Large language models have taken the public attention by storm – no pun intended. In just half a decade large language models – transformers – have almost completely changed the field of natural language processing. Moreover, they have also begun to revolutionize fields such as computer vision and computational biology. Since transformers have such a big impact on everyone's research agenda, I wanted to flesh out a short reading list (an extended version of my comment yesterday) for machine learning researchers and practitioners getting started. The following list below is meant to be read mostly chronologically, and I am entirely focusing on academic research papers.

In her global role based in London, UK, Hande leads the marketing of data and artificial intelligence services for HPE GreenLake Edge to Cloud Platform. Hande has 20 years of technology and marketing experience as a consultant, portfolio and marketing manager. Hande has passion for emerging technologies and their impact on organizations, societies and ethics.

The Association for Unmanned Vehicle Systems International (AUVSI), the world's largest nonprofit organization dedicated to the advancement of unmanned systems and robotics, has compiled a list of "wow-worthy" examples of the vision that the fifth generation of wireless technology (5G) is inspiring for the use of connected drones. It says that 5G can: bring data-throughput speeds of up to 10 gigabytes per second, enabling real-time sharing of aerial video and other sensor data; enable devices to stay connected while traveling hundreds of miles per hour, allowing for remote deployment of AI-enabled, ultra-responsive autonomous fleets; and it could support up to a million connected devices per square kilometer -- enough capacity to absorb an explosion in the Internet of Things alongside increasingly sophisticated mobile applications, on the ground and aloft. "5G is going to be transformative," says Tom Sawanobori, chief technology officer for CTIA (Cellular Telecommunications Industry Association). He cited a 2017 study by Accenture which estimated 5G would bring 3 million new jobs, $275 billion in new investment and a $500 billion boost to the U.S. gross domestic product. Active tech companies in the markets this week include FLIR Systems, Inc. (NASDAQ: FLIR), Plymouth Rock Technologies Inc. (CSE: PRT) (OTCQB: PLRTF), Verizon Communications Inc. (NYSE: VZ), Raytheon Technologies Corporation (NYSE: RTX), QUALCOMM Incorporated (NASDAQ: QCOM).

The field of AI (artificial intelligence), to those on the outside, must appear to be an orderly gathering of intellectuals collaborating at the cutting edge of technology. The reality is a bit different. Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it and offered the example of finding a way to police the misuse of the telephone because of its possible misuse by some individuals with bad intentions rather than not inventing the phone at all. One of the biggest misconceptions surrounding AI is that most individuals think that humanity is close to it, although in fact the reality is quite different. Although a great deal has been learned about how to engineer certain narrow problems like speech recognition in ways which could not have been imagined five or ten years ago, the idea of having machines that can reason about the world in the ways that human-beings can is still implausible.

The field of AI (artificial intelligence), to those on the outside, must appear to be an orderly gathering of intellectuals collaborating at the cutting edge of technology. The reality is a bit different. Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it and offered the example of finding a way to police the misuse of the telephone because of its possible misuse by some individuals with bad intentions rather than not inventing the phone at all. One of the biggest misconceptions surrounding AI is that most individuals think that humanity is close to it, although in fact the reality is quite different. Although a great deal has been learned about how to engineer certain narrow problems like speech recognition in ways which could not have been imagined five or ten years ago, the idea of having machines that can reason about the world in the ways that human-beings can is still implausible.