Published 4 years ago.
About a 6 minute read.
Image: Peter Ma, Environmental Monitor
Computer scientists at Intel are protecting the earth and we humans on it through a dedicated unit called AI for Social Good. We caught up with Head Anna Bethke and several of Intel’s software innovators to learn more about their work.
Artificial intelligence is as scary as it is exciting. On the one hand, it may eliminate vast job
categories, while on the other, it will enable humans to do more interesting
work and achieve incredible advancements that would have otherwise taken much
Computer scientists at Intel are deploying their skills in this area, to
protect the earth and we humans on it through a dedicated unit called AI for
Social Good. They are developing
applications for everything from classifying icebergs to monitoring whale health
digitally through their snot. Seriously, check out the
We caught up with Anna Bethke, Head
of AI for Social Good at Intel, as well as several of Intel’s software
innovators to learn more about their work and what kinds of breakthroughs to
Anna Bethke: Intel is committed to advancing uses of AI that most positively
impact our world; and there are both groups and individuals across many of our
business units that are applying the incredible work they do every day in
hardware, software and algorithm development to achieving this goal. As the head
of this cross-company initiative, I act as the glue between the Intel employees
who are able to help, and those socially impactful organizations that need extra
technical guidance to move their missions forward.
AB: Intel uses AI capabilities to impact the world in two ways. One is to
support social good organizations with AI technologies and expertise to
accelerate their positive work in the world. For example, we worked with
nonprofit RESOLVE to create TrailGuard AI — an AI
technology to detect poachers entering Africa's wildlife reserves; and alert
park rangers in real time, so poachers can be stopped before killing endangered
animals. RESOLVE is partnering with National Geographic Society and the
Leonardo DiCaprio Foundation to deploy the TrailGuard AI cameras this year.
The second is to support research efforts to ensure AI is more transparent, less
biased and more accessible to all. An example you're familiar with is Peter
Ma's Clean Water AI system to detect harmful bacteria in the water in real
time. The organizations we partner with often see AI as being more cost
effective than other, more traditional forms of technology; and when AI isn’t
the best solution for whatever reason, we always advise organizations to seek
the best solution for them. We partner with both nonprofit and commercial
organizations, as both types of organizations have the very real capability to
positively impact our world.
Let’s look at a few examples:
Rosemary Day: Over time, I plan to adopt a wider data set used to classify
plants and analyze
across the globe. I’m hopeful that governments and large corporates will look to
partner with one another to help make decisions that can change the world — like
combatting climate change and better predicting weather patterns for susceptible
groups of people. It is something that is impacting us all and that we all need
to think about.
Peter Ma: Our current prototype places water drops under microscope and
connects it to an Intel Movidius Neural Computing Stick. By doing this, we
can inference the camera image and classify different bacteria through the deep
learning neural network in near real time. Our next iteration of the prototype
will automate the water sampling process, so that our clients can connect it
directly to the water sources. Current water testing mainly relies on chemical
strips — a method that is effective but slow, as we have to wait for chemical
reactions. But if a new type of bacteria emerges, it would cost millions to
develop and deploy a new type of chemical strip. Because Clean Water AI is
optical, and it relies on image data to train neural networks, it makes
detection of new types of bacteria much easier. It runs on the $79 Movidius
Neural Compute Stick, a cost-effective solution that turns a low-cost laptop
into a high-powered computer engine, capable of advanced AI capabilities, that
can often cost thousands of dollars. Long term, this project is slated to
productize to scale into a wide variety of industries and third-world countries.
Risab Biswas: We can use AI applications to find and identify diseases in
plants by using the advanced capabilities of image recognition and
classification. Long term, my vision for this project is to scale the use case
to develop an app, and eventually drones to find and identify diseased plants.
Currently, we have a 95 percent accuracy rating for identifying plant disease,
thus based on this data I'm confident the percentage of yields will improve with
this technology. More specifically, according to our experimentation on both
labs and the farms, we have statistically calculated that the yield can be
increased to 30-40 percent. Moving forward, we have a planned pilot where we
will be testing the system to determine a more accurate calculation.
Published Jun 17, 2019 8am EDT / 5am PDT / 1pm BST / 2pm CEST