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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


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


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?


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


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


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?

VIDEO: Artificial Intelligence makes Einstein 'talk' again


The UneeQ, based in the United States and New Zealand, published a video of its artificial intelligence project Digital Einstein that has the father of relativity theory chat with a fictional version of his human Sofia. Users of UneeQ technology will be able to chat with the iconic Nobel Prize in Physics, who will answer their questions. The idea of this long-term project is to teach and accompany people who feel lonely, especially seeing the effects of quarantines around the world due to the COVID-19 pandemic. The company said in a statement that "Digital Einstein, among other digital humans, can communicate with people in a more natural way: using conversation, human expressions and emotional responses to provide the best daily interactions that we hope will make a difference in people's lives ".

Principal Component Analysis


"Machine intelligence is the last invention that humanity will ever need to make". The quote definitely makes it clear that machine learning is the future and vast opportunities and benefits for all. Let this be a fresh start for you to learn a really interesting algorithm in machine learning. As you all know, we often come across the problems of storing and processing huge data in machine learning tasks, as it's a time-consuming process and difficulties to interpret also arises. Not every feature of the data is necessary for predictions.

Can Artificial Intelligence Give Us Equal Justice?


It's "misleading and counterproductive" to block the use of machine-learning algorithms in the justice system on the grounds that some of them may be subject to racial bias, according to a forthcoming study in the American Criminal Law Review. The use of artificial intelligence by judges, prosecutors, police and other justice authorities remains "the best means to overcome the pervasive bias and discrimination that exists in all parts of the deeply flawed criminal justice system," said the study. Algorithmic systems are used in a variety of ways in the U.S. justice system in practices ranging from identifying and predicting crime "hot spots" to real-time surveillance. More than 60 kinds of risk assessment tools are currently in use by court systems around the country, usually to weigh whether individuals should be held in detention before trial or can be released on their own recognizance. The risk assessment tools, which assign weights to data points such as previous arrests and the age of the offender, have come under fire from activists, judges, prosecutors, and some criminologists who say they are susceptible to bias themselves.

Tesla drives on Autopilot through a regulatory gray zone

The Japan Times

BERKELEY, California – The fatal crash of a Tesla with no one apparently behind the wheel has cast a new light on the safety of semiautonomous vehicles and the nebulous U.S. regulatory terrain they navigate. Police in Harris County, Texas, said a Tesla Model S smashed into a tree on Saturday at high speed after failing to negotiate a bend and burst into flames, killing one occupant found in the front passenger seat and the owner in the back seat. Tesla Chief Executive Elon Musk tweeted on Monday that preliminary data downloaded by Tesla indicate the vehicle was not operating on Autopilot, and was not part of the automaker's "Full Self-Driving" (FSD) system. Tesla's Autopilot and FSD, as well as the growing number of similar semi-autonomous driving functions in cars made by other automakers, present a challenge to officials responsible for motor vehicle and highway safety. U.S. federal road safety authority, the National Highway Traffic Safety Administration (NHTSA), has yet to issue specific regulations or performance standards for semi-autonomous systems such as Autopilot, or fully autonomous vehicles (AVs).