Biscotti once fed Roman navies and Christopher Columbus's expeditions Long before it met espresso, this crunchy pastry kept sailors fed. Roman writer Pliny the Elder was the first writer to mention biscotti in 77 CE. Breakthroughs, discoveries, and DIY tips sent every weekday. Step into a typical Italian restaurant in the U.S. and you'll likely find "biscotti" on the menu. Typically served with a glass of sweet wine or cappuccino, these log-shaped crunchy cookies are a beloved treat that most of us associate with cozy dinners and Little Italy.

Cadastral data reveal key information about the historical organization of cities but are often non-standardized due to diverse formats and human annotations, complicating large-scale analysis. We explore as a case study Venice's urban history during the critical period from 1740 to 1808, capturing the transition following the fall of the ancient Republic and the Ancien Régime. This era's complex cadastral data, marked by its volume and lack of uniform structure, presents unique challenges that our approach adeptly navigates, enabling us to generate spatial queries that bridge past and present urban landscapes. We present a text-to-programs framework that leverages Large Language Models (\llms) to process natural language queries as executable code for analyzing historical cadastral records. Our methodology implements two complementary techniques: a SQL agent for handling structured queries about specific cadastral information, and a coding agent for complex analytical operations requiring custom data manipulation. We propose a taxonomy that classifies historical research questions based on their complexity and analytical requirements, mapping them to the most appropriate technical approach. This framework is supported by an investigation into the execution consistency of the system, alongside a qualitative analysis of the answers it produces. By ensuring interpretability and minimizing hallucination through verifiable program outputs, we demonstrate the system's effectiveness in reconstructing past population information, property features, and spatiotemporal comparisons in Venice.

When Sookie Orth sat down to write her college essay last fall, something quickly came to mind. Orth, then a senior at Sequoyah School in Pasadena, began her draft with a declaration: "I learned how to fold a pizza box at the age of nine." She told the story of her years-long connection with Pizza of Venice in Altadena, where she often dined with her family as a little kid. One day, the manager invited her to assemble a box. Impressed with Orth's speed, the woman told her she could work at the pizzeria when she was older.

Each user sits at a computer and answers a series of personal questions, which the exhibit – in the space of a few seconds – converts into a bespoke portrait of their life. The project, Tulpamancer, is officially the work of Brooklyn-based artists Marc Da Costa and Matthew Niederhauser. In practice, though, it amounts to a creative collaboration between the user and AI. Generative AI plays the role of Sleeping Beauty's bad fairy at Venice. The ongoing writers and actors' strike was largely prompted by fears over the new technology's impact on film and TV production and has resulted in numerous star performers deciding to skip this year's festival.

This morning, before checking in on my young son or making a coffee, I opened the Duolingo app on my phone and translated "They love smelling meat" into Italian. I've been starting my days like this for a few months now: wake up, wash face, grapple with the gerund. I usually spend between 10 and 20 minutes on it while the kettle boils or I load CBeebies or write some emails. Duolingo is a language learning app and pretty simple to use. After you've chosen which language you want to learn, you are presented with about 100 skill-sets divided by scenario or grammar (grocery shopping, the future tense and so on).

"In our field of risk analytics, as in many others, artificial intelligence and machine learning will make the type of information that we see as valuable …

OpenAI's GPT-2 has been discussed everywhere from The New Yorker to The Economist. What does it really tell us about natural and artificial intelligence? The Economist: Which technologies are worth watching in 2020? GPT-2: I would say it is hard to narrow down the list. The world is full of disruptive technologies with real and potentially huge global impacts. The most important is artificial intelligence, which is becoming exponentially more powerful. Consider two classic hypotheses about the development of language and cognition. One main line of Western intellectual thought, often called nativism, goes back to Plato and Kant; in recent memory it has been developed by Noam Chomsky, Steven Pinker, Elizabeth Spelke, and others (including myself).

Data science is all about data, and I'm pretty sure you already knew that. But did you know that we use data science to make business decisions? I'm pretty sure you knew that as well. So what else is new here? Well, do you know how data science is used to make business decisions?

In a lagoon in Venice, robotic lily pads float on the surface, with clusters of electronic mussels resting on the bed below. In July, a self-organising team of robots will be released into the murky waters of a lagoon near Venice, Italy. To continue reading this premium article, subscribe for unlimited access. Existing subscribers, please log in with your email address to link your account access.

The use of machine learning to garner insights about the future is one of the benefits of the technology most oft cited by enterprise. For historians, however, its true potential lies in its ability to reveal new things the past - potential that is now being realized on a massive scale. There have been a number of projects conducted by historians in recent years that have leveraged data analytics. Real Clear Politics, for example, applied text mining tools to 34 years of state of the union addresses, starting with Ronald Reagan in 1981, to analyze their political tone. They looked at the language used to chart each speech ideologically (on a left-right political scale) based on its content.