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Global Big Data Conference

#artificialintelligence

Artificial intelligence is no longer the domain of Hollywood technothrillers, nor is it available only to the Fortune 500 or VC-backed startups. In fact, use of the technology has become increasingly common at companies of all sizes. IBM describes artificial intelligence (AI) as technology that "leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind." But today, even small- and mid-sized companies can leverage AI by tapping into customer, product and market data to power their analytics, reduce their time-to-market and help get a leg up on their competition. Data makes an application of AI like machine learning (ML) possible.


The perfect storm striking World of Warcraft

BBC News

Scott Johnson has been making WoW content online since 2004. He says he chaired a panel at Blizzard's annual fan festival in 2018 with one of the people named in the allegations - something he now sees in a new light. As someone who plays an active role in the community, he says he personally knows some of the women who were victims.


NotCo gets its horn following $235M round to expand plant-based food products – TechCrunch

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NotCo, a food technology company making plant-based milk and meat replacements, wrapped up another funding round this year, a $235 million Series D round that gives it a $1.5 billion valuation. Tiger Global led the round and was joined by new investors, including DFJ Growth Fund, the social impact foundation, ZOMA Lab; athletes Lewis Hamilton and Roger Federer; and musician and DJ Questlove. Follow-on investors included Bezos Expeditions, Enlightened Hospitality Investments, Future Positive, L Catterton, Kaszek Ventures, SOSV and Endeavour Catalyst. This funding round follows an undisclosed investment in June from Shake Shack founder Danny Meyer through his firm EHI. In total, NotCo, with roots in both Chile and New York, has raised more than $350 million, founder and CEO Matias Muchnick told TechCrunch.


Segmentation of Bone with Region Based Active Contour Model in PD Weighted MR Images of Shoulder - PubMed

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Proton density (PD) weighted MR images present inhomogeneity problem, low signal to noise ratio (SNR) and cannot define bone borders clearly. Segmentation of PD weighted images is hampered with these properties of PD weighted images which even limit the visual inspection. The purpose of this study is to determine the effectiveness of segmentation of humeral head from axial PD MR images with active contour without edge (ACWE) model. We included 219 images from our original data set. We extended the use of speckle reducing anisotropic diffusion (SRAD) in PD MR images by estimation of standard deviation of noise (SDN) from ROI.


How robot carpenters could help solve Canada's housing crisis

#artificialintelligence

Promise Robotics CEO Ramtin Attar with a few Kuka Industrial robots similar to ones fitted with custom tooling developed by Promise Robotics to perform complex construction tasks. Robots constructing homes may sound like science fiction. Yet a Toronto-based startup aims to make this futuristic idea a reality within the next year, leveraging advances in automation, advanced manufacturing, cloud computing and artificial intelligence (AI). Promise Robotics was launched in 2019 by founders Ramtin Attar – a former technology lead at a multinational technology company – and Reza Nasseri, the chief executive officer of Landmark Homes. The technology company, which also has operations in Edmonton, seeks to bring emerging technologies to the home building industry to address the industry's biggest challenge: meeting the rising demand for housing amid a growing shortage of affordable homes.


AI vendors must offer more solutions for niche use cases

#artificialintelligence

All the sessions from Transform 2021 are available on-demand now. Most AI vendors develop solutions that target broad use cases with large markets. This is because investors have shown they are only interested in a target market if it is worth several billion dollars. Therefore smaller markets have been excluded, and AI solution ideas designed for niche markets often die out and the companies behind them come to a standstill before they have the chance to see the light of day. Another side effect of the limited capital to build niche models is that AI vendors tend to build one model and market it to a large set of disparate users.


Artificial Intelligence Helps Resolve Long-Running Astrophysics Debate on Supermassive Black Holes

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An image of Messier 101, the Pinwheel Galaxy, made with the Hubble Space Telescope. The bright blue clumps in the spiral arms are sites of recent star formation. Black holes with masses equivalent to millions of suns do put a brake on the birth of new stars, say astronomers. Using machine learning and three state-of-the-art simulations to back up results from a large sky survey, the researchers resolve a 20-year long debate on the formation of stars. Joanna Piotrowska, a PhD student at the University of Cambridge, presented the new work on July 20, 2021, at the virtual National Astronomy Meeting (NAM 2021).


Deep learning and liver disease

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Many medical imaging techniques have played a pivotal role in the early detection, diagnosis, and treatment of diseases, such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission tomography (PET), mammography, and X-ray. AI has made significant progress which allows machines to automatically represent and explain complicated data. It is widely applied in the medical field, especially in some domains that need imaging data analysis. According to Vivantil et al by using deep learning models based on longitudinal liver CT studies, new liver tumours could be detected automatically with a true positive rate of 86%, while the stand-alone detection rate was only 72% and this method achieved a precision of 87% and an improvement of 39% over the traditional SVM mode. CNN models which use ultrasound images to detect liver lesions were also developed. According to Liu et al by using a CNN model based on liver ultrasound images, the proposed method can effectively extract the liver capsules and accurately diagnose liver cirrhosis, with the diagnostic AUC being able to reach 0.968.


Getting familiar with Rmarkdown Stargazer

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Happiness in the present is only shattered by comparison with the past. Regression analysis does not require any separate introduction today. In fact, it would be hard to find a field of study that can put a bet and win for not using this technique at least once in their life cycle. There exists a relationship, waiting to be explored by someone through some variant of regression technique. Ever since mathematicians Adrien-Marie Legendre and Carl Friedrich Gauss invented this technique in the early 19th century, the world has been experiencing at least one use case every day; by some human being alive in the world.


Linear Predictive Models

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Welcome readers to Part 2 of the Linear predictive model series. If you haven't read Part 1 of this series, you can read that here: As a quick recap, in part 1 we obtained our data by web scraping AutoScout24 and obtained the dataset of car sales in Germany. Next, we cleaned and prepared the data for a preliminary Exploratory data analysis. Then we began with our modeling and used several Regression models like Linear regression with and without regularization, Linear regression with Regu, Pipeline, Cross Val Predict, and lastly with Polynomial regularization. Regression analysis can be described as a way of predicting the future of a dependable (target) variable use single or multiple independent variables(also known as predictors).