Africa
Arm takes machine learning mainstream with neural processing units
Arm aims to take machine learning to mainstream and low-end devices with the launch of its new neural processing units (NPUs). The company is unveiling the Ethos-N57 and Ethos-N37 NPUs, which it will license to chipmakers who can integrate it into their products. The idea is to extend the range of Arm machine learning (ML) processors to enable artificial intelligence (AI) applications in mainstream devices. The company also unveiled the Mali-G57 graphics processing unit (GPU). This is the first mainstream Valhall architecture-based GPU, delivering 1.3 times better performance over previous generations.
Learning Multiparametric Biomarkers for Assessing MR-Guided Focused Ultrasound Treatments Using Volume-Conserving Registration
Zimmerman, Blake, Johnson, Sara, Odรฉen, Henrik, Shea, Jill, Foote, Markus, Winkler, Nicole, Joshi, Sarang, Payne, Allison
Noninvasive MR-guided focused ultrasound (MRgFUS) treatments are promising alternatives to the surgical removal of malignant tumors. A significant challenge is assessing the treated tissue immediately after MRgFUS procedures. Although current clinical assessment uses the immediate nonperfused volume (NPV) biomarker derived from contrast enhanced imaging, the use of contrast agent prevents continuing MRgFUS treatment if margins are not adequate. In addition, the NPV has been shown to provide variable accuracy for the true treatment outcome as evaluated by follow-up biomarkers. This work presents a novel, noncontrast, learned multiparametric MR biomarker that is conducive for intratreatment assessment. MRgFUS ablations were performed in a rabbit VX2 tumor model. Multiparametric MRI was obtained both during and immediately after the MRgFUS ablation, as well as during follow-up imaging. Segmentation of the NPV obtained during follow-up imaging was used to train a neural network on noncontrast multiparametric MR images. The NPV follow-up segmentation was registered to treatment-day images using a novel volume-conserving registration algorithm, allowing a voxel-wise correlation between imaging sessions. Contrasted with state-of-the-art registration algorithms that change the average volume by 16.8%, the presented volume-conserving registration algorithm changes the average volume by only 0.28%. After registration, the learned multiparametric MR biomarker predicted the follow-up NPV with an average DICE coefficient of 0.71, outperforming the DICE coefficient of 0.53 from the current standard of NPV obtained immediately after the ablation treatment. Noncontrast multiparametric MR imaging can provide a more accurate prediction of treated tissue immediately after treatment. Noncontrast assessment of MRgFUS procedures will potentially lead to more efficacious MRgFUS ablation treatments.
Deterministic tensor completion with hypergraph expanders
Harris, Kameron Decker, Zhu, Yizhe
We provide a novel analysis of low rank tensor completion based on hypergraph expanders. As a proxy for rank, we minimize the max-quasinorm of the tensor, introduced by Ghadermarzy, Plan, and Yilmaz (2018), which generalizes the max-norm for matrices. Our analysis is deterministic and shows that the number of samples required to recover an order-$t$ tensor with at most $n$ entries per dimension is linear in $n$, under the assumption that the rank and order of the tensor are $O(1)$. As steps in our proof, we find an improved expander mixing lemma for a $t$-partite, $t$-uniform regular hypergraph model and prove several new properties about tensor max-quasinorm. To the best of our knowledge, this is the first deterministic analysis of tensor completion.
Deep Reinforcement Learning Based Power control for Wireless Multicast Systems
Raghu, Ramkumar, Upadhyaya, Pratheek, Panju, Mahadesh, Aggarwal, Vaneet, Sharma, Vinod
Deep Reinforcement Learning Based Power control for Wireless Multicast Systems Ramkumar Raghu 1, Pratheek Upadhyaya 1, Mahadesh Panju 1, V aneet Aggarwal 1,2, and Vinod Sharma 1 1 Indian Institute of Science, Bangalore, INDIA. Abstract -- We consider a multicast scheme recently proposed for a wireless downlink in [1]. It was shown earlier that power control can significantly improve its performance. However for this system, obtaining optimal power control is intractable because of a very large state space. Therefore in this paper we use deep reinforcement learning where we use function approximation of the Q-function via a deep neural network. We show that optimal power control can be learnt for reasonably large systems via this approach. The average power constraint is ensured via a Lagrange multiplier, which is also learnt. Finally, we demonstrate that a slight modification of the learning algorithm allows the optimal control to track the time varying system statistics. I NTRODUCTION Wireless networks are being constantly refined to cater for seamless delivery of huge amount of data to the end users. With increased user generated contents and proliferation of social networking sites, almost 78% of mobile data traffic is expected to be due to mobile videos [2]. Also, the requested traffic for these contents is ridden with redundant requests [3]. Thus, multicasting is a natural way to address these requests. A multicast queue with network coding is studied in [4], [5] with infinite library of files.
