Artificial Intelligence (AI) is taking the fast route to modernise society. But how about looking back at some past delights like poetry through AI? Researchers are up to the stage where they want to know how AI performs in understanding and summarizing poems. Poems are a bit complicated even to humans. They are metaphorical, has hidden meanings and representations which a normal person who has an average knowledge about poetry struggles to understand. Putting AI mechanism at the shoes of a poetry fanatic is quite a new establishment.

A few months ago I was at Johns Hopkins University's Applied Physics Lab in suburban Maryland, where I serve as a senior fellow. A group of us -- mostly retired four-star military officers -- were there to witness a computer-simulated dogfight of a unique character: man against machine. I was seated next to retired Admiral John Richardson, who until last fall had been chief of naval operations, the highest-ranking officer in the fleet. We were both skeptical that the artificial intelligence program that would be piloting one of the virtual aircraft would be able to outfight the human pilot, call sign "Banger," from the Air Force's equivalent of the Navy's legendary TOPGUN fighter-tactics instruction program. It was a remarkable blend of software development, AI, modelling and simulation, combat-aircraft dynamics and controls, and advanced video production -- it felt like watching an ESPN sports event.

A social media platform designed for America's military community is now equipped with a custom machine learning model that insiders say can rapidly review public posts and pinpoint those that show signs and risks of potential self-harm. With support from the Veterans Affairs Department and Harvard University's Nock Lab, Amazon Web Services linked up with the existing RallyPoint military social media platform to target the production of a technological solution that can speedily surface sensitive public posts and boost online suicide intervention. "Historically, the heavy lifting of mental health support on RallyPoint has been shouldered by RallyPoint members stepping up to help each other when they come across people sharing their challenges on our site," RallyPoint CEO Dave Gowel recently told Nextgov. "Now, through our work with the VA, AWS and mental health experts from Harvard, we are more proactive in reinforcing our members' good work by offering helpful resources when we are alerted about public posts showing signs of risk." Launched in 2012, RallyPoint enables nearly 2 million service members, veterans, and their families to connect, share stories and information, ask questions and ultimately chat on topics that accompany military and veteran life.

Immigration and Customs Enforcement (ICE) signed a contract with facial recognition company Clearview AI this week for "mission support," government contracting records show (as first spotted by the tech accountability nonprofit Tech Inquiry). The purchase order for $224,000 describes "clearview licenses" and lists "ICE mission support dallas" as the contracting office. ICE is known to use facial recognition technology; last month, The Washington Post reported the agency, along with the FBI, had accessed state drivers' license databases -- a veritable facial recognition gold mine, as the Post termed it -- but without the knowledge or consent of drivers. The agency has been criticized for its practices at the US southern border, which has included separating immigrant children from their families and detaining refugees indefinitely. "Clearview AI's agreement is with Homeland Security Investigations (HSI), which uses our technology for their Child Exploitation Unit and ongoing criminal investigations," Clearview AI CEO Hoan Ton-That said in an emailed statement to The Verge.

China announced new restrictions on artificial-intelligence technology exports that could further complicate the sale of TikTok's U.S. operations, while intensifying the tech battle between the world's two largest economies. The new restrictions, unveiled Friday by China's ministries in charge of commerce and science and technology, cover such computing and data-processing technologies as text analysis, content recommendation, speech modeling and voice-recognition. Technologies on the list can't be exported without a license from local commerce authorities. The new restrictions could throw a wrench into talks between Chinese tech firm Bytedance Ltd. and potential buyers, as the owner of TikTok faces pressure from the White House to quickly sell the popular short-video app's U.S. operations or face an effective ban. On Saturday, China's official Xinhua News Agency quoted a government trade adviser as saying that ByteDance should study the new export list and "seriously and cautiously" consider whether or not it should halt its sales negotiations.

In a groundbreaking first, British researchers have identified 50 new planets using artificial intelligence. A research team led by David Armstrong at the University of Warwick in the United Kingdom created a machine learning algorithm and trained it using data on confirmed planets and false-positives from NASA's retired Kepler mission. The scientists then used the algorithm on a dataset of still unconfirmed planetary candidates from Kepler, resulting in fifty new confirmed planets and the first to be validated by machine learning. Also read: Growing dent on Earth's magnetic field can damage satellites and navigation Their results were reported in a new study published in the Monthly Notices of the Royal Astronomical Society, where they also perform the first large scale comparison of such planet validation techniques. Previous machine learning techniques have ranked candidates, but never determined the probability that a candidate was a true planet by themselves, a required step for planet validation. By confirming that these fifty planets are real, astronomers can now prioritise these for further observations with dedicated telescopes.

A historian of technology and race responds to Tochi Onyebuchi's "How to Pay Reparations." Tochi Onyebuchi's "How to Pay Reparations" spoke to me. Its themes rang virtually every note of my twentysomething-year-long career. In 1998, I made my first digital footprint with a signed online petition in support of reparations for the Tulsa race riots. I endured countless run-ins with Oklahoma good ol' boys while crisscrossing the state, working for candidates representing a perpetually losing political party.

Artificial intelligence has enabled hype in the marketplace. The expensive technologies and expertise has not found a way to integrate cognitive projects with existing processes and systems. It's growing popularity has loomed developers to get expertise in technology. The updated contextual chatbots, the human motion detection technique, tracking insights on government and public companies progress, calculating ROI of businesses, calculate the electric load, and what not? AI progress has never halted to draw attention to scientists and researchers.

AutoML, the application of machine learning to create new automation tools, is branching out to new use cases, making itself useful for particularly tedious data science tasks when training speech recognition models. Among the latest attempts at automating the data science workflow is an AutoML tool from Deepgram, offering what the speech recognition vendor claims is a new model training framework for machine transcription. The startup's investors include Nvidia GPU Ventures and In-Q-Tel, the venture arm of the U.S. intelligence community. Deepgram's flagship platform scans audio data to train a speech recognition tool. Its deep learning tool uses a hybrid convolutional/recurrent neural network approach, training models via GPU accelerators.

The government has pledged £50 million for further investment in artificial intelligence to improve diagnostics across the NHS. The investment aims to speed up the diagnosis of deadly diseases like cancer through delivering digital upgrades to pathology and imaging services across the country. It will scale up the work of the existing Digital Pathology and Imaging AI Centres of Excellence, launched in 2018 to develop cutting-edge digital tools to improve the diagnosis of disease. The three centres set to receive a share of the funding, based in Coventry, Leeds and London, will deliver digital upgrades to pathology and imaging services across an additional 38 NHS Trusts, benefiting some 26.5 million patients across England, according to the Department of Health and Social Care (DHSC). It's hoped the funding will lead to faster and more accurate diagnosis and more personalised treatments for patients, freeing up clinicians' time and ultimately saving lives.