Advertisement

Adversarial Machine Learning Threat Matrix – A Framework To Defend AI Systems From Adversarial Attacks | MarkTechPost

adversarial machine learning threat matrix – a framework to defend ai systems from adversarial attacks | marktechpost

BEGIN ARTICLE PREVIEW:

Background vector created by rawpixel.com – www.freepik.com

Microsoft, in collaboration with MITRE research organization and a dozen other organizations, including IBM, Nvidia, Airbus, and Bosch, has released the Adversarial ML Threat Matrix, a framework that aims to help cybersecurity experts prepare attacks against artificial intelligence models. 

With AI models being deployed in several fields, there is a rise in critical online threats jeopardizing their safety and integrity. The Adversarial Machine Learning (ML) Threat Matrix attempts to assemble various techniques employed by malicious adversaries in destabilizing AI systems.

AI models perform several tasks, including identifying objects in images by analyzing the information they ingest for specific common patterns. The researchers have developed malicious patterns that hackers could introduce into the AI systems to trick these models into making mistakes. An Auburn University team had even managed to fool a Google LLC image recognition model into misclassifying objects in photos by slightly adjusting the objects’ position in each input image. 

The organizations have contributed a collection of adversarial AI system vulnerabilities and hacking tactics to the Adversarial ML Threat Matrix that helps to investigate and overcome online attacks. One sample demonstrates a method of targeting AI models with malicious …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE

‘Words do matter’: Artificial intelligence helping review, change word choices in workplace

‘words do matter’: artificial intelligence helping review, change word choices in workplace

BEGIN ARTICLE PREVIEW:

SAN JOSE, Calif. (KGO) — The Oakland Unified School District this week issued an apology for sending out a survey that included a historically racist term for people of Asian descent. Words can offend.However, a movement is underway to prevent bad word choices. It’s part of the changing workplace in Building A Better Bay Area.”I think that words do matter, so I think that you do have to be very mindful of the words that you use,” says Jaye Bailey, Valley Transportation Authority’s head of civil rights and employee relations.Whether it’s a transit agency like VTA or a private company, attention to messaging has never been greater as a result of the social justice movement.RELATED: Oakland Unified School District apologizes after ‘historically racist’ term used in survey”You really work hard to normalize the language within your organization so that everybody is aware of it so that it becomes second, second nature,” she added.VTA is engaged in a conscious effort to improve language on websites and in marketing materials, employee communications and advertising. Thirteen employees, ranging from bus operators to department heads, are in training developed by the Government Alliance on Race and Equity.At …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “‘Words do matter’: Artificial intelligence helping review, change word choices in workplace”

Biometric Cards, Digital ID, and Machine Learning: This Week’s Top Mobile ID Stories – Mobile ID World

biometric cards, digital id, and machine learning: this week’s top mobile id stories – mobile id world

BEGIN ARTICLE PREVIEW:

This week’s roundup of Mobile ID World’s top stories brings us two prominent themes: alternative approaches to digital ID, and biometric cards.The latter topic has been gaining momentum over the last several months, and this week brought the latest big development in this emerging space. IDEMIA and Mastercard have launched their first trial of biometric payment cards in Asia, in collaboration with Singapore-based FinTech specialist MatchMove:IDEMIA and Mastercard Announce First Biometric Card Pilot in AsiaMeanwhile, another biometric cards specialist had some news of its own. IDEX announced this week that it had received a production order from Ubivelox, which is integrating IDEX’s TrustedBio fingerprint sensors into its own biometric payment card solution:Korean Smart Card Specialist Orders IDEX Biometrics SensorsIn the world of digital ID, readers proved interested in the news that the University of Tennessee has become the latest academic institution to let students keep digital versions of their student ID cards on their iPhones or Apple Watches. This is part of a growing trend, and one that could intensify in the wake of COVID-19, if the UT case is any example:Allegion and CBORD Provide Mobile IDs for University of Tennessee StudentsAnd in …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Biometric Cards, Digital ID, and Machine Learning: This Week’s Top Mobile ID Stories – Mobile ID World”

Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures

decoding covid-19 pneumonia: comparison of deep learning and radiomics ct image signatures

BEGIN ARTICLE PREVIEW:

This article was originally published here
Eur J Nucl Med Mol Imaging. 2020 Oct 23. doi: 10.1007/s00259-020-05075-4. Online ahead of print.

