The emerge of new technologies to synthesize and analyze big data with high-performance computing, has increased our capacity to more accurately predict crop yields. Recent research has shown that Machine learning (ML) can provide reasonable predictions, faster, and with higher flexibility compared to simulation crop modeling. The earlier the prediction during the growing season the better, but this has not been thoroughly investigated as previous studies considered all data available to predict yields. This paper provides a machine learning based framework to forecast corn yields in three US Corn Belt states (Illinois, Indiana, and Iowa) considering complete and partial in-season weather knowledge. Several ensemble models are designed using blocked sequential procedure to generate out-of-bag predictions. The forecasts are made in county-level scale and aggregated for agricultural district, and state level scales. Results show that ensemble models based on weighted average of the base learners outperform individual models. Specifically, the proposed ensemble model could achieve best prediction accuracy (RRMSE of 7.8%) and least mean bias error (-6.06 bu/acre) compared to other developed models. Comparing our proposed model forecasts with the literature demonstrates the superiority of forecasts made by our proposed ensemble model. Results from the scenario of having partial in-season weather knowledge reveal that decent yield forecasts can be made as early as June 1st. To find the marginal effect of each input feature on the forecasts made by the proposed ensemble model, a methodology is suggested that is the basis for finding feature importance for the ensemble model. The findings suggest that weather features corresponding to weather in weeks 18-24 (May 1st to June 1st) are the most important input features.

Cybersecurity attacks are growing both in frequency and sophistication over the years. This increasing sophistication and complexity call for more advancement and continuous innovation in defensive strategies. Traditional methods of intrusion detection and deep packet inspection, while still largely used and recommended, are no longer sufficient to meet the demands of growing security threats. As computing power increases and cost drops, Machine Learning is seen as an alternative method or an additional mechanism to defend against malwares, botnets, and other attacks. This paper explores Machine Learning as a viable solution by examining its capabilities to classify malicious traffic in a network. First, a strong data analysis is performed resulting in 22 extracted features from the initial Netflow datasets. All these features are then compared with one another through a feature selection process. Then, our approach analyzes five different machine learning algorithms against NetFlow dataset containing common botnets. The Random Forest Classifier succeeds in detecting more than 95% of the botnets in 8 out of 13 scenarios and more than 55% in the most difficult datasets. Finally, insight is given to improve and generalize the results, especially through a bootstrapping technique.

Find here a listing of the latest industry news in genomics, genetics, precision medicine, and beyond. Updates are provided on a monthly basis. Sign-Up for our newsletter and never miss out on the latest news and updates. As 2019 came to an end, Veritas Genetics struggled to get funding due to concerns it had previously taken money from China. It was forced to cease US operations and is in talks with potential buyers. The GenomeAsia 100K Project announced its pilot phase with hopes to tackle the underrepresentation of non-Europeans in human genetic studies and enable genetic discoveries across Asia. Veritas Genetics, the start-up that can sequence a human genome for less than $600, ceases US operations and is in talks with potential buyers Veritas Genetics ceases US operations but will continue Veritas Europe and Latin America. It had trouble raising funding due to previous China investments and is looking to be acquired. Illumina loses DNA sequencing patents The European Patent ...

Companies are starting to see a few benefits from artificial intelligence, but there are still many roadblocks to progress. In Living in an AI World: Achievements and Challenges of Artificial Intelligence Across Five Industries, KPMG looks at what's working and what isn't in five industries. The report explores how leaders in healthcare, financial services, transportation, technology, and retail are using artificial intelligence (AI) to change operations and workflows. Two findings were not a surprise. A majority of leaders in four of the five industries report that AI is overhyped, ranging from 57% of tech leaders and going up to 69% among transportation industry leaders.