Omniviolence Is Coming and the World Isn't Ready - Facts So Romantic
In The Future of Violence, Benjamin Wittes and Gabriella Blum discuss a disturbing hypothetical scenario. A lone actor in Nigeria, "home to a great deal of spamming and online fraud activity," tricks women and teenage girls into downloading malware that enables him to monitor and record their activity, for the purposes of blackmail. The real story involved a California man who the FBI eventually caught and sent to prison for six years, but if he had been elsewhere in the world he might have gotten away with it. Many countries, as Wittes and Blum note, "have neither the will nor the means to monitor cybercrime, prosecute offenders, or extradite suspects to the United States." Technology is, in other words, enabling criminals to target anyone anywhere and, due to democratization, increasingly at scale.
Top Army modernization priorities are 'on track,' says Army Vice Chief of Staff
Fox News Flash top headlines for Oct. 22 are here. Check out what's clicking on Foxnews.com "----A 1986 graduate of West Point, Martin deployed to Iraq five times including stints as a company commander during Operation Desert Storm, as a battalion and brigade commander during Iraqi Freedom and he commanded the famed 1st Infantry Division at Fort Riley, Kansas. Martin also served as the commander of the Combined Joint Forces Land Component Command during the pivotal Battle of Mosul, a major multi-national offensive that helped the Iraqi government retake control of the Iraqi city from ISIS forces----" From an Army Report --- MARTIN ARMY BIO HERE --- Warrior: There is a lot of discussion about the Army's Top 6 Modernization priorities:...Long Range Precision Fires, Next Generation Combat Vehicles, Future Vertical Lift, Network, Air and Missile Defense, and Soldier Lethalityโฆ. How are they progressing and what sticks out in your mind?
World's first artificial intelligence varsity in Abu Dhabi
It is the first graduate level, research-based AI university in the world. MBZUAI will enable graduate students, businesses, and governments to advance artificial intelligence. The university is named after His Highness Sheikh Mohamed bin Zayed Al Nahyan, Crown Prince of Abu Dhabi and Deputy Supreme Commander of the UAE Armed Forces, who has long advocated for the UAE's development of human capital through knowledge and scientific thinking to take the nation into the future. MBZUAI will introduce a new model of academia and research to the field of AI, providing students and faculty access to some of the world's most advanced AI systems to unleash its potential for economic and societal development. The announcement was made at a press conference at the University campus in Masdar City and was immediately followed by the first meeting of the MBZUAI Board of Trustees. Dr Sultan Ahmed Al Jaber, UAE Minister of State, who has been appointed Chair of the MBZUAI board of trustees and is spearheading the establishment of the University, said: "Mohamed bin Zayed University of Artificial Intelligence aligns with the vision of the UAE leadership that is based on sustainable development, progress and the overall well-being of humanity and underpinned by capacity-building and active participation in finding practical solutions based on innovation and state-of-the-art technology.
Techfest - Wikipedia
Techfest is the annual science and technology festival of Indian Institute of Technology Bombay.[1] It also refers to the independent body of students who organize this event along with many other social initiatives and outreach programs around the year. Techfest is known for hosting a variety of events that include competitions, exhibitions, lectures as well as workshops. Started in 1998 with the aim of providing a platform for the Indian student community to develop and showcase their technical prowess, it has now grown into Asia's Largest Science and Technology Festival[2] with a footfall of 1.75 lakhs in its latest edition.[3][4][5] The activities culminate in a grand three-day event in the campus of IIT Bombay which attracts people from all over the World, including students, academia, corporates and the general public.[6] The very first edition of Techfest was in 1998. The underlying spirit of Techfest was "to promote technology and scientific thinking and innovation" a motto that has been followed by every Techfest since. Techfest '98 also set the broad outlines of Techfest in the form of competitions, lectures, workshops, and exhibitions which went on to become a standard feature at every Techfest. Entrepreneurship also made an appearance in the 1999 and 2000 editions. Technoholix--Techfest in the Dark, showcasing technological entertainment at the end of each day as well as the hub of on the spot activities, made their debut during these years. Techfest 2001-2002 saw the incorporation of IIT Bombay's department oriented events like Yantriki, Chemsplash and Last Straw. Students from G H Raisoni College of Engineering got the Engineering Excellence Award for best design.
The Future Of Everything That Matters In Digital Marketing
When The Wall Street Journal first had the audacity to create a magazine and event series called The Future of Everything, I had to stop myself from rolling my eyes. But then my curiosity got the best of me and I started reading about everything from the problems with fully autonomous vehicles to the new jobs being created as the era of artificial intelligence shows up in the next generation of software. All of this got me thinking about the future of marketing. Having been in the digital marketing industry for the past 24 years, I've witnessed the utter chaos that has plagued the industry (and some would argue it still does). When I first started my career in 1994, all the industry pundits were advocating that television was dead and that broadcast media would soon be replaced with on-demand programming.
Two Canadian startups receive grants from Microsoft's AI for Accessibility initiative BetaKit
Two Canadian startups have been named grantees of Microsoft's AI for Accessibility initiative, a $25 million, five year grant program launched last year to help NGOs, academics, researchers, and inventors accelerate their work for people with disabilities. "We have a huge opportunity and a responsibility to be making technology smarter and more useful for people with disabilities." AI for Accessibility wants to amplify human capability for people around the world with disabilities, by funding relevant projects that leverage and apply AI technology. The program is part of Microsoft's broader AI for Good initiative. This new round of 11 grantees brings the total projects included in the program to 32, which are spread across 13 countries.