Democratic Congresswoman Ilhan Omar faces condemnation over her'some people did something' comments; reaction from Fox News contributor Ari Fleischer, former White House contributor. Rep. Ilhan Omar, D-Minn, blasted President Trump over his handling of Iran and suggested that his administration is to blame over the increased tensions between the two nations. Over the weekend, Iran-backed Houthi rebels claimed they launched drone attacks on the world's largest oil processing facility in Saudi Arabia and a major oil field Saturday, sparking huge fires and halting about half of the supplies from the world's largest exporter of oil. The attacks marked the latest of many drone assaults on the Kingdom's oil infrastructure in recent weeks, but easily the most damaging. They raised concerns about the global oil supply and could further escalate tensions across the Persian Gulf amid a growing crisis between the U.S. and Iran over the troubled nuclear deal.
Repeat after me: Machines are our friends; they're with us till the end! There, now doesn't that feel better? Oh, sure, the "narrative" says that machines will take jobs away from humans, but that's only somewhat true. Mostly, the machines of tomorrow will do what they've always done: streamline and expedite workflow across the spectrum of business processes. Keep in mind, the cotton gin eradicated thousands of jobs all over the Southern United States (and elsewhere), back when it stormed the market in the 1800s.
Without the software that powers them, iPhones and Android phones would be high-priced pieces of glass, metal and plastic. So let's see how the new mobile OSes from Apple and Google compare. On one side of the table, iOS 13 includes a systemwide dark mode, more control over privacy settings and a bushel of improvements designed to make the iPhone more secure and easier to use. On the other side, Google's Android 10 also brings on dark mode, a focus on privacy and useful AI enhancements. With the iPhone 11, 11 Pro and 11 Max Pro just announced, we'll soon see this the new iOS software absorbed into hardware.
Training and inference using ee.Classifier or ee.Clusterer is generally effective up to a request size of approximately 100 megabytes. This is only an approximate guideline due to additional overhead around the request, but note that for b 100 (i.e. Since Earth Engine processes 256x256 image tiles, inference requests on imagery must have b 400 (again assuming 32-bit precision of the imagery). Examples of machine learning using the Earth Engine API can be found on the Supervised Classification page or the Unsupervised Classification page. Regression is generally performed with an ee.Reducer as described on this page, but see also ee.Reducer.RidgeRegression.
Last year, Reuters broke the news that Amazon had been working on a secret AI recruiting tool that showed bias against women. I found it interesting as a case study of an AI project with broad implications for business people and machine learning professionals. After all, everyone has either hired or been hired at least once. We all have a stake in the recruiting game. Sadly, most reporting was sensationalist trash, and the news cycle quickly moved on. It seems nobody tried to answer the question of how a company of the caliber of Amazon -- with seemingly infinite resources -- could stumble so badly. Is AI technology inherently evil? Are all software engineers and data scientists sexist brutes? Is the technology too immature for complex business problems? Or is there something specific about AI projects that makes them difficult -- even for the best companies? The Reuter article was widely circulated and became a prime example of the pitfalls of AI projects.
Machine learning is a term we hear all the time. "Everyone loves it -- machine learning is everyone's BFF these days," says Avinash Kaushik, who leads a team of analysts in Google's marketing department. But putting all the hype aside, can the latest marketing trend actually help companies achieve important business goals?
Artificial intelligence (AI) and automation more broadly continue to be identified as the next frontier in productivity enhancement and growth. Last year, McKinsey estimated AI could potentially increase economic outputs by $13 trillion by 2030, and add to global GDP by approximately 1.2%. Consistent with the trend, it is likely that Australian boards will increasingly look to AI and machine learning to improve the quality of their decision making. But can an algorithm run a company instead of a director? The term'AI' is often used synonymously with machine learning, but this is not strictly correct.
Recently no day goes by without a publication of a new outstanding machine learning application, most likely powered by some deep learning model. At the latest when it supports critical decision-making, you should think about the degree of certainty that comes with every prediction. We will go through why that is, how to define uncertainty and eventually look at some code examples so that you will be able to apply our findings in your next project. Let's do a thought experiment. Imagine you're a company that organizes safaris, and you want to create a safer experience for clients in their adventures.
Robotic Process Automation (RPA) is at the peak of inflated expectation cycle, says Gartner. They estimate by 2022, 85% of large and very large organizations would have deployed some form of RPA solutions to automate their business. Overall, the global Robotic Process Automation software spend is expected to reach $2.4 billion in 2022. Robotic Process Automation today is mainstream with increasing adoption across industries. More so in Insurance Industry, where technology advancement has been moving at a snails' pace.
A local defense company hopes artificial intelligence can help stop mass shootings. Training started on Saturday, all with the goal of eventually saving lives. The training was as realistic as possible and put on by the security company Defendry. A host of actors came together to replicate a scene where an active shooter comes toward them. Recordings of the drill will be marked down and uploaded to program artificial intelligence; all to develop a system that spots a gunman before any shots ring out.