manufactured goods. An example is the company Invisalign,
which uses computer imaging of customers’ teeth to make near-invisible
braces tailored to their mouths. Other medical applications are taking
3D printing in a more biological direction: by directly printing human
cells, it is now possible to create living tissues that may find
potential application in drug safety screening and, ultimately, tissue
repair and regeneration. An early example of this bioprinting is
Organovo’s printed liver-cell layers, which are aimed at drug testing,
and may eventually be used to create transplant organs. Bioprinting has
already been used to generate skin and bone, as well as heart and
vascular tissue, which offer huge potential in future personalized
medicine.
An important next stage in additive manufacturing would be the 3D
printing of integrated electronic components, such as circuit boards.
Nano-scale computer parts, like processors, are difficult to manufacture
this way because of the challenges of combining electronic components
with others made from multiple different materials. 4D printing now
promises to bring in a new generation of products that can alter
themselves in response to environmental changes, such as heat and
humidity. This could be useful in clothes or footwear, for example, as
well as in healthcare products, such as implants designed to change in
the human body.
Like distributed manufacturing, additive manufacturing is potentially
highly disruptive to conventional processes and supply chains. But it
remains a nascent technology today, with applications mainly in the
automotive, aerospace and medical sectors. Rapid growth is expected over
the next decade as more opportunities emerge and innovation in this
technology brings it closer to the mass market.
6. Emergent artificial intelligence
What happens when a computer can learn on the job?

Artificial
intelligence (AI) is, in simple terms, the science of doing by computer
the things that people can do. Over recent years, AI has advanced
significantly: most of us now use smartphones that can recognize human
speech, or have travelled through an airport immigration queue using
image-recognition technology. Self-driving cars and automated flying
drones are now in the testing stage before anticipated widespread use,
while for certain learning and memory tasks, machines now outperform
humans. Watson, an artificially intelligent computer system, beat the
best human candidates at the quiz game Jeopardy.
Artificial intelligence, in contrast to normal hardware and software,
enables a machine to perceive and respond to its changing environment.
Emergent AI takes this a step further, with progress arising from
machines that learn automatically by assimilating large volumes of
information. An example is NELL, the Never-Ending Language Learning
project from Carnegie Mellon University, a computer system that not only
reads facts by crawling through hundreds of millions of web pages, but
attempts to improve its reading and understanding competence in the
process in order to perform better in the future.
Like next-generation robotics, improved AI will lead to significant
productivity advances as machines take over – and even perform better –
at certain tasks than humans. There is substantial evidence that
self-driving cars will reduce collisions, and resulting deaths and
injuries, from road transport, as machines avoid human errors, lapses in
concentration and defects in sight, among other problems. Intelligent
machines, having faster access to a much larger store of information,
and able to respond without human emotional biases, might also perform
better than medical professionals in diagnosing diseases. The Watson
system is now being deployed in oncology to assist in diagnosis and
personalized, evidence-based treatment options for cancer patients.
Long the stuff of dystopian sci-fi nightmares, AI clearly comes with
risks – the most obvious being that super-intelligent machines might one
day overcome and enslave humans. This risk, while still decades away,
is taken increasingly seriously by experts, many of whom signed an
open letter coordinated by the Future of Life Institute
in January 2015 to direct the future of AI away from potential
pitfalls. More prosaically, economic changes prompted by intelligent
computers replacing human workers may exacerbate social inequalities and
threaten existing jobs. For example, automated drones may replace most
human delivery drivers, and self-driven short-hire vehicles could make
taxis increasingly redundant.
On the other hand, emergent AI may make attributes that are still
exclusively human – creativity, emotions, interpersonal relationships –
more clearly valued. As machines grow in human intelligence, this
technology will increasingly challenge our view of what it means to be
human, as well as the risks and benefits posed by the rapidly closing
gap between man and machine.
7. Distributed manufacturing
The factory of the future is online – and on your doorstep

