Africa, Artificial Iintelligence, Arts, Australia, Biodiversity,
Climate Change, Data, Data Mining, Europe, Fish, Flying Car,
India, International Space Station, Net Zero, Ocean, Open Data,
Plastic, Recycling, Waste
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January 2021 - January 2023:
Starks: At Icebreaker One were making data
work harder to deliver net zero. Were promoting the idea that
companies publish their reports, data, and metadata in a way that can
be properly indexed.
have an incredible opportunity to leverage data to their advantage,
but only if they can harness the power of that data to yield real, valuable,
and actionable insights. This course examines some of the hottest trends
in data, including The Internet of Things, Machine Learning, Data Visualization,
and Big Data. The Future of Data explains what these terms mean, and
how they could impact you. This course also illustrates proper data
collection and analysis process management, and how to effectively present
plastic waste from space and counting the fish in the seas: heres
how AI can help protect the oceans
Philipp Bayer, Adjunct Research
Fellow, UWA Oceans Institute, The University of
Western Australia; Ahmed Elagali, Research associate, The University
of Western Australia; Julie Robidart, Adjunct Senior Research Fellow,
UWA Oceans Institute, The University of Western Australia, and Kate
Marie Quigley, Adjunct Senior Research Fellow, James Cook University
You’ve seen the art AI image
generators can create, and you may have played with natural language
AI chatbots. You’ve benefited from artificial intelligence tools recommending
you music and suggesting your next streaming show.
But AI can do much more. Humans
are excellent at spotting patterns. It’s why we see faces
on Mars or in the clouds. But in some areas, AI is even better.
Give one of these tools a million photographs and ask it to spot telltale
signs – and it can. AI can enable research at scales previously impossible.
We’ve used AI’s exceptional
pattern recognition to trawl through satellite images and map the tonnes
of plastic pollution threatening our seas – in real time. Already, this
found more than 4,000 unreported informal dumps next to rivers.
This is useful, given just
ten rivers contribute nearly all the plastic entering our
This is just the start. So
far, AI has shown promise in our
projects mapping seagrass meadows from space and finding
unknown reefs likely to harbour heat-resilient coral. Soon, we hope
we’ll be able to put AI on the job to find out exactly what fish live
where – without ever seeing them.
Is AI really a gamechanger for science?
Yes. Think of the vast volumes
of data scientists have gathered in recent decades. Until now, trawling
through the data has been painstaking and at times tedious. That’s because
while detecting patterns is something humans do well, we’re slower.
AI mines large data sets,
which can be anything from photos to numbers. You train it so it knows
what you’re looking for. Then the software tool gets to work, detecting
patterns – and importantly, offering up predictions about how these
These methods are especially
powerful for messy and complex biological data. For example, the AI
tool AlphaFold has totally
revolutionised the slow process of understanding how proteins
fold themselves into origami-like shapes inside cells. Previously, it
might have taken months or years to figure out a single protein structure.
This year, AlphaFold announced predicted structures for 200
What can AI offer ecology?
We’ve found AI useful at finding
unknown reefs with corals primed to survive despite warming
waters. That’s vital, given the oceans have taken up almost all of the
heat trapped by the trillion tonnes of greenhouse gases we’ve put in
And we’ve found AI can usefully
identify specific environmental conditions under which reefs will survive
as the oceans heat up. Our research suggests hundreds of reefs among
the thousands in the Great Barrier Reef may
be home to corals which have higher heat tolerance than normal.
Now we know this, we can protect these reefs – and turn to them for
potential use to restore dying reefs elsewhere.
of “super reefs” isn’t new. Other researchers have focused on protecting
coral reefs globally in the hope of safeguarding these ecosystems
against the expected mass coral death as water temperatures rise. What
we have added was the discovery that AI can help find these heat-resilient
corals. Without AI, it would have been like trying to find a needle
in a haystack.
waste from space would have been almost impossible before AI image detection
programs became available. How does it work? Essentially, photos taken
by European Space Agency satellites are scanned by AI to spot hidden
plastic dumps. Then we refine it over time, to see if these sites are
getting bigger – and if they’re close to rivers or lakes, which could
carry plastics into the seas and add to the millions of tonnes of turtle-choking,
fish-killing plastics already swilling around.
