The graph represents a network of 1,066 Twitter users whose tweets in the requested range contained "iiot bigdata", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 12 August 2022 at 11:03 UTC. The requested start date was Friday, 12 August 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 15-hour, 7-minute period from Tuesday, 09 August 2022 at 08:52 UTC to Thursday, 11 August 2022 at 23:59 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Thirty-five years ago, New Zealand adopted a law declaring the official status of Te Reo Māori, the language spoken by the country's indigenous Māori people. Decades of repression put the language, also called simply te reo, under serious threat: only one in four Māori spoke it by 1960, with a very low percentage of speakers among children. Since then, the language has started regaining lost ground, enjoying formally equal status with English and being taught widely to New Zealand schoolchildren. Still, reviving it as a living language takes time and persistence. Lately, the nascent te reo renaissance is gaining added momentum with the help of artificial intelligence (AI).

The graph represents a network of 2,308 Twitter users whose tweets in the requested range contained "InsurTech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 12 August 2022 at 12:34 UTC. The requested start date was Friday, 12 August 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 5-day, 11-hour, 8-minute period from Saturday, 06 August 2022 at 12:48 UTC to Thursday, 11 August 2022 at 23:57 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

Verdict has listed five of the companies that trended the most in Twitter discussions related to disruptive tech, using research from GlobalData's Technology Influencer platform. The top companies are the most mentioned companies among Twitter discussions of more than 513 disruptive tech experts tracked by GlobalData's Technology Influencer platform during the second quarter (Q2) of 2022. OpenAI's text-to-image engine DALL·E 2 not understanding some mysterious language, and the company's release of GPT-3, a new generative language model, were some of the popularly discussed topics in Q2. Spiros Margaris, a venture capitalist and board member at the venture capital firm Margaris Ventures, shared an article on the artificial intelligence (AI) company, OpenAI, having found its text-to-image engine DALL·E 2 to show peculiar behaviours, including something that may be hidden or a fictional language. According to Giannis Daras, a PhD student at the University of Texas at Austin, the AI model produced an artwork when given the input "apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons", which makes no sense to humans but the machine generated images of birds eating bugs constantly, the article detailed.

To solve the most pressing scientific problems, scientists today often face enormous hurdles when it comes to gathering the data they need to embark on research. Enter Ramkumar Hariharan, a data scientist and computational biologist at Northeastern University in Seattle. A scientist and an engineer, Hariharan's current research is centered around an emerging scientific field called geroscience, or the "study of aging as it relates to age-related diseases." Hariharan has been trying to understand the reasons why some cancer patients respond better to certain kinds of immunotherapies. To do so requires lots of information about the patients themselves, the specific forms of cancer and the drugs used to treat patients.

I can't help thinking that, too often, the future is owned by the very people who should never own it. If Facebook, Google and the like had been created by more sensitive, worldly and, dare one suggest, human hands, we wouldn't be stuck with today's glorious mess. So yes, as you've surely guessed already, we're here today to discuss Starbucks. Get the perfect brew at home with ZDNet's favorite coffee makers. Here's a company that made its own little contributions to the future and came to dominate the streets, malls, minds and coffee plantations of the world.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Unlocking greater performance gains in warehouses using artificial intelligence (AI) and machine learning (ML) helps make supply chains more resilient and capable of bouncing back faster from disruptions. Unfortunately, the severity and frequency of supply chain disruptions are increasing, with McKinsey finding that, on average, companies experience a disruption of one to two months in duration every 3.7 years. Over a decade, the financial fallout of supply chain disruptions in the consumer goods sector can equal 30% of a year's earnings before interest, taxes, depreciation and amortization (EBITDA).