Distributed
manufacturing turns on its head the way we make and distribute
products. In traditional manufacturing, raw materials are brought
together, assembled and fabricated in large centralized factories into
identical finished products that are then distributed to the customer.
In distributed manufacturing, the raw materials and methods of
fabrication are decentralized, and the final product is manufactured
very close to the final customer.
In essence, the idea of distributed manufacturing is to replace as
much of the material supply chain as possible with digital information.
To manufacture a chair, for example, rather than sourcing wood and
fabricating it into chairs in a central factory, digital plans for
cutting the parts of a chair can be distributed to local manufacturing
hubs using computerized cutting tools known as CNC routers. Parts can
then be assembled by the consumer or by local fabrication workshops that
can turn them into finished products. One company already using this
model is the US furniture company AtFAB.
Current uses of distributed manufacturing rely heavily on the DIY
“maker movement”, in which enthusiasts use their own local 3D printers
and make products out of local materials. There are elements of
open-source thinking here, in that consumers can customize products to
their own needs and preferences. Instead of being centrally driven, the
creative design element can be more crowdsourced; products may take on
an evolutionary character as more people get involved in visualizing and
producing them.
Distributed manufacturing is expected to enable a more efficient use
of resources, with less wasted capacity in centralized factories. It
also lowers the barriers to market entry by reducing the amount of
capital required to build the first prototypes and products.
Importantly, it should reduce the overall environmental impact of
manufacturing: digital information is shipped over the web rather than
physical products over roads or rails, or on ships; and raw materials
are sourced locally, further reducing the amount of energy required for
transportation.
If it becomes more widespread, distributed manufacturing will disrupt
traditional labour markets and the economics of traditional
manufacturing. It does pose risks: it may be more difficult to regulate
and control remotely manufactured medical devices, for example, while
products such as weapons may be illegal or dangerous. Not everything can
be made via distributed manufacturing, and traditional manufacturing
and supply chains will still have to be maintained for many of the most
important and complex consumer goods.
Distributed manufacturing may encourage broader diversity in objects
that are today standardized, such as smartphones and automobiles. Scale
is no object: one UK company, Facit Homes, uses personalized designs and
3D printing to create customized houses to suit the consumer. Product
features will evolve to serve different markets and geographies, and
there will be a rapid proliferation of goods and services to regions of
the world not currently well served by traditional manufacturing.
8. ‘Sense and avoid’ drones
Flying robots to check power lines or deliver emergency aid

Unmanned
aerial vehicles, or drones, have become an important and controversial
part of military capacity in recent years. They are also used in
agriculture, for filming and multiple other applications that require
cheap and extensive aerial surveillance. But so far all these drones
have had human pilots; the difference is that their pilots are on the
ground and fly the aircraft remotely.
The next step with drone technology is to develop machines that fly
themselves, opening them up to a wider range of applications. For this
to happen, drones must be able to sense and respond to their local
environment, altering their height and flying trajectory in order to
avoid colliding with other objects in their path. In nature, birds, fish
and insects can all congregate in swarms, each animal responding to its
neighbour almost instantaneously to allow the swarm to fly or swim as a
single unit. Drones can emulate this.
With reliable autonomy and collision avoidance, drones can begin to
take on tasks too dangerous or remote for humans to carry out: checking
electric power lines, for example, or delivering medical supplies in an
emergency. Drone delivery machines will be able to find the best route
to their destination, and take into account other flying vehicles and
obstacles. In agriculture, autonomous drones can collect and process
vast amounts of visual data from the air, allowing precise and efficient
use of inputs such as fertilizer and irrigation.
In January 2014, Intel and Ascending Technologies showcased prototype
multi-copter drones that could navigate an on-stage obstacle course and
automatically avoid people who walked into their path. The machines use
Intel’s RealSense camera module, which weighs just 8g and is less than
4mm thick. This level of collision avoidance will usher in a future of
shared airspace, with many drones flying in proximity to humans and
operating in and near the built environment to perform a multitude of
tasks. Drones are essentially robots operating in three, rather than
two, dimensions; advances in next-generation robotics technology will
accelerate this trend.
Flying vehicles will never be risk-free, whether operated by humans
or as intelligent machines. For widespread adoption, sense and avoid
drones must be able to operate reliably in the most difficult
conditions: at night, in blizzards or dust storms. Unlike our current
digital mobile devices (which are actually immobile, since we have to
carry them around), drones will be transformational as they are
self-mobile and have the capacity of flying in the three-dimensional
world that is beyond our direct human reach. Once ubiquitous, they will
vastly expand our presence, productivity and human experience.
9. Neuromorphic technology
Computer chips that mimic the human brain

