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The State of AI in 2021: Language models, healthcare, ethics, and AI agnosticism

#artificialintelligence

AI is expanding in two key areas of human activity and market investment -- health and language. Picking up the conversation from where we left off last week, we discussed AI applications and research in those areas with AI investors and authors of the State of AI 2021 report, Nathan Benaich and Ian Hogarth. After releasing what probably was the most comprehensive report on the State of AI in 2020, Air Street Capital and RAAIS founder Nathan Benaich and AI angel investor and UCL IIPP visiting professor Ian Hogarth are back for more. Last week, we discussed AI's underpinning: Machine learning in production, MLOps, and data-centric AI. This week we elaborate on specific areas of applications, investment, and growth.


Forecasting with Machine Learning Models

#artificialintelligence

TL;DR: We introduce mlforecast, an open source framework from Nixtla that makes the use of machine learning models in time series forecasting tasks fast and easy. It allows you to focus on the model and features instead of implementation details. With mlforecast you can make experiments in an esasier way and it has a built-in backtesting functionality to help you find the best performing model. You can use mlforecast in your own infrastructure or use our fully hosted solution. Just send us a mail to federico@nixtla.io


Best Ethical AI Research for 2021

#artificialintelligence

There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of AI. Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development.



An overview on gradient descent and its variants

#artificialintelligence

The term "optimization" refers to the process of iteratively training a model to produce a maximum and minimum function evaluation to get a minimum cost function. It is crucial since it will assist us in obtaining a model with the least amount of error (as there will be discrepancies between the actual and predicted values). There are various optimization methods; in this article, we'll look at gradient descent and its three forms: batch, stochastic, and mini-batch. Note: Hyperparameter optimization is required to fine-tune the model. Before you begin training the model, you must first specify hyperparameters.


Support vector machines illustrated

#artificialintelligence

Support vector machines are a class of techniques in data science, which had great popularity in the data science community. They are mainly used in classification tasks and perform really well when few training data is available.


Scientists Built an AI to Give Ethical Advice, But It Turned Out Super Racist

#artificialintelligence

Researchers at the Allen Institute for AI created Ask Delphi to make ethical judgments — but it turned out to be awfully bigoted and racist instead.


WWE releases 2022 pay-per-view schedule

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. WWE is ready for 2022. The pro wrestling company released its pay-per-view schedule for the next year with two more shows left on the docket for the year, Survivor Series in November and TLC: Tables Ladders & Chairs in December. MIAMI GARDENS, FL - APRIL 1: John Cena looks on before his match against Dwayne ''The Rock'' Johnson during WrestleMania XXVIII at Sun Life Stadium on April 1, 2012 in Miami Gardens, Florida.


Officials: Iran behind drone attack on US base in Syria

Boston Herald

U.S. officials say they believe Iran was behind the drone attack last week at the military outpost in southern Syria where American troops are based. Officials said Monday the U.S. believes that Iran resourced and encouraged the attack, but that the drones were not launched from Iran. They were Iranian drones, and Iran appears to have facilitated their use, officials said, speaking on condition of anonymity to discuss details that have not been made public. Officials said they believe the attacks involved as many as five drones laden with explosive charges, and that they hit both the U.S. side of al-Tanf garrison and the side where Syrian opposition forces stay. There were no reported injuries or deaths as a result of the attack.


What Is Edge Computing In AI?

#artificialintelligence

What was the motivation for adding voice and image recognition to the iPhone's SoC? If you've ever used Siri, Apple's voice assistant, you may have run into occasional problems where, instead of responding to your command, she says something along the lines of "Please wait a moment..." This is because at present, Siri uses cloud processing of voice data, and if she is unable to connect to Apple's servers through the internet, that's where the party ends. This is due to change very soon however, as this fall's release of iOS 15 will switch Siri to process your voice commands completely on the device itself. Voice assistants such as Siri, Amazon's Alexa, Google Assistant, or Microsoft's Cortana, on-device processing brings a host of benefits: Reduced latency since the data doesn't have to travel over the internet to be processed with wearable technologies Less use of bandwidth which can translate to cheaper internet bills Better privacy as the processing is all done locally and not on someone else's computer The Natural Language Processing (NLP) functionality on these smart assistants are sometimes designed as a hybrid edge and cloud solution known as "fog computing" because it's at the "edge of the cloud". In these systems, they process some data locally and more complex data in the cloud.