The goal is
to find the sites at highest risk of adding to ocean plastics. Once
we know this, enforcement agencies in each of the 112 countries we’ve
mapped can respond to the most urgent problems first. So far we’ve
found more than 4,000 sites, with around one in five within
200 metres of a waterway. When we looked at Indonesia in detail, we
found double the number of publicly listed dump sites.
AI is also
proving itself as a labour-saver. One part of science often hidden to
the general public is the sheer number of manual, repetitive tasks.
For instance, if you want to figure out why some baby coral polyps survive
heat or more acid water while others die, you have to measure colour,
growth and survival rates over time. We’ve found AI can do
this work, precisely and fast.
AI is not magic. It is a tool, and all tools have pitfalls. One problem
is placing too much trust in AI outputs, believing them true because
the algorithm has seen more data than we have. But this is dangerous,
as the confidently
wrong answers given by the new ChatGPT AI demonstrate.
free from biases either. That means we have to carefully evaluate the
data we use to train the AI. Plus, we have to remain vigilant and manually
evaluate AI predictions to figure out if they fit with our reality.
AI is a valuable assistant for ecologists – not a replacement.
autonomous floating or underwater drones sampling seawater, with AI
neural networks looking for fish DNA. It sounds like sci-fi, but it’s
now entirely possible. Drone technology has matured. AI tools have arrived.
And we no longer need to catch fish to know what lives in the seas.
All you need are tiny traces of environmental
DNA marine species leave behind in water. Similarly, we could
track coral reef ecosystem health in near real time.
let us take the pulse of these ecosystems at a time when our oceans
are under unprecedented pressure from industrial fishing, marine heatwaves
and acidification from climate change, and plastic pollution. The more
we know, the better we can respond.
and algorithms: pros and cons
by DW Documentary, Tilman
Wolff and Ranga Yogeshwar
Developments in artificial
intelligence (AI) are leading to fundamental changes in the way we live.
Algorithms can already detect Parkinson's disease and cancer, and control
both cars and aircraft. How will AI change our society in the future?
This documentary journeys
to the hot spots of AI research in Europe, the USA and China, and looks
at the revolutionary developments which are currently taking place.
The rapid growth of AI offers many opportunities, but also many dangers.
AI can be used to create sound and video recordings which will make
it more and more difficult to distinguish between fact and fiction.
It will make the world of work more efficient and many professions superfluous.
Algorithms can decide whether to grant loans, who is an insurance risk,
and how good employees are. But there is a huge problem: humans can
no longer comprehend how algorithms arrive at their decisions. And another
big problem is AIs capacity for widespread surveillance. The Chinese
city of Rongcheng is already using an AI-supported 'social credit system'
to monitor and assess its citizens. Does AI pose a danger to our personal
freedoms or democracy? Which decisions can we leave to the algorithms
- and which do we want to? And what are AIs social implications?
be as open as possible, while protecting peoples privacy, commercial
confidentiality and national security. Data from multiple organisations
is needed to address challenges and the data needs to be accessible.
Open Net Zero is a starting point for net-zero data infrastructure built
to address commercial, non-commercial, government and public needs.
It is designed to help make net-zero data discoverable, accessible and
There is substantial Open Data related
to net zero (e.g. company disclosures) and we aim to make this far more
discoverable than it is today.
However, much of the data needed to drive
net-zero decisions is not openly licensed or free for anyone to use.
We aim to make this data more discoverable. To address restricted usage,
we are building a Trust Framework for data sharing enabling Shared
Data to be discovered and licensed at scale.
Credits Gavin Starks CEO & Founder of Icebreaker One
London, United Kingdom
Axiom Space operates missions to the International Space Station (ISS)
for customers, including space agencies, companies, and individuals.
Axiom Space is also the builder and future owner and operator of Axiom
Station, the successor to the ISS.
Axiom Spaces team
has peerless space station construction and operations management experience
and has been involved with every ISS mission since the programs
inception over two decades ago. Axiom Space is the only company with
the privilege of connecting its modules to the ISS during the new stations
assembly in Earths orbit.
This connection allows
Axiom Space to build the successor station cost-effectively, while adopting
the multinational user base and select hardware from the ISS.
Established in 2016
to build the world's first commercial space station
Leveraging the International
Space Station to become its natural successor by 2031
1st Axiom Station module
on schedule to launch and attach to the ISS in late 2025
$2 Billion in customer
contracts & awards
$400 million in customer
4 space launches purchased
from launch provider SpaceX
First private astronaut
crew to the ISS was a 17-day mission launched on April 8, 2022; the
second mission is planned for late Spring 2023
partnership agreements in place
The XPENG X2 is the fifth-generation
flying car independently developed and manufactured by XPENG AEROHT.
