Goto

Collaborating Authors

application


Williams F1 drives digital transformation in racing with AI, quantum

#artificialintelligence

"The thing that really attracted me to Formula 1 is that it's always been about data and technology," says Graeme Hackland, Williams Group IT director and chief information officer of Williams Racing. Since joining the motorsport racing team in 2014, Hackland has been putting that theory into practice. He is pursuing what he refers to as a data-led digital transformation agenda that helps the organization's designers and engineers create a potential competitive advantage for the team's drivers on race day. Hackland explains to VentureBeat how Williams F1 is looking to exploit data to make further advances up the grid and how emerging technologies, such as artificial intelligence (AI) and quantum computing, might help in that process. This interview has been edited for clarity.


Global Economic Impact of AI: Facts and Figures

#artificialintelligence

Wall Street, venture capitalists, technology executives, data scientists -- all have important reasons to understand the growth and opportunity in the artificial intelligence market to access business growth and opportunities. This gives them insights on funds invested in AI and analytics as well potential revenue growth and turnover. Indeed, the growth of AI, continuing research, development of easier open source libraries and applications in small to large scale industries are sure to revolutionize the industry the next two decades and the impact is getting felt in almost all the countries worldwide. To dive deep into the growth of AI and future trends, an insight into the type and size of the market is essential along with (a) AI-related industry market research forecasts and (b) data from reputable research sources for insight into AI valuation and forecasting. IBM's CEO claims a potential $2 trillion dollar market for "cognitive computing").


Use of Artificial Intelligence in the Making of Hearing Aids

#artificialintelligence

Applications of artificial intelligence are growing every day in different sectors. There are numerous instances of AI applications in healthcare. The AI that occurs in hearing aids has actually been going on for years and the following is about how it happened. Hearing aids used to be relatively simple, he notes, but when hearing aids introduced a technology known as wide dynamic range compression (WDRC), the devices actually began to make a few decisions based on what is heard. For hearing aids to work effectively, they need to adapt to a person's individual hearing needs as well as all sorts of background noise environments. AI, machine learning, and neural networks are very good techniques to deal with such a complicated, nonlinear, multi-variable problem.


£36 million funding for AI technologies - htn

#artificialintelligence

The Department of Health and Social Care has announced a £36 million increase in funding for AI technology-based healthcare services and products. Sir Simon Stevens, Chief Executive of NHS England, said: "Through our NHS AI Lab we're now backing a new generation of groundbreaking but practical solutions to some of the biggest challenges in healthcare. Precision cancer diagnosis, accurate surgery, and new ways of offering mental health support are just a few of the promising real-world patient benefits. Because as the NHS comes through the pandemic, rather than a return to old ways, we're supercharging a more innovative future." "So today our message to developers worldwide is clear – the NHS is ready to help you test your innovations and ensure our patients are among the first in the world to benefit from new AI technologies."


NHS to receive £36m injection for AI tech in national health bounce back - CityAM

#artificialintelligence

The NHS is set to receive a £36m injection to bolster its AI capabilities across 38 new projects designed to make diagnoses faster. While the NHS has been handling the Covid-19 pandemic, concerns over a diagnoses backlog have emerged, with people more hesitant to go to the GP or hospital for check-ups. The new technology will help detect cancers and provide mental health support and form part of the NHS AI Lab's £140m AI in Health and Care award money pot – which will be dished out over three years. Chief executive of NHS England, Simon Stevens, said: "As the NHS comes through the pandemic, rather than a return to old ways, we're supercharging a more innovative future. "So today our message to developers worldwide is clear – the NHS is ready to help you test your innovations and ensure our patients are among the first in the world to benefit from new AI technologies."


Machine Learning Core Repository on GitHub, 4 Application Examples to Try Machine Learning in Sensors in Minutes - ELE Times

#artificialintelligence

ST published its machine learning core repository on GitHub, with examples and configuration files, to vastly improve the developers' experience. Artificial intelligence is notoriously difficult because it relies on data science. Additionally, creating the right algorithm, such as a decision tree, and setting it up, can also be tricky. Unfortunately, all these issues tend to limit the number of engineers that can easily start working on machine learning applications. Hence, we published a repository on GitHub to solve this problem.


China Admits Its Top Air Force Pilots Defeated By 'Adversaries' In Fighter Jet Dogfight

#artificialintelligence

The Chinese PLA Central Theater Command Air Force simulated a dogfight in which a highly experienced pilot was shot down by an artificial intelligence (AI)-driven aircraft. China's state media Global Times cited a report by PLA Daily, Army's official newsletter, on the simulation exercise. It does not mention which aircraft was used in this exercise though. There has been an increasing application of artificial intelligence (AI) and machine learning in military combat training with major powers including the US, China, and Russia joining the race. A mock combat exercise was held in which AI-enabled opponents outperformed many of the PLA Air Force pilots. According to the GT report, China has been investing heavily in AI and machine learning.


Naive Bayes for Data Science -- With Python

#artificialintelligence

There are many solutions proposed for classification purposes. Most of them share one common approach. Calculate the probability that a given sample belongs to a specific class. After that it is more subjective to decide if the given probability is an indication of class membership which is derived by cut-off threshold. This threshold is mainly determined by the utility function or risk-aversion policies.


Applications of conversational AI in retail - AskSid - AskSid

#artificialintelligence

Conversational insights – Natural Language Processing enables conversational AI to be sensitive to conversational behavior, such as the use of emojis, abbreviated forms, or even slang, as well as tonal nuances that could indicate a shift in moods such as a decrease in interest or a sense of frustration. Moreover, the data analyzed by the AI can facilitate not only individual conversations but overall retail decisions. Based on query patterns, the retail brand can identify changes that they might need to make, such as an expanded size range or a more prominent placement of the CTA button. It can also tap into unarticulated demand patterns, enabling the retail brand to address them before customers even express their needs.


The Practicalities of Predicting The Future

#artificialintelligence

So, you think I'm kidding about predicting the future? Predicting the future is not only possible, but even simple, if you stack the probabilities on your side by making precise statements about the object and time of the prediction. Example 1: I predict everyone alive today will die. Certainly, there's a non-zero chance I'm wrong, but historically that seems a pretty safe bet. Example 2: Similarly, I can predict that for the next two seconds, you will continue to read this article, or at least finish this sentence. So clearly you can predict many things as a party trick, by picking the right granularity of events and time horizon for the prediction. The question is, where is the line between what's defensible mathematically, and what's actually new information that's useful? If you're too conservative, you end up with tautologies, i.e. statements that are obviously true but add no value or information besides a tired chuckle from the audience. If you're too aggressive, then you'll end up with highly interesting information that simply has no connection to reality, or at best is just a coin toss, and get dismissed as a charlatan. Is there a sweetspot in between? Well, that's what we're going to find out!