LOS ALAMITOS, Calif.,
Dec. 3, 2020 /PRNewswire/ -- The IEEE
Computer Society (IEEE CS) revealed the scorecard for its 2020
Technology Predictions, which were published in Computer
magazine's December 2019 issue. The
2020 Technology Predictions garnered a collective grade of B-.
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"Last year was the least predictable of all years for which we
have conducted technology predictions, and—not surprisingly—our
grade was B-," said Dejan Milojicic,
former IEEE CS president (2014) and current Distinguished
Technologist at Hewlett Packard Labs. "The advancement of most
technologies slowed due to the ongoing pandemic, but then a few
were actually accelerated."
The highest grades were given to AI@Edge, additive
manufacturing, adversarial machine learning (ML), and artificial
intelligence (AI) and critical systems:
- AI@Edge (graded A-) was driven by the need to automate
and filter data close to the edge by applying AI; it was critical
in collecting pandemic-related information.
- Additive manufacturing (graded A/B) helped produce
critical medical components and provided evidence that distributed,
local manufacturing capabilities can be essential during times of
supply-chain upheaval.
- Adversarial ML (graded B+) was increasingly used as
systems continue to incorporate ML, in particular through variants
of reinforcement learning and neural networks.
- AI and critical systems (also graded B+) were deployed
increasingly in more systems that affect public health, safety, and
welfare.
All 2020 Technology Predictions and Grades
1
|
AI@Edge (A-).
Not surprisingly, the adoption of AI at edge dominated the
predictions in 2020.
|
2
|
Additive
manufacturing (A/B). The bulk of our predictions for additive
manufacturing proved valid in 2020.
|
3-4
|
Adversarial ML
(B+). We correctly predicted that adversarial ML would become
increasingly important in 2020.
|
3-4
|
AI and critical
systems (B+). We predicted that AI would be deployed in more
systems that affect public health, safety, and welfare (as opposed
to, for example, entertainment systems) over the next five
years.
|
5
|
Non-volatile
memory products, interfaces, and applications (B). Non-volatile
memory enables next-generation computing in the data center, at the
edge, and embedded in industrial and consumer
products.
|
6
|
Legal and related
implications to reflect security and privacy (B). We predicted
that legal and policy responses to security and privacy concerns
would continue to demand the attention of engineers, the public,
and policymakers.
|
7
|
Digital Twins,
including Cognitive Twins (B-). Digital Twins are now
mainstream in business, particularly in the manufacturing area with
availability of industrial platforms to support them (GE and
Siemens are main players in this area).
|
8
|
Reliability and
safety challenges for intelligent systems (B/C). Intelligent
systems, which are capable of making autonomous decisions based on
AI algorithms, are becoming increasingly widespread in several
application fields (for example, autonomous robots and
vehicles).
|
9
|
Applying AI to
cybersecurity (B/C). We expected that AI/ML would start being
widely adopted in cybersecurity and even envisioned broad
participation of industry, government, and academia.
|
10
|
Practical delivery
drones (B/C). Our team is largely in consensus that the promise
of practical delivery drones hasn't panned out during
2020.
|
11
|
Cognitive skills
for robots (C+). We predicted that recent breakthroughs in
large-scale simulations, deep reinforcement learning, and computer
vision collectively would bring forth a basic level of cognitive
abilities to robots that would lead to significant improvements of
robotic applications.
|
12
|
Quantum computing
(C+). Quantum computing gained tremendous visibility in
2020.
|
Visit the IEEE CS 2020 Scorecard to view the complete analysis
and evaluation for each prediction.
The Evaluation Process
Following the established process from previous years, the authors
who originally made the predictions in November 2019 evaluated their predictions
individually. The averages and standard deviations were used as a
basis for the discussion that eventually resulted in the final
rating.
The authors' collective rating for the 2020 predictions resulted
in a grade of B-, which was a bit lower than the 2019 and
2018 B grades, and lower still than
the 2017 A- grade.
The technical contributors for this document are available
for interviews. The IEEE CS team of leading technology
experts includes Mary Baker, HP
Inc.; Tom Coughlin, Coughlin
Associates; Erik DeBenedictis,
entrepreneur; Paolo Faraboschi, Hewlett Packard Enterprise VP and
Fellow; Eitan Frachtenberg, data
scientist; Danny Lange, VP of AI at
Unity; Phil Laplante, professor,
Penn State; Andrea Matwyshyn, Professor and Assoc. Dean of
Innovation, Penn State Law – University Park, and professor, Penn
State Engineering; Avi Mendelson,
professor, Technion and NTU Singapore; Cecilia Metra, professor, Bologna University,
and IEEE CS past president; Dejan
Milojicic, Hewlett Packard Enterprise Distinguished
Technologist and former IEEE CS president; Roberto Saracco, Chair of the IEEE-FDC's
Symbiotic Autonomous Systems Initiative; and Jeffrey Voas, NIST.
About the IEEE Computer Society
The IEEE Computer
Society is the world's home for computer science, engineering, and
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