Symbolic AI algorithms have played an important role in AI's history, but they face challenges in learning on their own. After IBM Watson used symbolic reasoning to beat Brad Rutter and Ken Jennings at Jeopardy in 2011, the technology has been eclipsed by neural networks trained by deep learning. The power of neural networks is that they help automate the process of generating models of the world. This has led to several significant milestones in artificial intelligence, giving rise to deep learning models that, for example, could beat humans in progressively complex games, including Go and StarCraft. But it can be challenging to reuse these deep learning models or extend them to new domains.

Section 101 states "[w]hoever invents or discovers…may obtain a patent therefore…" According to 35 U.S.C. § 100, an inventor is defined as an individual or individuals. As technology has advanced and the possibility that AI would invent something became a probability, the question has arisen whether AI can be an inventor under United States law.

Six Army soldiers who were injured in a ballistic missile attack in Iraq in January have been awarded Purple Hearts, and 23 others have been approved for the award and will get them later this week, U.S. Central Command said Monday. Bill Urban said the awards were approved by Lt. Gen. Pat White, the top U.S. commander in Iraq, following a review. About 110 U.S. service members were diagnosed with traumatic brain injuries after the Iranian ballistic missile attack at al-Asad Air Base in Iraq on Jan. 8. More than a dozen missiles struck the base in an attack that Iran carried out as retaliation for a U.S. drone strike in Baghdad that killed Tehran's most powerful general, Qassem Soleimani, on Jan. 3. Troops at al-Asad were warned of an incoming attack, and most were in bunkers scattered around the base. Initially, commanders and President Donald Trump said there were no injuries during the attack.

Leesman hopes that in coaching Team Liquid, he can translate formative life experiences across esports and traditional sports into competitive success. Growing up in Cranbrook, British Columbia, Leesman was (and still is) an avid NBA and NFL fan, spending four years in high school quarterbacking the local under-18 Rocky Mountain Rams football team and then staying on for a year as their offensive coordinator. He idolizes Phil Jackson, especially the way Jackson would often refuse to call timeouts when his teams were struggling, preferring to let them learn how to execute and escape adversity in the moment. With no timeouts during a League of Legends game, Leesman believes proper preparation is essential to impactful coaching.

The apartment complexes near Western Kentucky University sued the United States Postal Service and a postmaster in January after the agency began delivering mail in bulk to property management offices instead of tenants' mailboxes. The change came after the Postal Service reclassified the residences as dormitories, according to the lawsuit.

An anti-Trump political organization is using AI originally designed to tackle Islamic State propaganda to counter coronavirus disinformation spread by the president. The system has been repurposed to spot comments from Trump that are about to go viral. It will then identify the most popular counter-narratives, and invite a network of more than 3.4 million influencers "to share these highly visual and emotional narratives from real people in unison and at scale." The initiative is being led by Defeat Disinfo, a political action committee (PAC) advised by retired general Stanley McChrystal, who commanded US and NATO forces during the Afghanistan war. The PAC claims that it won't use any bots, sock puppets, or false information.

This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist.

One evening last October, the artificial intelligence researcher Gary Marcus was amusing himself on his iPhone by making a state-of-the-art neural network look stupid. Marcus' target, a deep learning network called GPT-2, had recently become famous for its uncanny ability to generate plausible-sounding English prose with just a sentence or two of prompting. When journalists at The Guardian fed it text from a report on Brexit, GPT-2 wrote entire newspaper-style paragraphs, complete with convincing political and geographic references. Marcus, a prominent critic of AI hype, gave the neural network a pop quiz. Surely a system smart enough to contribute to The New Yorker would have no trouble completing the sentence with the obvious word, "fire."

For this episode, we have the pleasure to have a thought leader in the data and analytics space, Felix Liao, with us to share some latest trends and amazing insights into the present and future of data science, machine learning, and AI. Felix is the Head of AI/ML and Analytics Platform for SAS Australia/New Zealand. He has been working with SAS for over 10 years now and has worked in positions of Business Solution Manager – Data Visualisation and Big Data Analytics and Business Solution Manager – Information Management and Big Data before becoming the head of AI/ML and analytics platform. SAS is a global leader in business analytics software and services, and one of the largest independent vendors in the data science and business intelligence market. What gives Felix an added edge as an expert in the field of data technologies, is his unique mix of knowledge.

The Coronavirus Disease 2019 (COVID-19) pandemic has caused extreme strains on health systems, public health infrastructure, and economies of many countries. As of April 2020, millions of people have been infected, and more than two billion globally are staying home to avoid coronavirus. This raging pandemic continues to disrupt our lives while the scientific community is rushing to find a cure for COVID-19. We can leverage artificial intelligence (AI) and big data to help combat the COVID-19 pandemic. For example, ongoing AI efforts aim to expedite the development of a safe and effective COVID-19 vaccine, use networks to repurpose drugs for COVID-19, predict antibacterial properties of new molecules, and design machine-readable datasets of scientific literature on the novel coronavirus.