A briefing from the European Parliament [1] provides accessible introductions to some of the key techniques that come under the Artificial Intelligence banner, grouped into three sections to give a sense the chronology of its development. The first describes early techniques, described as'symbolic AI' while the second focuses on the'data driven' approaches that currently dominate, and the third looks towards possible future developments. By explaining what is'deep' about deep learning and showing that AI is more maths than magic, the briefing aims to equip the reader with the understanding they need to engage in clear-headed reflection about AI's opportunities and challenges. In 2019, community groups, researchers, policymakers, and workers demanded a halt to risky and dangerous AI. AI Now's 2019 report [2] spotlights these growing movements, examining the coalitions involved and the research, arguments, and tactics used.

Federal agencies and the private sector would have new guidelines for developing artificial intelligence technologies, such as AI-powered medical devices and autonomous vehicles and drones, under a draft set of principles from the Trump administration. The 10 principles released Tuesday by the White House Office of Science and Technology Policy would direct federal agencies to develop consistent policies on AI technology, including soliciting public engagement from academics, nonprofits, industry and civil society, while also ensuring the products are safe for the public and don't discriminate. "We believe that consistency is really, really important and it sends a very important and very powerful message to industry so that they actually have clarity on the way that they should be thinking about bringing forth products which fall under some sort of regulatory oversight," Michael Kratsios, U.S. chief technology officer, said on a press call yesterday. "With this consistency, we think we can spur greater innovation around the country, and we can also help all of our regulators across all of our agencies be more consistent and be more aware of what they need to do to promulgate regulations at a good clip and speed," Kratsios added. Kratsios and Lynne Parker, the U.S. deputy chief technology officer, are expected to speak further about the the AI regulatory principles during separate panels on Wednesday at CES, the year's largest tech show, taking place in Las Vegas.

A few months after taking part in Tampa Bay Wave's TechDiversity accelerator, TheIncLab has established an office in Ybor City. The company, headquartered in Washington, D.C. and with an office in Nashville, develops artificial intelligence-based systems designed to learn and collaborate with humans. On Monday, the company moved into The Undercroft, a cybersecurity guild and development center in Ybor City. Local civic, business and government leaders have been pushing to grow the technology sector, so the TheIncLab's decision to open an office here comes as welcome news. "TheIncLab's announcement is further proof that Tampa's reputation as a rising tech market is gaining national attention and attracting some really innovative companies," said Marie Chinnici-Everitt, managing director of The Depository Trust & Clearing Corp. and chair of the Tampa Bay Economic Development Council.

The Pentagon's nascent center devoted to artificial intelligence research and development wants to learn more about people's perceptions of the budding technology. According to a proposed information collection notice published in the Federal Register Thursday, the Defense Department's Joint Artificial Intelligence Center is funding a RAND Corporation-led study "exploring civil-military views regarding AI and related technologies." "This data collection will help ensure [Defense's] ability to engage with leading private sector technology corporations and their employees," officials said in the notice. As is standard with federal information collections, the Pentagon must engage public feedback on whether it is necessary before the study is conducted. Defense will accept comments until March 16 on that specific matter.

Last year, communities banded together to prove that they can--and will--defend their privacy rights. As part of ACLU-led campaigns, three California cities--San Francisco, Berkeley, and Oakland--as well as three Massachusetts municipalities--Somerville, Northhampton, and Brookline--banned the government's use of face recognition from their communities. Following another ACLU effort, the state of California blocked police body cam use of the technology, forcing San Diego's police department to shutter its massive face surveillance flop. And in New York City, tenants successfully fended off their landlord's efforts to install face surveillance. Even the private sector demonstrated it had a responsibility to act in the face of the growing threat of face surveillance.

US politicians expressed concerns about the accuracy and growing use of facial recognition software, at a hearing on Wednesday. The technology is being developed by firms including Amazon and Microsoft and increasingly used by law enforcement worldwide. Civil liberties and privacy groups have raised concerns about how the data for these programs is being gathered. "This is some real-life Black Mirror stuff that we're seeing here," said New York congresswoman Alexandria Ocasio-Cortez, a reference to a science-fiction TV show that explores the dark side of technology. US lawmakers are working on a proposal for a bill to limit the use of facial recognition.