AI has the ability to transform every aspect of our lives, from automating our homes and informing commercial decisions to performing complex surgery. The applications of AI are far and wide, but how can we leverage this emerging technology for business? Professor Whittle is an experienced research and education leader – and a world-renowned software engineering specialist. Formerly the Technical Area Lead at NASA Ames Research Center, he's received extensive recognition including two 10-year research impact awards and the CEO Magazine's 2019 Education Executive of the Year award. Dr Catherine is an industry leader and educator in big data, machine learning and analytical management.
Without any doubt, today's biggest buzzword is Artificial Intelligence or AI. Most prominent research organizations, including Gartner, McKinsey, and PWC, have glorified the future of AI with mind-blowing statistics and future predictions. Here is the PWC's report (2018), where it predicts that by 2030, AI will contribute $15.7 trillion to the global economy. The overall productivity increase will be 55%, and the GDP increase by 14%. The executive order could quickly demonstrate the importance of AI within the united states, as signed by the US President Donald J.Trump.
SpaceX made an early holiday delivery to the International Space Station on Sunday, bringing muscle-bound "mighty mice," pest-killing worms and a smart, empathetic robot. The station commander, Italy's Luca Parmitano, used a large robot arm to grab onto the Dragon three days after its launch from Cape Canaveral. The two spacecraft soared 260 miles (420 kilometers) above the South Pacific at the time of capture. "Whenever we welcome a new vehicle on board, we take on board also a little bit of the soul of everybody that contributed to the project, so welcome on board," Parmitano told Mission Control. It marks the third visit for this recycled Dragon.
I am not a genius, have no inside information and don't have influential friends feeding me high-tech solutions to common problems. However, people wonder why I have huge social media followings, know what the next big thing is and have opportunities thrust upon me. The simple answer is I love watching for disruptive technologies and I follow trends--have done so for years. I think you must be on top of what is happening around you and gather intelligence on what technology can change the world and what technology is simple taking up space like marijuana. I've watched the marijuana "technologies" reaping incredible rewards from the few who got in at the early stages.
The Department of Defense (DoD) will harness artificial intelligence (AI) to transform all functions of DoD positively, according to a summary of the Department's AI strategy. AI, machine learning (ML) and related technologies have great potential to transform how the DoD and national security agencies operate and deliver on their mission--but these technologies also require agencies to think in new ways about technology, policy and workforce strategies. AI is generating buzz in part because of its high'cool' quotient-but coolness counts for nothing in national security, where it's all about the mission. Leveraging AI means investing in an AI ecosystem that includes the people, computing infrastructure, data, and policies required to support any organization's deployment of AI technology. As the Center for Strategic and International Studies points out, the technology required to deliver AI results for national security applications differ from what is expected from commercial AI.
CAPE CANAVERAL, FLORIDA – SpaceX made an early holiday delivery to the International Space Station on Sunday, dropping off super muscular "mighty mice," pest-killing worms and a smart, empathetic robot. The station commander, Italy's Luca Parmitano, used a large robot arm to grab onto the Dragon three days after its launch from Cape Canaveral. The two spacecraft soared 260 miles (420 km) above the South Pacific at the time of capture. "Whenever we welcome a new vehicle on board, we take on board also a little bit of the soul of everybody that contributed to the project, so welcome on board," Parmitano told Mission Control. The capsule holds 3 tons (2,720 kg) of supplies, including 40 mice for a muscle and bone experiment.
We formulate the problem of metric learning for k nearest neighbor classification as a large margin structured prediction problem, with a latent variable representing the choice of neighbors and the task loss directly corresponding to classification error. We describe an efficient algorithm for exact loss augmented inference,and a fast gradient descent algorithm for learning in this model. The objective drives the metric to establish neighborhood boundaries that benefit the true class labels for the training points. Our approach, reminiscent of gerrymandering (redrawing of political boundaries to provide advantage to certain parties), is more direct in its handling of optimizing classification accuracy than those previously proposed. In experiments on a variety of data sets our method is shown to achieve excellent results compared to current state of the art in metric learning.
Most stuff here is just raw unstructured text data, if you are looking for annotated corpora or Treebanks refer to the sources at the bottom. Blog Authorship Corpus: consists of the collected posts of 19,320 bloggers gathered from blogger.com in August 2004. Amazon Fine Food Reviews [Kaggle]: consists of 568,454 food reviews Amazon users left up to October 2012. ASAP Automated Essay Scoring [Kaggle]: For this competition, there are eight essay sets. Each of the sets of essays was generated from a single prompt.
This included the technology ProFound AI for Digital Breast Tomosynthesis (DBT), which is said to be the first artificial intelligence software for DBT to be approved by the U.S. Food and Drug Administration (FDA). Also on offer at the event were medical software solutions designed for 2D mammography and to assess breast density. During the meeting, the iCAD unveiled its vision for future technologies. This predictive aspect included technologies that should enable clinicians to more easily interpret patients' earlier images and prospective breast cancer risk assessment to form a clearer picture of the specific patient's condition. Clinical data from a large reader study involving ProFound AI for DBT were recently published in the journal Radiology: Artificial Intelligence ("Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis").
Facial recognition technology has advanced swiftly in the last five years. As University of Texas at Dallas researchers try to determine how computers have gotten as good as people at the task, they are also shedding light on how the human brain sorts information. UT Dallas scientists have analyzed the performance of the latest echelon of facial recognition algorithms, revealing the surprising way these programs -- which are based on machine learning -- work. Their study, published online Nov. 12 in Nature Machine Intelligence, shows that these sophisticated computer programs -- called deep convolutional neural networks (DCNNs) -- figured out how to identify faces differently than the researchers expected. "For the last 30 years, people have presumed that computer-based visual systems get rid of all the image-specific information -- angle, lighting, expression and so on," said Dr. Alice O'Toole, senior author of the study and the Aage and Margareta Møller Professor in the School of Behavioral and Brain Sciences.