For the first time, the X2 adopts an enclosed cockpit with a minimalist
teardrop-shaped design and a sci-fi appearance that takes high-efficient
aerodynamics into account to achieve the ultimate in-flight performance.
In order to reduce weight, the XPENG X2 has a complete carbon fiber
XPENG AEROHT, an affiliate of XPeng Inc., is the largest flying car
company in Asia. Integrating intelligent vehicles and modern aviation,
we are dedicated to producing the safest intelligent electric flying
car for individual users. In the future, we will provide products and
solutions in the field of 3D transportation.
Climate change mechanisms, impacts, risks,
mitigation, adaption, and governance are widely recognized as the biggest,
most interconnected problem facing humanity. Big Data Mining for Climate
Change addresses one of the fundamental issues facing scientists of
climate or the environment: how to manage the vast amount of information
available and analyse it. The resulting integrated and interdisciplinary
big data mining approaches are emerging, partially with the help of
the United Nation's big data climate challenge, some of which are recommended
widely as new approaches for climate change research. Big Data Mining
for Climate Change delivers a rich understanding of climate-related
big data techniques and highlights how to navigate huge amount of climate
data and resources available using big data applications. It guides
future directions and will boom big-data-driven researches on modeling,
diagnosing and predicting climate change and mitigating related impacts.
This book mainly focuses
on climate network models, deep learning techniques for climate dynamics,
automated feature extraction of climate variability, and sparsification
of big climate data. It also includes a revelatory exploration of big-data-driven
low-carbon economy and management. Its content provides cutting-edge
knowledge for scientists and advanced students studying climate change
from various disciplines, including atmospheric, oceanic and environmental
sciences; geography, ecology, energy, economics, management, engineering,
and public policy.
of Big Data Mining for Climate Change Research Group
Director of Climate Modeling Laboratory
Shandong University, China
Prof. Zhang uses big data
mining methods to model, diagnosis, and predict climate change and related
impacts. He has published more than 50 first-authored articles, some
of which were reported by New Scientist (UK), China Science Daily, and
China Social Science Daily.
Jianping Li is a professor
at the State Key Laboratory of Earth Surface Processes and Resource
Ecology and the College of Global Change and Earth System Sciences (GCESS).
He is also vice-chair of the IUGG Union Commission on Climatic and Environmental
Change (CEC) and Executive Secretary General of the International Commission
of Climate (ICCL). His research interests include climatic dynamics
and predictability, monsoon, and annular modes. He is also co-editor
of the title Dynamics and Predictability of Large-Scale, High-Impact
Weather and Climate Event (Cambridge, 2016).
With biodiversity declining
rates and less than a decade remaining to avert the worst
effects of climate change, world leaders and policymakers are on the
hunt for new and innovative solutions. In the halls and meeting rooms
of global COP conferences, digital technologies have been heavily promoted
these interrelated threats to our ecosystem.
At the recent COP27 climate
conference in Egypt, the
Forest Data Partnership — a global consortium co-ordinated
by the World Resources Institute (WRI) in partnership with the U.S.
Department of State, NASA, Google and Unilever — called
for a “global alliance to unlock the value of land use data
to protect and restore nature.” The WRI promoted its Land
and Carbon Lab to measure carbon stocks associated with land
Nature4Climate — a coalition
of 20 environmental organizations — revealed a new online
platform to help implement natural climate solutions. They
also exhibited a report
on the “nature tech market.” At the COP15 biodiversity conference in
a provider of nature intelligence technology, launched
a new digital dashboard to enable standardized measurements
of the health of ecosystems.
Many, however, see such
efforts as a dangerous
push to get untried and untested corporate technologies accepted
as “nature-positive solutions” in the Convention on Biological Diversity
and climate negotiations.
As researchers examining
the role of technologies in biodiversity monitoring and protected area
management, we find that these digital technologies have the potential
to yield positive results, if co-developed and used ethically with Indigenous
Microsoft’s $50 million
for Earth” program, for instance, aims to “transform the
way we monitor, model and ultimately manage Earth’s natural resources
through grants, technology and access to data.” Such programs, including
Forest Data Partnership, have helped establish partnerships
involving philanthropic, academic, non-governmental, public and private
In a critique
of the Forest Data Partnership, the environmental organization
Greenpeace argued that it is “nothing but a green light for eight more
years of forest destruction, with little respect for the rights of Indigenous
Peoples and local communities.” It also argued that this allows polluters
to do more business as usual through “carbon trickery instead of advancing
true climate action.”