ABSTRACT
PURPOSE: High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for COVID-19 pneumonia prediction, and uncover CT image features significant for COVID-19 pneumonia from deep learning and radiomics framework.
METHODS: A total of 266 patients with COVID-19 and other viral pneumonia with clinical symptoms and CT signs similar to that of COVID-19 during the outbreak were retrospectively collected from three hospitals in China and the USA. All the pneumonia lesions on CT images were manually delineated by four radiologists. One hundred eighty-four patients (n = 93 COVID-19 positive; n = 91 COVID-19 negative; 24,216 pneumonia lesions from 12,001 CT image slices) from two hospitals from China served as discovery cohort for model development. Thirty-two patients (17 COVID-19 positive, 15 COVID-19 negative; 7883 pneumonia lesions from 3799 CT image slices) from a US hospital served as external validation cohort. A bi-directional adversarial network-based framework and PyRadiomics package were used to extract deep learning and radiomics features, respectively. Linear and Lasso classifiers were used to develop models predictive of COVID-19 …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures”

Deep learning model provides rapid detection of stroke-causing blockages

deep learning model provides rapid detection of stroke-causing blockages

BEGIN ARTICLE PREVIEW:

A sophisticated type of artificial intelligence (AI) called deep learning can help rapidly detect blockages in the arteries that supply blood to the head, potentially speeding the onset of life-saving treatment, according to a study published in Radiology.
Large vessel occlusions are blockages in the arteries that supply oxygenated blood to the brain. These occlusions account for a significant proportion of ischemic strokes, the most common type of stroke. Prompt diagnosis is critical in order to begin recanalization, or opening of the blocked artery, through a treatment known as endovascular therapy.
“Minutes matter in this time-sensitive diagnosis,” said study lead author Matthew T. Stib, M.D., a radiology resident at the Warren Alpert Medical School at Brown University in Providence, Rhode Island. “Every minute that we reduce the time to recanalization extends the patient’s disability-free life by a week.”
CT angiography (CTA), a three-minute exam that provides detailed views of the blood vessels, is the gold standard for detecting these occlusions. Radiologists are highly accurate at identifying large vessel occlusions on CTA, but they are not always available, and any backlogs at the hospital can further delay care.
Dr. Stib and his colleagues at Brown explored the use of deep …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Deep learning model provides rapid detection of stroke-causing blockages”

USPTO publishes report on public views on artificial intelligence and IP Policy – US IP law adequate for now, until artificial general intelligence is reached?

uspto publishes report on public views on artificial intelligence and ip policy – us ip law adequate for now, until artificial general intelligence is reached?

BEGIN ARTICLE PREVIEW:

White & Case Technology NewsflashAs artificial intelligence (AI) evolves, it becomes imperative to examine whether the current intellectual property (IP) legal frameworks, in the US and abroad, are adequate to address issues specific to AI. The United Kingdom Intellectual Property Office (UKIPO), European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) have all recently had the opportunity to weigh in on the issue of whether an AI machine can be named as the inventor on a patent application. In late 2018 and in 2019, Dr. Stephen Thaler filed two patent applications in each of the UKIPO, EPO and USPTO, naming DABUS,1 a patented AI machine, as the inventor of the subject inventions.2 All three offices came to the same conclusion for similar reasons: Current law suggests that an inventor must be a human.3 In January 2019, the USPTO held an AI IP policy conference, which included panel discussions featuring IP specialists to discuss AI and IP policy considerations.4 Following the conference and Thaler’s patent applications, the USPTO sought further insight into public opinion on how IP laws and policy should develop as AI technology advances and issued two requests for comment (each an “RFC”), one on August 27, 20195 and a second …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “USPTO publishes report on public views on artificial intelligence and IP Policy – US IP law adequate for now, until artificial general intelligence is reached?”

