weekly artificial intelligence news
hello viewers welcome back to your one
stop shop for all news ai we're back
once more with the latest sometimes
shocking happenings of the artificial
intelligence universe from working
towards building smarter ai artificial
neurons going quantum and safeguarding
neural networks from attacks all the way
to using natural eye movement for
training metaverse platforms and
computer chips that will predict the
future of gene synthesis we have it all
and more so without further ado let's
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highlights of the week
hybrid human machine framework for
building smarter ai
from chat bots that answer tax questions
to algorithms that drive autonomous
vehicles and dish out medical diagnoses
artificial intelligence undergirds many
aspects of daily life
creating smarter more accurate systems
requires a hybrid human machine approach
according to researchers at the
university of california irvine in a
study published this month in
proceedings of the national academy of
sciences they present a new mathematical
model that can improve performance by
combining human and algorithmic
predictions and confidence scores
humans and machine algorithms have
complementary strengths and weaknesses
each uses different sources of
information and strategies to make
predictions and decisions said co-author
mark stavers uci professor of cognitive
sciences
we show through empirical demonstrations
as well as theoretical analyses that
humans can improve the predictions of ai
even when human accuracy is somewhat
below that of the ai and vice versa
and this accuracy is higher than
combining predictions from two
individuals or two ai algorithms
to test the framework researchers
conducted an image classification
experiment in which human participants
and computer algorithms worked
separately to correctly identify
distorted pictures of animals and
everyday items chairs bottles bicycles
trucks the human participants ranked
their confidence in the accuracy of each
image classification as low medium or
high while the machine classifier
generated a continuous score
the results showed large differences in
confidence between humans and ai
algorithms across images
when predictions and confidence scores
from both were combined using the
researcher's new bahegian framework the
hybrid model led to better performance
than either human or machine predictions
achieved alone
artificial neurons going quantum with
photonic circuits
in recent years artificial intelligence
has become ubiquitous with applications
such as speech interpretation image
recognition medical diagnosis and many
more at the same time quantum technology
has been proven capable of computational
power well beyond the reach of even the
world's largest supercomputer
physicists at the university of vienna
have now demonstrated a new device
called quantum memristor which may allow
to combine these two worlds thus
unlocking unprecedented capabilities
the experiment carried out in
collaboration with the national research
council cnr and the polytechnico di
milano in italy has been realized on an
integrated quantum processor operating
on single photons the work is published
in the current issue of the journal
nature photonics at the heart of all
artificial intelligence applications are
mathematical models called neural
networks these models are inspired by
the biological structure of the human
brain made of interconnected nodes just
like our brain learns by constantly
rearranging the connections between
neurons neural networks can be
mathematically trained by tuning their
internal structure until they become
capable of human level tasks recognizing
our face interpreting medical images for
diagnosis even driving our cars
having integrated devices capable of
performing the computations involved in
neural networks quickly and efficiently
has thus become a major research focus
both academic and industrial one of the
major game changers in the field was the
discovery of the memristor made in 2008.
this device changes its resistance
depending on the memory of the past
current hence the name memory resistor
or memristor
immediately after its discovery
scientists realized that among many
other applications the peculiar behavior
of memristors was surprisingly similar
to that of neural synapses the memristor
has thus become a fundamental building
block of neuromorphic architectures
making deep neural networks safe from
attacks
if a sticker on a banana can make it
show up as a toaster how might strategic
vandalism warp how an autonomous vehicle
perceives a stop sign
now an immune inspired defense system
for neural networks can ward off such
attacks designed by engineers biologists
and mathematicians at the university of
michigan
deep neural networks are a subset of
machine learning algorithms used for a
wide variety of classification problems
these include image identification and
machine vision used by autonomous
vehicles and other robots natural
language processing language translation
and fraud detection however it is
possible for a nefarious person or group
to adjust the input slightly and send
the algorithm down the wrong train of
thought so to speak
to protect algorithms against such
attacks the michigan team developed the
robust adversarial immune inspired
learning system
rails represents the very first approach
to adversarial learning that is modeled
after the adaptive immune system which
operates differently than the innate
immune system said alfred hero the john
h holland distinguished university
professor who co-led the work published
in ieee access
while the innate immune system mounts a
general attack on pathogens the
mammalian immune system can generate new
cells designed to defend against
specific pathogens it turns out that
deep neural networks already inspired by
the brain system of information
processing can take advantage of this
biological process too
simulated human eye movement to train
metaverse platforms
computer engineers at duke university
have developed virtual eyes that
simulate how humans look at the world
accurately enough for companies to train
virtual reality and augmented reality
programs
called icin for short the program will
help developers create applications for
the rapidly expanding metaverse while
protecting user data the results have
been accepted and will be presented at
the international conference on
information processing in sensor
networks a leading annual forum on
research in network sensing and control
if you're interested in detecting
whether a person is reading a comic book
or advanced literature by looking at the
rise alone you can do that said maria
gorlitova the nortel network's assistant
professor of electrical and computer
engineering at duke
but training that kind of algorithm
requires data from hundreds of people
wearing headsets for hours at a time
corletova added we wanted to develop
software that not only reduces the
privacy concerns that come with
gathering this sort of data but also
allows smaller companies who don't have
those level of resources to get into the
metaverse game
the poetic insight describing eyes as
the windows to the soul has been
repeated since at least biblical times
for good reason the tiny movements of
power rise move and pupils dilate
provide a surprising amount of
information
human eyes can reveal if we're bored or
excited where concentration is focused
whether or not we're expert or novice at
a given task or even if we're fluent in
a specific language
eye movement data is invaluable to
companies building platforms and
software in the metaverse for example
reading a user's eyes allows developers
to tailor content to engagement
responses or reduce resolution in their
peripheral vision to save computational
power
computer chip to predict the future of
gene synthesis
creating synthetic life could be easily
within our grasp soon based on a
comparison with the evolution of
computer chips computer programming and
gene synthesis appear to share little in
common but according to university of
cincinnati professor andrew steckel an
ohio eminent scholar leaps forward in
technology in the former make him
optimistic that wide-scale gene
manufacture is achievable
steckle and his student joseph ryolo
used the history of microchip
development and large-scale computer
software platforms as a predictive model
to understand another complex system
synthetic biology
stekel said the project was inspired by
comments by another student in his group
elliot gomez
no analogy is perfect dna doesn't meet
certain definitions of digital code
ryolo said but there are a lot of ways
the genome and software code are
comparable
according to the uc study synthetic
biology has the potential to be the next
epochal technological human advancement
following microelectronics and the
internet its applications are boundless
from creating new biofuels to developing
new medical treatments scientists at the
j craig venter institute created the
first synthetic organism in 2010 when
they transplanted an artificial genome
of mycoplasma mycoids into another
bacterial cell
this relatively simple artificial genome
took 15 years to develop at a cost of
more than 40 million dollars
but by using computer chip development
as a guide cycle said we can infer the
speed and costs of producing similar
synthetic life might follow a similar
trajectory as the performance and cost
of electronics over time
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