Technology for a just and sustainable future
At COP15 there has been
a critical parallel movement to support Indigenous-led
conservation to meet global biodiversity and climate change
Recycling is the process
of converting waste materials into new materials and objects. The recovery
of energy from waste materials is often included in this concept. The
recyclability of a material depends on its ability to reacquire the
properties it had in its original state. It is an alternative to "conventional"
waste disposal that can save material and help lower greenhouse gas
emissions. It can also prevent the waste of potentially useful materials
and reduce the consumption of fresh raw materials, reducing energy use,
air pollution (from incineration) and water pollution (from landfilling).
Recycling is a key component
of modern waste reduction and is the third component of the "Reduce,
Reuse, and Recycle" waste hierarchy. It promotes environmental
sustainability by removing raw material input and redirecting waste
output in the economic system. There are some ISO standards related
to recycling, such as ISO 15270:2008 for plastics waste and ISO 14001:2015
for environmental management control of recycling practice.
Recyclable materials include
many kinds of glass, paper, cardboard, metal, plastic, tires, textiles,
batteries, and electronics. The composting and other reuse of biodegradable
waste such as food and garden waste is also a form of
recycling. Materials for recycling are either delivered to a household
recycling center or picked up from curbside bins, then sorted, cleaned,
and reprocessed into new materials for manufacturing new products.
In ideal implementations,
recycling a material produces a fresh supply of the same material
for example, used office paper would be converted into new office paper,
and used polystyrene foam into new polystyrene. Some types of materials,
such as metal cans, can be remanufactured repeatedly without losing
their purity. With other materials, this is often difficult or too expensive
(compared with producing the same product from raw materials or other
sources), so "recycling" of many products and materials involves
their reuse in producing different materials (for example, paperboard).
Another form of recycling is the salvage of constituent materials from
complex products, due to either their intrinsic value (such as lead
from car batteries and gold from printed circuit boards), or their hazardous
nature (e.g. removal and reuse of mercury from thermometers and thermostat.
Top 10 awesome
RECYCLING BUSINESSES with high profit in future
by Eco Snooki
START A WASTE RECYCLING BUSINESS IN AFRICA (2022), best waste recycling
business ideas by Business in Africa
How People Profit Off Indias
Garbage | World Wide Waste
by Insider Business
urban recycling cooperatives in Brazil
by Earthworm Foundation
Recycling revolutionary Veena Sahajwalla turns old clothes into kitchen
tiles | Australian Story by ABC NewsIn-depth
Human Waste into Renewable Energy? by Undecided with Matt Ferrell
Managing waste in an environmentally
sound manner and making use of the secondary materials they contain
are key elements of the EUs
EU waste policy aims to
contribute to the circular economy by extracting high-quality resources
from waste as much as possible. The European Green Deal aims to promote
growth by transitioning to a modern, resource-efficient and competitive
economy. As part of this transition, several EU waste laws will be reviewed.
The Waste Framework Directive
is the EUs legal framework for treating and managing waste in
the EU. It introduces an order of preference for waste management called
the waste hierarchy.
Certain categories of waste
require specific approaches. Therefore, as well as the overarching legal
framework, the EU has many laws to address different types of waste.
is the worlds top ranked Financial Market Futurist. He is the
Chairman of the Futurist
and the President of Prestige
Economics. Mr. Schenker advises executives, corporate boards,
public corporations, private companies, central banks, and governmental
bodies. As the Chairman of the Futurist Institute®, Mr. Schenker
has been the driving force behind creating a professional certification
program to help analysts and economists become futurists. He also leads
in-person futurist training courses, gives speeches on futurist topics,
and he directs forecasting, risk management, scenario planning, and
strategic consulting projects of The Futurist Institute®.
volumes of data have made the push to derive data implications more
challenging. And there are political risks and challenges posed by a
rabid democratization of information sharing, social media, and fake
news. In The Fog of Data, Chairman of The Futurist Institute, Jason
Schenker, describes the best ways to navigate data challenges -- and
how to derive valuable data insights.
Disruptions: Real or Imagined
- The Future of Transportation - Jason Schenker at Transparency18 by FreightWaves