National Review editor-in-chief Rich Lowry and FOX Business' Liz Claman join'MediaBuzz' to discuss Hegseth's heated press conference where he called out the media's'hatred' of President Donald Trump. FIRST ON FOX: Defense Secretary Pete Hegseth has issued sweeping new orders to fast-track drone production and deployment, allowing commanders to procure and test them independently and requiring drone combat simulations across every branch of the military. As part of an aggressive push to outpace Russia and China in unmanned warfare, "the Department's bureaucratic gloves are coming off," Hegseth wrote. "Lethality will not be hindered by self-imposed restrictions... Our major risk is risk-avoidance." In a pair of memos first obtained by Fox News Digital, Hegseth rescinded legacy policies that he believes restricted innovation.

Origins With Cush Jumbo Widely available, episodes weekly Cush Jumbo is always good fun when doing press interviews for her work (The Good Wife, Criminal Record, Hamlet) – and she's just as great now the tables are turned in her first podcast. She speaks to stars about their origin stories, including Kate Nash, Harlan Coben, David Schwimmer and, in episode one, Anna Wintour, who says she hates people who waffle and recalls getting fired from Harper's Bazaar because she couldn't pin a dress. Rebel Spirit Widely available, episodes weekly Comedian Akilah Hughes gives her serious mission a light touch as she returns to her Kentucky home town to try to change her high school's racist mascot from a Confederate general to a biscuit. Can she drag the school into the modern age – and what will the change mean to her and other pupils? Sara & Cariad's Weirdos Book Club Widely available, episodes weekly Sara Pascoe and Cariad Lloyd go beyond the usual selections with season two of their book club for people who don't want to discuss reading over cheese and wine.

We study routing for on-demand last-mile logistics with two crucial novel features: i) Multiple depots, optimizing where to pick-up every order, ii) Allowing vehicles to perform depot returns prior to being empty, thus adapting their routes to include new orders online. Both features result in shorter distances and more agile planning. We propose a scalable dynamic method to deliver orders as fast as possible. Following a rolling horizon approach, each time step the following is executed. First, define potential pick-up locations and identify which groups of orders can be transported together, with which vehicle and following which route. Then, decide which of these potential groups of orders will be executed and by which vehicle by solving an integer linear program. We simulate one day of service in Amsterdam that considers 10,000 requests, compare results to several strategies and test different scenarios. Results underpin the advantages of the proposed method

Wolfenstein is a classic game series, one of the progenitors of first-person shooters. You never forget the first time you got to shoot a cybernetic Hitler with a flamethrower. After languishing a bit in the early 2000s, it came back into glorious form with a soft reboot in 2014 with Wolfenstein: The New Order. It's the weekly giveaway on the Epic Games Store, and well worth picking up if you haven't played it already. Though The New Order preserves the straightforward, action-packed shooting action that the series is known for, it also has a surprisingly engaging narrative.

Simulated environments are increasingly used by trading firms and investment banks to evaluate trading strategies before approaching real markets. Backtesting, a widely used approach, consists of simulating experimental strategies while replaying historical market scenarios. Unfortunately, this approach does not capture the market response to the experimental agents' actions. In contrast, multi-agent simulation presents a natural bottom-up approach to emulating agent interaction in financial markets. It allows to set up pools of traders with diverse strategies to mimic the financial market trader population, and test the performance of new experimental strategies. Since individual agent-level historical data is typically proprietary and not available for public use, it is difficult to calibrate multiple market agents to obtain the realism required for testing trading strategies. To addresses this challenge we propose a synthetic market generator based on Conditional Generative Adversarial Networks (CGANs) trained on real aggregate-level historical data. A CGAN-based "world" agent can generate meaningful orders in response to an experimental agent. We integrate our synthetic market generator into ABIDES, an open source simulator of financial markets. By means of extensive simulations we show that our proposal outperforms previous work in terms of stylized facts reflecting market responsiveness and realism.

As we begin to slowly emerge from behind the shadow of COVID-19, the virus has brought new meaning to words like adaptability, mitigation and recovery for business. Although we've had no choice but to scramble to operate in a new world of distributed labor forces, we have at our disposal dynamic technologies and innovations that have helped us through -- not the least of which is artificial intelligence. With automation as a foundation, we are seeing a growing number of organizations bringing AI to bear on areas of the business that are individually distinct but transcend industries. Each of these operations is vital to the health and success of the company and even more so in times of disruption. Perhaps one of the more overlooked operations has been the IT infrastructure.

A future chart-topping song may soon come from an algorithm. Sony Computer Science Laboratory (CSL) in Paris is developing a system of algorithms which can create songs that cater to the user's taste, based on styles adapted from existing music. The starting point of the song creation is a database of sheet music of more than 13,000 existing songs, from which the user can choose any number of titles with a sound or feel they would like the new song to incorporate. The algorithm analyses the songs' characteristics, and statistical properties related to rhythm, pitch and harmony. It will learn, for instance, which notes "go well" with a given chord, what chord is probable after a given chord, or which notes usually follow after a given note.