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Energy's AI director reviewing 600-plus projects for technologies worth replicating - FedScoop

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The Department of Energy's first artificial intelligence director is currently reviewing more than 600 AI projects across its agencies to identify "critical" technologies worth advancing and replicating. Earlier this month, Cheryl Ingstad was named head of DOE's new Artificial Intelligence and Technology Office (AITO), intended to prioritize department resources for AI projects as the coordinating agency. The Trump administration proposed funding AITO at $5 million in fiscal 2021 -- up from $2.5 million the previous fiscal year -- but the office will be tapping into other agencies' funds as well. "They have program and project resources available," Ingstad told FedScoop in an interview. Energy has 17 national laboratories developing and applying AI to power generation, cybersecurity, national security, and accelerating scientific discoveries.


Overlapping community detection in networks via sparse spectral decomposition

arXiv.org Machine Learning

We consider the problem of estimating overlapping community memberships in a network, where each node can belong to multiple communities. More than a few communities per node are difficult to both estimate and interpret, so we focus on sparse node membership vectors. Our algorithm is based on sparse principal subspace estimation with iterative thresholding. The method is computationally efficient, with a computational cost equivalent to estimating the leading eigenvectors of the adjacency matrix, and does not require an additional clustering step, unlike spectral clustering methods. We show that a fixed point of the algorithm corresponds to correct node memberships under a version of the stochastic block model. The methods are evaluated empirically on simulated and real-world networks, showing good statistical performance and computational efficiency.


Adversarial Attacks against Neural Networks in Audio Domain: Exploiting Principal Components

arXiv.org Machine Learning

Adversarial attacks are inputs that are similar to original inputs but altered on purpose. Speech-to-text neural networks that are widely used today are prone to misclassify adversarial attacks. In this study, first, we investigate the presence of targeted adversarial attacks by altering wave forms from Common Voice data set. We craft adversarial wave forms via Connectionist Temporal Classification Loss Function, and attack DeepSpeech, a speech-to-text neural network implemented by Mozilla. We achieve 100% adversarial success rate (zero successful classification by DeepSpeech) on all 25 adversarial wave forms that we crafted. Second, we investigate the use of PCA as a defense mechanism against adversarial attacks. We reduce dimensionality by applying PCA to these 25 attacks that we created and test them against DeepSpeech. We observe zero successful classification by DeepSpeech, which suggests PCA is not a good defense mechanism in audio domain. Finally, instead of using PCA as a defense mechanism, we use PCA this time to craft adversarial inputs under a black-box setting with minimal adversarial knowledge. With no knowledge regarding the model, parameters, or weights, we craft adversarial attacks by applying PCA to samples from Common Voice data set and achieve 100% adversarial success under black-box setting again when tested against DeepSpeech. We also experiment with different percentage of components necessary to result in a classification during attacking process. In all cases, adversary becomes successful.


Artificial intelligence in COVID-19 drug repurposing

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One study estimated that pharmaceutical companies spent US$2·6 billion in 2015, up from $802 million in 2003, for the development of a new chemical entity approved by the US Food and Drug Administration (FDA). N Engl J Med. 2015; 372: 1877-1879 The increasing cost of drug development is due to the large volume of compounds to be tested in preclinical stages and the high proportion of randomised controlled trials (RCTs) that do not find clinical benefits or with toxicity issues. Given the high attrition rates, substantial costs, and low pace of de-novo drug discovery, exploiting known drugs can help improve their efficacy while minimising side-effects in clinical trials. As Nobel Prize-winning pharmacologist Sir James Black said, "The most fruitful basis for the discovery of a new drug is to start with an old drug". New uses for old drugs.


High-tech Ship Marks 400 Anniversary of the Mayflower

#artificialintelligence

A high-tech ship is marking the 400th anniversary of the sailing of the Mayflower -- the ship that carried a group of European settlers to North America. The famous trip prepared the way for England's colonization of what Europeans in 1620 called the New World. The anniversary was marked this week in Plymouth, England – the starting point for the historic Mayflower crossing of the Atlantic Ocean. Local officials gathered with sea travelers and scientists for the launch of the new ship. It is called the Mayflower Autonomous Ship.


