Telcos are hoping that 5G will transform enterprises the way 4G helped consumers. For instance, watching Fifa World Cup 2022 would have been a delight for many with 5G networks. The first rollouts took place in 2019 in South Korea and the US, but since then 5G has been rolled out in over 70 countries. In India, 5G services were launched by Bharti Airtel and Reliance Jio in October. According to a GSMA Intelligence report, published in October, 5G can contribute $455 billion to the Indian economy between 2023 and 2040.

Say you need to implement some machine learning system. Should you purchase a product, re-use open-source code, or develop your own algorithms? The decision does not need to be a binary one. I discuss the pluses and minuses of both options. Combining them offers the best of both worlds.

A detailed article on the Georgia Tech and Facebook partnership aimed at building diversity in the AI field appears in the January issue of University-Industry Engagement Advisor. In the initial steps of a program of collaboration with U.S. universities "that serve significant populations of Black and Latino students," Facebook has partnered with Georgia Tech to develop, co-teach, and fund graduate-level online deep learning courses. The program will be expanded in 2021 to include additional institutions. The collaboration at Georgia Tech came about through discussions between Facebook and the university's Machine Learning Center and the School of Interactive Computing, says Zsolt Kira, PhD, associate director of the Machine Learning Center at Georgia Tech and an assistant professor in the School of Interactive Computing. This is not the first collaboration between the two partners, says Paco Guzmán, research scientist manager at Facebook and a lecturer for Facebook's Co-teaching AI Program.

X4Impact, the leading Insights-as-a-Service company in the Nonprofit and Tech for Good sector honored by Fast Company as a World Changing Idea, partnered with Ability Central, providing the data that powers their disability-related directory service. Ability Central's Service Locator, powered by X4Impact, is a searchable database of organizations supporting Deaf and disabled communities. The Locator helps people easily find resources and local services that fit their needs. Included are organizations serving people who are Deaf, blind or low vision, neurodiverse, have speech or mobility issues, and more. X4Impact provided up-to-date information and links to local support services anywhere in the United States, from community organizations to care facilities.

Say you need to implement some machine learning system. Should you purchase a product, re-use open-source code, or develop your own algorithms? The decision does not need to be a binary one. I discuss the pluses and minuses of both options. Combining them offers the best of both worlds.

A NEW tool has emerged online, which uses artificial intelligence to generate a sketch of subjects based on a phrase typed into a search bar. Artificial intelligence refers to computers which have been given the ability to solve problems like humans. In this case, the DALL-E-mini generator uses images from a series of large internet databases to generate a sketch of a phrase – which sometimes comes back with a clear image and other times not. As you can see above it has a fair idea what a cattle feedlot is. The generator has mainly been used to spread silly images on social media, like this one of Shane Warne bowling out Vladimir Putin.

SARDI scientist Rhiannon Schilling showcases a demonstration application created by using paddock data and machine learning models. PINPOINTING the cause of paddock-yield variability using large data sets and innovative machine-learning models is the focus of a project led by the University of Adelaide and funded by the Grains Research and Development Corporation (GRDC). South Australian Research and Development Institute (SARDI) agriculture scientist Rhiannon Schilling gave an update of the project at ABARES Outlook online this week. Ms Schilling said the research looked at the challenge of working out what is behind variability in crop growth and yield across paddocks. "Often there has been a focus on improving grain yields of our varieties; but when we drive around and have a look at our paddocks, we can see that we are not always achieving uniform crop growth and yield across our paddocks," Ms Schilling said.

BE PART OF BUILDING THE FUTURE. What do NASA and emerging space companies have in common with COVID vaccine R&D teams or with Roblox and the Metaverse? The answer is data, -- all fast moving, fast growing industries rely on data for a competitive edge in their industries. And the most advanced companies are realizing the full data advantage by partnering with Pure Storage. Pure's vision is to redefine the storage experience and empower innovators by simplifying how people consume and interact with data.

In a Q&A, Vincent Granville, executive data scientist and co-founder of Data Science Central, discusses how AI has changed the data science field and the ways in which it will continue to do so. The data science field has changed greatly with the advent of AI. Artificial intelligence has enabled the rise of citizen data scientists, the automation of data scientist's workloads, as well as the need for more skilled data scientists. Vincent Granville, co-founder of Data Science Central, a community and resource site for data specialists, expects to see an increase in AI and IoT in data science over the next few years, even as AI continues to change the data science field. In this Q&A, Granville discusses data science trends, the impact of AI and IoT on data scientists, how organizations and data scientists will have to adapt to increased data privacy regulations, and the evolution of AI. Data Science Central was acquired by TechTarget on March 4. Will an increase in citizen data scientists due to AI, as well as an increase of more formal data science education programs, help fix the so-called data scientist shortage?

Editor's note: Although this author absolves the researchers (from Google) and blames only the journalists for the widespread false claims of a 95% accuracy level for mortality prediction, note that the research paper itself does indeed use the word "accuracy" multiple times as a synonym of AUROC, thus "starting it" among the non-technical or less technical journalists at large. Having my newsfeed cluttered with articles about Google creating an AI that beats hospitals by predicting death with 95% accuracy (or some other erroneous claim), I dug up the original research paper to fact check this wondrous new advancement. Many of said articles used this quote from the abstract (academia's equivalent of a paperback blurb): These models outperformed traditional, clinically used predictive models in all cases. We believe that this approach can be used to create accurate and scaleable predictions for a variety of clinical scenarios. To the best of our knowledge, our models outperform existing EHR (Electronic Health Record) models in the medical literature.