In the post-pandemic, post-Brexit world, businesses of all sorts face a range of new challenges – and many will be wondering if AI-based automation could help them win through. From adding more self-service capabilities for hotel guests through modernising e-commerce fulfilment to replacing missing workers in farming, the opportunities are many, but so are the pitfalls. Given all this, some research that we carried out last year on attitudes to AI – and in particular its subset, machine learning (ML) – is looking even more relevant now than it was then. It gives a picture not just of where AI could add value, but of key routes to get there and of hurdles that must be overcome along the way. As well as asking how our respondents perceived AI and ML, and hearing a lot of weariness with the noise and hype, we asked how well their organisations understood "the AI imperative".
Nearly three-quarters of businesses now consider artificial intelligence (AI) critical to their success, and AI continues to grow in importance across companies of various sizes and industries, according to a new report. And despite turbulent times, more than two-thirds of respondents to Appen Limited's 2020 State of AI Report do not expect any negative impact from the COVID-19 pandemic on their AI strategies. Nearly half of companies have accelerated their AI strategies, 20% doing so "significantly," betting their AI projects will have a positive impact on their organization's resiliency, efficiency, and innovation, according to the annual report. SEE: Managing AI and ML in the enterprise 2020: Tech leaders increase project development and implementation (TechRepublic Premium) Yet almost half (49%) of respondents feel their company is behind in their AI journey, suggesting a critical gap exists between the strategic need and the ability to execute among business leaders and technologists, Appen said. Surprisingly, respondents are not that leery of AI: The report also found that only 25% of companies said unbiased AI is mission-critical.
California is one of the hardest-hit states when it comes to coronavirus with more than 200,000 total cases. Data scientists seeking ways to help the state reopen the economy participated in a two-week 2020 COVID-19 Computational Challenge (CCC) in mid-June. The challenge was to provide guidance for risk mitigation for Los Angeles County. Additionally, the solution "must incorporate the ethical protection of individual data and respect data privacy norms." The winning teams revealed location-based COVID-19 exposure at different L.A. communities, developed apps for people to calculate their potential for infection, and delivered applicable data-driven recommendations along with L.A.'s reopening stages, officials said.
These are the lecture notes for FAU's YouTube Lecture "Deep Learning". This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. If you spot mistakes, please let us know!
New research in Scientific Reports conducted by Washington University shows how comprehending brain activity as a network rather than by electroencephalography readings, provides more accurate identification of epileptic seizures in real-time. The study, which mixes machine learning with systems theory, was steered by lead author Walter Bomela. "Our technique allows us to get raw data, process it and extract a feature that's more informative for the machine learning model to use," Bomela stated in a news release. "The major advantage of our approach is to fuse signals from 23 electrodes to one parameter that can be efficiently processed with much less computing resources." As explained by researchers, using an EEG, epileptic seizures can be observed through irregular brain activity in the form of spikes and waves during the measurement of electrical output.
Before diving into Artificial Intelligence's future, Let's have a look at what is Artificial Intelligence. Artificial Intelligence is a machine Intelligence. In contrast with natural intelligence, machine intelligence is more accurate and efficient because it demonstrated by machines, not by humans or animals. Today, AI properly knowns as narrow AI (or weak AI), just because of designed it for narrow tasks. But, for a long-term goal, many researchers go for general AI (AGI or strong AI).
A smartphone that can warn you not to send a text while you're upset? Early in my career--back in the stone age before computers and smartphones--I worked in environments where memos were a primary means of communication. Sure, my colleagues and I could talk face-to-face, but the culture of the time was to memorialize much of our interaction in writing. Believe it or not, there were some advantages in what now seems such an archaic practice. Unlike texts and emails--where one tap of the "send" button can fill you with instant regret--the old-fashioned memo provided a cushion of safety, a chance to reconsider.
Fraym is using artificial intelligence and machine learning to help aid organizations in Africa and South Asia identify populations at risk due to Covid-19 using new geospatial visualizations. Fraym identifies high-risk populations and how to best communicate with them – making it an invaluable tool for more than 40 organizations and governments fighting the pandemic, including the Nigerian CDC, Kenyan presidential office, Zambian public health policymakers and aid organizations in Pakistan. Fraym has mapped communities based on concentrations of common transmission variables and then combined this with data from household surveys and remote sensing data, to then understand how these individuals consume news at a hyper-local level. The company is providing this information, which is at a 1-square kilometer level, for free to help fight the spread of Covid19. Since March 2020, Fraym has produced more than 300 COVID-19 related data layers in nearly 20 different countries.