IBM's Watson Assistant can now field election questions

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Ahead of the U.S. presidential election on November 3, IBM today announced it's working with states to put information into the hands of potential voters. Using the AI and natural language processing capabilities of Watson Assistant, IBM says it's helping field voter queries online and via phone by advising people on polling place locations, voting hours, procedures for requesting mail-in ballots, and deadlines. Research from the Pew Center indicates that nearly half of all U.S. voters expect to have difficulties casting a ballot due to the coronavirus pandemic. In a recent NPR/PBS NewsHour/Marist Poll, 41% of those surveyed said they believed the U.S. is not very prepared or not at all prepared to keep November's election safe and secure. IBM's election-focused Watson Assistant offering taps Watson Discovery to surface information about voting logistics from federal, state, and county websites; local news reports; and government documents.


Iran vows 'hit' on all involved in U.S. killing of top general

Boston Herald

The chief of Iran's paramilitary Revolutionary Guard threatened Saturday to go after everyone who had a role in a top general's January killing during a U.S. drone strike in Iraq. The guard's website quoted Gen. Hossein Salami as saying, "Mr. Our revenge for martyrdom of our great general is obvious, serious and real." U.S. President Donald Trump warned this week that Washington would harshly respond to any Iranian attempts to take revenge for the death of Gen. Qassem Soleimani, tweeting that "if they hit us in any way, any form, written instructions already done we're going to hit them 1000 times harder." The president's warning came in response to a report that Iran was plotting to assassinate the U.S. ambassador to South Africa in retaliation for Soleimani's killing at Baghdad's airport at the beginning of the year.


Google Cloud secures U.S. military AI cancer research contract

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Google Cloud announced today that it landed a contract to supply Veterans Affairs hospitals and Defense Health Agency treatment facilities with AI for predictive cancer and disease diagnosis. The contract comes from the Defense Innovation Unit (DIU), a Pentagon organization that brings consumer technology into the military. "The initial rollout will take place at select Defense Health Agency treatment facilities and Veteran's Affairs hospitals in the United States, with future plans to expand across the broader U.S. Military Health System," a Google Cloud post reads. "The AI-based models used to assist doctors as part of the prototype were developed from public and private datasets that were de-identified to remove personal health information and any personally identifiable information. All patient diagnostic data will solely be managed by the individual hospital or provider."


AI Weekly: Cutting-edge language models can produce convincing misinformation if we don't stop them

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It's been three months since OpenAI launched an API underpinned by cutting-edge language model GPT-3, and it continues to be the subject of fascination within the AI community and beyond. Portland State University computer science professor Melanie Mitchell found evidence that GPT-3 can make primitive analogies, and Columbia University's Raphaël Millière asked GPT-3 to compose a response to the philosophical essays written about it. But as the U.S. presidential election nears, there's growing concern among academics that tools like GPT-3 could be co-opted by malicious actors to foment discord by spreading misinformation, disinformation, and outright lies. In a paper published by the Middlebury Institute of International Studies' Center on Terrorism, Extremism, and Counterterrorism (CTEC), the coauthors find that GPT-3's strength in generating "informational," "influential" text could be leveraged to "radicalize individuals into violent far-right extremist ideologies and behaviors." Bots are increasingly being used around the world to sow the seeds of unrest, either through the spread of misinformation or the amplification of controversial points of view.


UAE gets American drones as China ramps up sales

Al Jazeera

The White House's recent decision to allow the sale of advanced weapons systems to the United Arab Emirates highlights the deliberate shift in US policy towards the UAE after it signed "normalisation" accords with Israel. Why would the UAE want American drones as it already has dozens of Chinese armed unmanned aerial vehicles (UAVs) in its inventory? And why has the United States now agreed to these sales, overcoming its traditional reticence to sell sophisticated weapons to other countries? Chinese armed drones have made a significant effect on the battlefields across the Middle East and North Africa. They have been used to assassinate Houthi rebel leaders in Yemen, kill ISIL-affiliated fighters in the Sinai, and for a time help Khalifa Haftar dominate the battlespace in Libya.