If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The US military has killed senior al Qaeda leader Abdul Hamid al-Matar in a drone strike in Syria, a US Central Command spokesman said. "The removal of this al Qaeda senior leader will disrupt the terrorist organisation's ability to further plot and carry out global attacks threatening US citizens, our partners, and innocent civilians," US Army Major John Rigsbee said in a written statement late on Friday. The strike comes two days after a US outpost in southern Syria was attacked. Rigsbee did not say if the US drone strike was carried out in retaliation of the attack.
As the sports betting industry is gaining steam, I am interested in selling NBA spread picks to sports bettors via subscription to my service. I will use regression models to predict outcomes of NBA games. My goal is to make a prediction on the spreads (point differential) of each game, and use that information to bet against the Vegas spread. Because Vegas typically takes a 10% rake for each bet, I have to be able to beat Vegas 52.5% of the time in order to be profitable. My data was collected via scraping, using Beautiful Soup, basketball-reference.com and sportsbookreviewonline.com, using data from all regular season games from 2011–2020, which includes 11,656 games.
Today's artificial intelligence technology is intended to mimic nature and replicate the same decision-making abilities that people develop naturally in a computer. Artificial neural networks, like living brains, are made up of many individual cells. When a cell becomes active, it transmits a signal to all other cells in the vicinity. The following cell's signals are added together to determine if it will become active as well. The system's behavior is determined by the way one cell influences the activity of the next.
Artificial Intelligence (AI) and machine learning are paving the way in digital marketing at the moment. It is a huge and ever growing technology, which is being recognised now by many large companies. Just last month (September 2021), Oracle Corp incorporated AI into it's digital marketing campaigns in order to qualify their potential leads. Instead of their sales team rifling through thousands of wasted leads, they have employed an AI system which automatically determines whether a person who is interacting with their content (advertisements, emails, social media posts etc), is going to end up being a sale for them. If they are, their contact details will be sent to the sales team.
Artificial Intelligence (AI) has become a major focus of, and the most valuable asset in, many technology transactions and the competition for top AI companies has never been hotter. According to CB Insights, there have been over 1,000 AI acquisitions since 2010. The COVID pandemic interrupted this trajectory, causing acquisitions to fall from 242 in 2019 to 159 in 2020. However, there are signs of a return, with over 90 acquisitions in the AI space as of June 2021 according to the latest CB Insights data. With tech giants helping drive the demand for AI, smaller AI startups are becoming increasingly attractive targets for acquisition. AI companies have their own set of specialized risks that may not be addressed if buyers approach the transaction with their standard process.
Artificial intelligence adoption is increasing in higher education for both academic and research purposes. Too often, though, universities lack the IT infrastructure needed to sustainably power these systems. "To do AI at scale, you need data, but you also need compute power, networking, storage and software," says Cheryl Martin, director of global business development for higher education and research at NVIDIA. "Universities need a platform to bring all those things together." Modern AI requires purpose-built infrastructure that can handle its massively parallel computational demands.
New social audio app Wisdom has launched in the US, UK, Australia and Canada, attempting to "create an inclusive space where diverse people come together to have conversations that matter," according to founder Dayo Akinrinade. Akinrinade said she was inspired by the success of Clubhouse and Tik Tok, which prompted her to create her own platform that could "democratize access to mentorship." "As a Black woman working in London's largest diversity startup program One Tech, I've observed firsthand how lack of access to mentors contributes to systemic inequality," Akinrinade explained to ZDNet. "In addition to this, I observed that would-be mentors on other platforms today have a clear problem: they have no way of engaging the many inbound requests they receive so they ignore them all, unless they get a'warm intro,' which is itself a crystallization of systemic inequality. I created Wisdom to do something about it and democratize access to mentors." Akinrinade envisions the app focusing on conversations around a variety of topics including parenting, fitness, dating, startups, mental health and beauty.
This is the latest in my series of screencasts demonstrating how to use the tidymodels packages. If you are a tidymodels user, either just starting out or someone who has used the packages a lot, we are interested in your feedback on our priorities for 2022. The survey we fielded last year turned out to be very helpful in making decisions, so we would so appreciate your input again! Today's screencast is great for someone just starting out with workflowsets, the tidymodels package for handling multiple preprocessing/modeling combinations at once, with this week's #TidyTuesday dataset on giant pumpkins from competitons. Here is the code I used in the video, for those who prefer reading instead of or in addition to video.
Two experiences of how AI developers within the federal government are pursuing AI accountability practices were outlined at the AI World Government event held virtually and in-person this week in Alexandria, Va. Taka Ariga, chief data scientist and director at the US Government Accountability Office, described an AI accountability framework he uses within his agency and plans to make available to others. And Bryce Goodman, chief strategist for AI and machine learning at the Defense Innovation Unit (DIU), a unit of the Department of Defense founded to help the US military make faster use of emerging commercial technologies, described work in his unit to apply principles of AI development to terminology that an engineer can apply. Ariga, the first chief data scientist appointed to the US Government Accountability Office and director of the GAO's Innovation Lab, discussed an AI Accountability Framework he helped to develop by convening a forum of experts in the government, industry, nonprofits, as well as federal inspector general officials and AI experts. "We are adopting an auditor's perspective on the AI accountability framework," Ariga said.