Even
today’s best supercomputers cannot rival the sophistication of the
human brain. Computers are linear, moving data back and forth between
memory chips and a central processor over a high-speed backbone. The
brain, on the other hand, is fully interconnected, with logic and memory
intimately cross-linked at billions of times the density and diversity
of that found in a modern computer. Neuromorphic chips aim to process
information in a fundamentally different way from traditional hardware,
mimicking the brain’s architecture to deliver a huge increase in a
computer’s thinking and responding power.
Miniaturization has delivered massive increases in conventional
computing power over the years, but the bottleneck of shifting data
constantly between stored memory and central processors uses large
amounts of energy and creates unwanted heat, limiting further
improvements. In contrast, neuromorphic chips can be more energy
efficient and powerful, combining data-storage and data-processing
components into the same interconnected modules. In this sense, the
system copies the networked neurons that, in their billions, make up the
human brain.
Neuromorphic technology will be the next stage in powerful computing,
enabling vastly more rapid processing of data and a better capacity for
machine learning. IBM’s million-neuron TrueNorth chip, revealed in
prototype in August 2014, has a power efficiency for certain tasks that
is hundreds of times superior to a conventional CPU (Central Processing
Unit), and more comparable for the first time to the human cortex. With
vastly more compute power available for far less energy and volume,
neuromorphic chips should allow more intelligent small-scale machines to
drive the next stage in miniaturization and artificial intelligence.
Potential applications include: drones better able to process and
respond to visual cues, much more powerful and intelligent cameras and
smartphones, and data-crunching on a scale that may help unlock the
secrets of financial markets or climate forecasting. Computers will be
able to anticipate and learn, rather than merely respond in
pre-programmed ways.
10. Digital genome
Healthcare for an age when your genetic code is on a USB stick

While
the first sequencing of the 3.2 billion base pairs of DNA that make up
the human genome took many years and cost tens of millions of dollars,
today your genome can be sequenced and digitized in minutes and at the
cost of only a few hundred dollars. The results can be delivered to your
laptop on a USB stick and easily shared via the internet. This ability
to rapidly and cheaply determine our individual unique genetic make-up
promises a revolution in more personalized and effective healthcare.
Many of our most intractable health challenges, from heart disease to
cancer, have a genetic component. Indeed, cancer is best described as a
disease of the genome. With digitization, doctors will be able to make
decisions about a patient’s cancer treatment informed by a tumour’s
genetic make-up. This new knowledge is also making precision medicine a
reality by enabling the development of highly targeted therapies that
offer the potential for improved treatment outcomes, especially for
patients battling cancer.
Like all personal information, a person’s digital genome will need to
be safeguarded for privacy reasons. Personal genomic profiling has
already raised challenges, with regard to how people respond to a
clearer understanding of their risk of genetic disease, and how others –
such as employers or insurance companies – might want to access and use
the information. However, the benefits are likely to outweigh the
risks, because individualized treatments and targeted therapies can be
developed with the potential to be applied across all the many diseases
that are driven or assisted by changes in DNA.
This list was compiled by the Meta-Council on Emerging Technologies,
who would like to thank: Justine Cassell, Professor, Human-Computer
Interaction, Carnegie Mellon University; Paolo Dario, Director, The
BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa; Julia Greer,
Professor of Materials Science and Mechanics, California Institute of
Technology (Caltech); and Jennifer Lewis, Hansjorg Wyss Professor at the
Harvard School of Engineering and Applied Sciences, from the Network of Global Agenda Councils; Michael Pellini, President and Chief Executive Officer, Foundation Medicine Inc., from the Technology Pioneers;
and William “Red” Whittaker, Professor at Carnegie Mellon University,
for their invaluable contributions to the creation of this list.
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