Many multi-billion-dollar companies have been built by providing tools to make software development easier and more productive. Venture capitalists like to refer to businesses like these as "pick and shovel" opportunities, a reference to Mark Twain's famous line: "When everyone is looking for gold, it's a good time to be in the pick and shovel business." Atlassian, which offers a suite of software development and collaboration tools, has a public market capitalization above $30B. GitHub, a code repository, was acquired for $7.5B by Microsoft in 2018. Pivotal, which accelerates app development and deployment, was valued at $2.7B in VMWare's acquisition last year.

This article is part of a special report on artificial intelligence, The AI Issue. Europe's plan to ride a new wave of AI innovation into a technological renaissance relies on companies sharing their data with researchers and entrepreneurs. But will the companies play along? According to interviews with industry groups representing Silicon Valley, European tech companies and Germany's industrial base, the answer for now is: maybe, but only to a limited extent, and even then only when sharing data will not benefit rivals. "We haven't seen any single company speaking up in public saying it was a great idea," said Alexandre Roure of the Computer and Communications Industry Association (CCIA), a tech lobby whose members include Google and Facebook.

Health experts analyze the Spanish Flu, Asian Flu, Hong Kong Flu and swine flus of 1976 and 2009 in a special hosted by Harris Faulkner. Some police departments in California plan on using drones to enforce a coronavirus lockdown and to, in part, monitor the homeless population, according to a report on Friday. The Chula Vista Police Department, located just south of San Diego near the California-Mexico border, recently purchased two $11,000 drones -- doubling its fleet -- that will be outfitted with speakers and night vision cameras. "We have not traditionally mounted speakers to our drones, but ... if we need to cover a large area to get an announcement out, or if there were a crowd somewhere that we needed to disperse -- we could do it without getting police officers involved," said Capt. The Chula Vista Police Department plans on using drones to enforce a coronavirus lockdown.

An unmanned convenience store began operations Monday at a recently opened station on Tokyo's Yamanote loop line, using artificial intelligence not just to allow speedy self-checkouts but to also prevent shoplifting. The store is a key feature at the Takanawa Gateway Station, which opened on March 14 as the first new stop on the line in nearly 50 years. About 50 cameras installed inside the roughly 60-square-meter store identify every item customers pick up. The store's exit gates open once the customer makes a payment. The AI used at the shop has been trained to recognize customer behavior, including how items are carried, and it almost fully prevents shoplifting by accurately recognizing when merchandise is taken from shelves, according to its developer Touch To Go Co. Attempts in a demonstration to hide merchandise under clothes or avoid being seen on the cameras while stashing it in a bag were all detected.

From e-scooters to self-driving shuttles, to ride-hailing and car-sharing, auto companies and startups are testing any number of mobility services. While the long-term viability of some of these services remains unclear, one factor surrounding them is certain: The need for comprehensive insurance coverage for users. And that may present an opportunity for a new kind of insurance policy, one that could be on demand, for example. PSA North America's Free2Move short-term rental fleet in Washington, D.C., uses coverage through mobility insurance provider Trov. Insurance premiums are adjusted based on data Trov receives in real time from Free2Move's connected vehicles.

In this special guest feature, Ido Ramati, Founder, COO & President at Revuze, discusses how unstructured data is being wasted by companies the world over. It is estimated 90 percent of an enterprise's data is unstructured, living in emails, online reviews, or other untouched and ultimately useless formats. This data – defined as "unstructured" and growing at 55 to 65 percent each year – offers valuable customer insight if properly understood. Ido is a serial entrepreneur with extensive business and leadership experience, including deep business and technological Internet knowledge. He has founded and led a number of start-up companies through fundraising and launch.

Spain will unleash robots capable of testing 80,000 patients a day into the heart of its coronavirus fight. The Spanish government says it will deploy the machines that will increase testing from its current daily figure of between 15,000 and 20,000. Raquel Yotti, head of Madrid's Health Institute Carlos III, said the plans to deploy the robots are already under way. She spoke as Spain's death toll surpassed 1,300 and the number of cases reached nearly 25,000. She said at a conference: "A plan to automate tests through robots has been already designed, and Spain has committed to buying four robots that will allow us to execute 80,000 tests per day."

A team of US researchers has invented a portable surveillance device powered by machine learning called'FluSense' that can detect coughing and crowd size in real time, analyse the data to directly monitor flu-like illnesses and influenza trends and predict the next pandemic in the making. The'FluSense' creators from University of Massachusetts Amherst said that the new edge-computing platform, envisioned for use in hospitals, healthcare waiting rooms and larger public spaces, may expand the arsenal of health surveillance tools used to forecast seasonal flu and other viral respiratory outbreaks, such as the COVID-19 pandemic or SARS. "This may allow us to predict flu trends in a much more accurate manner," said study co-author Tauhidur Rahman, assistant professor of computer and information sciences. Models like these can be lifesavers by directly informing the public health response during a flu epidemic. These data sources can help determine the timing for flu vaccine campaigns, potential travel restrictions, the allocation of medical supplies and more.

In recent years, there has been an increasing interest in open-ended language generation thanks to the rise of large transformer-based language models trained on millions of webpages, such as OpenAI's famous GPT2 model. The results on conditioned open-ended language generation are impressive, e.g. Besides the improved transformer architecture and massive unsupervised training data, better decoding methods have also played an important role. This blog post gives a brief overview of different decoding strategies and more importantly shows how you can implement them with very little effort using the popular transformers library! All of the following functionalities can be used for auto-regressive language generation (here a refresher).

My co-author Henry King and I have been asked several times since launching our series on Flow whether the model can tell us anything about the coronavirus pandemic as it is currently being defined by the WHO (as of March 15, 2020). We aren't health professionals, so we are reluctant to comment on the virus, how it works and spreads, or on medical interventions and antiviral technologies. But we can make observations about the emerging, and now normalizing, response to the virus at least in the USA, what we may learn from it, and what, if any, long term implications there might be for business and our society more generally. From cancelled conferences to disrupted supply chains, not a corner of the global economy is immune to the spread of COVID-19. The mandate we have all been given, from health professionals, from politicians, from our employers, is "stay at home".