Language models have demonstrated remarkable performance on complex multi-step reasoning tasks. However, their evaluation has been predominantly confined to high-resource languages such as English. In this paper, we introduce a manually translated Bangla multi-step reasoning dataset derived from the English Reveal dataset, featuring both binary and non-binary question types. We conduct a controlled evaluation of English-centric and Bangla-centric multilingual small language models on the original dataset and our translated version to compare their ability to exploit relevant reasoning steps to produce correct answers. Our results show that, in comparable settings, reasoning context is beneficial for more challenging non-binary questions, but models struggle to employ relevant Bangla reasoning steps effectively. We conclude by exploring how reasoning steps contribute to models' predictions, highlighting different trends across models and languages.

Robots have rolled into retail, from six-foot-tall free-moving machines spotting spills in Giant Foods Stores to autonomous shelf-scanners checking inventory in Walmart. At Lowe's, the home improvement chain, a "LoweBot" in some stores can answer simple questions, such as where to find items, and can assist with inventory monitoring. The real benefit of retail robots is the opportunity to capture more granular data about the products on the shelves and customer buying patterns, which can increase efficiency and accuracy in inventory management. The key is using retail robots as data-collectors within an internet-of-things (IoT), which is best thought of as a complex network of connected devices, objects, and sensors gathering voluminous data that is analyzed in the cloud or with edge computing, which uses nearby servers to lower latency. From manufacturing to transportation and now retail, IoT creates an intelligent digital ecosystem.

Lior Elazary believes that robots are a net positive for humans. That's a good thing, because he is the CEO of InVia Robotics and offers a robots-as-a-service platform that can 5-10X productivity in shipping and receiving warehouses. And presumably, he wants to sleep at night. The question, however, remains: is Elazary right? "A lot of people don't realize how gruesome it is to work inside the warehouse," Elazary told me recently in a TechFirst podcast.

When Shamir Rahim, founder and CEO of VersaFleet, transformed his bio-medical startup into an AI-powered transportation management system, he never imagined being at the epicenter (in a good way) of a supply chain revolution during a worldwide pandemic. As anyone desperately searching for toilet paper discovered earlier this year, the last mile is the crucial link in every supply chain. VersaFleet's SaaS-based cloud platform relies on AI to meet one of the toughest supply chain challenges: last mile delivery. "We wanted to provide our customers with a command center view of last mile product delivery with cost and time savings," said Shamir Rahim, founder and CEO of VersaFleet. "As our customers slowly open up again, VersaFleet is providing greater agility so they can quickly adjust logistics for maximum efficiency, whether people are out sick or returning to work, quarantines are lifted or imposed again, and operational hours shift at any time."

Artificial intelligence may be the most powerful tool humans have. When applied properly to a problem suited for it, AI allows humans to do amazing things. We can diagnose cancer at a glance or give a voice to those who cannot speak by simply applying the right algorithm in the correct way. In fact, when improperly applied, it's a dangerous snake oil that should be avoided at all costs. To that end, I present six types of AI that I believe ethical developers should avoid.

Artificial intelligence may be the most powerful tool humans have. When applied properly to a problem suited for it, AI allows humans to do amazing things. We can diagnose cancer at a glance or give a voice to those who cannot speak by simply applying the right algorithm in the correct way. In fact, when improperly applied, it's a dangerous snake oil that should be avoided at all costs. To that end, I present six types of AI that I believe ethical developers should avoid.

Machine-learning models trained on normal behavior are showing cracks --forcing humans to step in to set them straight. People weren't just searching, they were buying too--and in bulk. The majority of people looking for masks ended up buying the new Amazon #1 Best Seller, "Face Mask, Pack of 50". When covid-19 hit, we started buying things we'd never bought before. The shift was sudden: the mainstays of Amazon's top ten--phone cases, phone chargers, Lego--were knocked off the charts in just a few days.

After hovering at around $10 consistently, the price of a five-pound bag of Nishiki medium grain rice shot up to $30 on Amazon.com in March and hit a peak of $59.99 at 9 p.m. on Saturday, March 21, according to the Amazon price tracker Keepa. As of Friday, April 24, the bag of rice was priced at around $20. Prices on Amazon have been volatile since the outbreak of COVID-19 in the United States. By the end of March, Keepa's data revealed, an eight-pack of Barilla spaghetti, whose price normally hovers around $10, shot up to $49.25. The cost of an eight-pack of Skippy Superchunk Peanut Butter nearly quadrupled, from $12.52 to $45. COVID-19 has made the public more aware of price fluctuations on basics like toilet paper, hand sanitizer, and dried goods, as demand for those products surged beyond expectations.

Panic buying has taken hold of many Americans who are stocking up on supplies and leaving shelves empty during the coronavirus. Now, the Pentagon is harnessing the power of artificial intelligence to help predict and address shortages of water, medicines, food, medical supplies and other essentials across the country. The predictive model pulls data from the Census Bureau, Medicare, hospitals and projects how the virus is spreading, along with a number of essential items at retailers to determine where scarcities may occur. Military groups can then use this information to move essential items to specific locations, while retailers can look at the data to predictively restock their shelves. Panic buying has taken hold of many Americans who are stocking up on supplies and leaving shelves empty during the coronavirus.

Demand for Alphabet's drone delivery Wing is soaring in a Virginia town amid the coronavirus pandemic. Residents of Christianburg are under stay at home orders and are taking advantage of the service to receive goods without having to leave their homes. Wing was approved to test deliveries in the area last October, but has recently added new vendors to better serve residents during the lockdown. The firm has made more than 1,000 deliveries in the past two weeks, with toilet paper, coffee and cookies being the most popular. Demand for Alphabet's drone delivery Wing is soaring in a Virginia town amid the coronavirus pandemic.