Deep Science: Alzheimer’s screening, forest-mapping drones, machine learning in space, more

deep science: alzheimer’s screening, forest-mapping drones, machine learning in space, more

BEGIN ARTICLE PREVIEW:

Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect the most relevant recent discoveries and papers — particularly in but not limited to artificial intelligence — and explain why they matter.
This week, a startup that’s using UAV drones for mapping forests, a look at how machine learning can map social media networks and predict Alzheimer’s, improving computer vision for space-based sensors and other news regarding recent technological advances.
Predicting Alzheimer’s through speech patterns
Machine learning tools are being used to aid diagnosis in many ways, since they’re sensitive to patterns that humans find difficult to detect. IBM researchers have potentially found such patterns in speech that are predictive of the speaker developing Alzheimer’s disease.
The system only needs a couple minutes of ordinary speech in a clinical setting. The team used a large set of data (the Framingham Heart Study) going back to 1948, allowing patterns of speech to be identified in people who would later develop Alzheimer’s. The accuracy rate is about 71% or 0.74 area under the curve …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “Deep Science: Alzheimer’s screening, forest-mapping drones, machine learning in space, more”

FDA leader talks evolving strategy for AI and machine learning

fda leader talks evolving strategy for ai and machine learning

BEGIN ARTICLE PREVIEW:

At a virtual meeting of the U.S. Food and Drug Administration’s Center for Devices and Radiological Health and Patient Engagement Advisory Committee on Thursday, regulators offered updates and new discussion around medical devices and decision support powered by artificial intelligence.One of the topics on the agenda was how to strike a balance between safety and innovation with algorithms getting smarter and better trained by the day.
In his discussion of AI and machine learning validation, Bakul Patel, director of the FDA’s recently-launched Digital Health Center of Excellence, said he sees huge breakthroughs on the horizon.
“This new technology is going to help us get to a different place and a better place,” said Patel. “You’re seeing a great opportunity. You’re seeing automated image diagnostics. We have seen some advanced prevention indicators. Data is becoming the new water. And AI is helping healthcare professionals and patients get more insights into how they can translate what we already knew in different silos into something that’s useful.”
As new tools like those are deployed to “augment what we already have in place,” he said, “we’re also seeing that evidence and information that used to be in different areas that were only …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “FDA leader talks evolving strategy for AI and machine learning”

5 Emerging AI And Machine Learning Trends To Watch In 2021

5 emerging ai and machine learning trends to watch in 2021

BEGIN ARTICLE PREVIEW:

Artificial Intelligence and machine learning have been hot topics in 2020 as AI and ML technologies increasingly find their way into everything from advanced quantum computing systems and leading-edge medical diagnostic systems to consumer electronics and “smart” personal assistants.
Revenue generated by AI hardware, software and services is expected to reach $156.5 billion worldwide this year, according to market researcher IDC, up 12.3 percent from 2019.
But it can be easy to lose sight of the forest for the trees when it comes to trends in the development and use of AI and ML technologies. As we approach the end of a turbulent 2020, here’s a big-picture look at five key AI and machine learning trends– not just in the types of applications they are finding their way into, but also in how they are being developed and the ways they are being used.

The Growing Role Of AI And Machine Learning In Hyperautomation

Hyperautomation, an IT mega-trend identified by market research firm Gartner, is the idea that most anything within an organization that can be automated – such as legacy business processes – should be automated. The pandemic has accelerated adoption of the concept, which is also known as “digital process automation” and “intelligent process …

END ARTICLE PREVIEW

READ MORE FROM SOURCE ARTICLE Continue reading “5 Emerging AI And Machine Learning Trends To Watch In 2021”