Goto

Collaborating Authors


Are medical AI devices evaluated appropriately?

#artificialintelligence

In just the last two years, artificial intelligence has become embedded in scores of medical devices that offer advice to ER doctors, cardiologists, oncologists, and countless other health care providers. The Food and Drug Administration has approved at least 130 AI-powered medical devices, half of them in the last year alone, and the numbers are certain to surge far higher in the next few years. Several AI devices aim at spotting and alerting doctors to suspected blood clots in the lungs. Some analyze mammograms and ultrasound images for signs of breast cancer, while others examine brain scans for signs of hemorrhage. Cardiac AI devices can now flag a wide range of hidden heart problems.


When Artificial Intelligence Discriminates

#artificialintelligence

Are machines biased? The FTC has issued Business Guidance about the use of artificial intelligence (AI), warning marketers about the danger of the …


Excellence and trust in artificial intelligence

#artificialintelligence

This is why the European Commission has proposed a set of actions to boost excellence in AI, and rules to ensure that the technology is trustworthy. The Regulation on a European Approach for Artificial Intelligence and the update of the Coordinated Plan on AI will guarantee the safety and fundamental rights of people and businesses, while strengthening investment and innovation across EU countries. Once the AI system is on the market, authorities are in charge of the market surveillance, users ensure human oversight and monitoring, while providers have a post-market monitoring system in place. Providers and users will also report serious incidents and malfunctioning. In 2018, the Commission and EU Member States took the first step by joining forces through a Coordinated Plan on AI that helped lay the ground for national strategies and policy developments.


em Monster Hunter Rise /em Is Infuriating, but I Love It

Slate

Both things can be true: I spent my first three hours playing Monster Hunter Rise screaming, "I hate this game!" at my Nintendo Switch screen. Since then, I have logged more hours in Rise than in any other game this year, and I've successfully convinced several friends to pick the game up as well. For some further context, I'd never played a Monster Hunter game before. I knew that the title did most of the explaining as to what the franchise is about--you hunt big monsters--but that was about it. Rise's debut marks the sixth main Monster Hunter game (the games have been popular enough to spawn several spinoffs, as well as a recent blockbuster adaptation starring Milla Jovovich), but that success has been a mixed blessing, as the series has become notorious for having a steep learning curve.


Fujifilm starts new late-stage trial of Avigan in Japan for COVID-19

The Japan Times

Fujifilm Holdings Corp. said on Wednesday it started a new late-stage trial in Japan of its Avigan drug for COVID-19, reviving hopes for a home-grown treatment for the virus. Domestic approval for the antiviral drug to treat the coronavirus was dealt a setback in December after a health ministry panel said that trial data was inconclusive. Fujifilm has over the years pivoted from its traditional camera and office solutions businesses to health care. The new double-blind, placebo-controlled study is targeting patients aged 50 and older, as well as those at risk of developing serious conditions, Fujifilm said in a release. Avigan, known generically as favipiravir, has been studied in dozens of trials worldwide, and it has been approved as a COVID-19 treatment in Russia, India and Indonesia.


Save on a pair of wireless earbuds with an impressive battery life

Mashable

A pair of affordable, high-quality wireless earbuds can be hard to come by. Most options are either high-quality but way too expensive or affordable but not very durable. The xFyro ANC Pro AI-Powered Wireless Earbuds are a pair of reliable Bluetooth earbuds designed to be your everyday workhorses. You can toggle on active noise cancellation when you need to block out the world around you, or toggle to AI Transparency Mode to stay in tune with your surroundings. The earbuds are also water-resistant, have an ergonomic fit, and feature automatic Bluetooth pairing within 30 feet.


How To Ensure Your Machine Learning Models Aren't Fooled - InformationWeek

#artificialintelligence

All neural networks are susceptible to "adversarial attacks," where an attacker provides an example intended to fool the neural network. Any system that uses a neural network can be exploited. Luckily, there are known techniques that can mitigate or even prevent adversarial attacks completely. The field of adversarial machine learning is growing rapidly as companies realize the dangers of adversarial attacks. We will look at a brief case study of face recognition systems and their potential vulnerabilities.


Companies are Investing in Machine Learning in 2021. Why?

#artificialintelligence

According to reports, machine learning is one of the most sought-after jobs in 2021. Companies have been in high demand for machine learning engineers to build algorithms that can enable business growth and efficiency. Disruptive technology is not a stranger anymore. Companies are pouring money into the development and deployment of cutting-edge technologies and automation. Companies are adopting business intelligence and automation to boost their services and get a deeper insight into the business.


Tilted empirical risk minimization

AIHub

Classical ERM () minimizes the average loss and is shown in pink. As (blue), TERM finds a line of best fit while ignoring outliers. In some applications, these'outliers' may correspond to minority samples that should not be ignored. As (red), TERM recovers the min-max solution, which minimizes the worst loss. This can ensure the model is a reasonable fit for all samples, reducing unfairness related to representation disparity.


[D] Complexity of Time Series Models: ARIMA vs. LSTM

#artificialintelligence

Does this concept of VC Dimension carry over to models in time series analysis? Is it possible to show that LSTM's have a higher VC dimension compared to ARIMA style models? Supposedly, neural network based time series models were developed because modeols like ARIMA was unable to provide reliable estimates for bigger and complex datasets. Mathematically speaking, what allows a LSTM to capture more variation and complexity in a dataset compared to ARIMA? Just as a general question: in what instances would it be better to use a CNN for time series forecasting compared to an LSTM?