In today’s episode on the Delta Dialog, we look into the cyclical nature of AI's progress, the evolving public perception, the critical role of international cooperation, and the invaluable lessons from past setbacks.

In today’s episode on the Delta Dialog, we delve into misconceptions and AI that range from overestimating AI's capabilities and misunderstanding the historical development process, to confusing AI with automation.

The Yuan’s five-part series on the history of AI wraps up with this final installment. AI expert Gil Press recites the landmark events of the 2010s, among them the emergence of Big Data, DL, and neural networks. Is AGI next? Experts diverge on the course ensuing events will take.

The 1990s and 2000s logged more real-world applications of ML and the revival of artificial neural networks. In this fourth in a five-part series on the history of AI, AI expert Gil Press tells how ‘godfathers of AI’ Geoffrey Hinton and Yann LeCun and others catalyzed this shift.

The 1970s and 1980s were pivotal in AI’s development. ML and expert systems gained ground, but short-lived AI euphoria soon gave way to the AI winter in the 1990s. Data and AI analyst Gil Press conducts a tour of this era in this third in his five-part series on the history of AI.

AI moved beyond its conceptual phase and appeared in real-world applications in the 1950s, with early computer scientists, mathematicians, and psychologists winning recognition for their works, prescience, and herculean achievements, which set the stage for further breakthroughs.

AI has come a long way since its humble beginnings in the 1940s, and a look back at this history is both fascinating and informative as an indicator of how the tech might continue to evolve, notes Gil Press, managing partner at the consultancy gPress and a noted AI commentator.

Day eight brings The Yuan’s expedition of intelligent exploration back to the shores of Massachusetts Bay, land of MIT, the pulsating tech hub of Boston, and the Native American nation of the Wampanoag - ‘People of the First Light’ - whose generous humanity saved the Pilgrims from starvation during their first desperate winter (1621) amid the harsh, unfamiliar conditions of the New World. Gil Press, managing partner at marketing, publishing, research, and education consultancy gPress and a noted AI commentator, sits in the pilot seat to propound his thesis that its very humanity will allow humanity to stay a hop, skip and a jump ahead of AGI, or any other sentient AI since, even in the unlikely event it does ultimately arise, it will be but a pale, artificial shadow of its creator.

AI personalized healthcare and medical treatments target patients’ unique traits and needs, but equally important is preventative care encompassing personalized nutrition plans tailored to, e.g., gut microbes, lifestyle, and socioeconomic factors, states AI commentator Gil Press.

The US healthcare system is notorious for fragmentation, inefficiency, and high costs. Many efforts have been made to address these problems, but with limited success. Will ChatGPT and other newly available tools hold novel answers, or will they just generate even more data silos?

In this episode Gil Press, David Wood and Emir M. Isler explore the underdevelopment of open medical data in the United States, and the challenges faced by patients who are seeking greater access to their own medical information.

Digital health tech is upending US healthcare delivery. From wearables that track vital signs to remote consultations with doctors, tech will improve patient outcomes, cut costs, and open access to care, but concerns abound over data privacy and worsened healthcare disparities.

AI healthcare applications have succeeded in analyzing data to discover new insights and help healthcare professionals do their jobs better. Natural language processing promises to take this a step further by analyzing unstructured data such as written text in patients’ health records, which will result in even more in-depth insights and better, more accurate healthcare decisions, predicts AI commentator Gil Press.

The Covid-19 pandemic has transformed healthcare, forcing it to digitalize and become more at-home, a change which is now going beyond telehealth and remote monitoring to providing hospital-level care at home. Big Tech is also moving beyond health apps and into mainstream healthcare, a development which holds huge ramifications for the industry.

Gil Press looks back at his predictions of the evolution of artificial intelligence in 2022. He acknowledges it is difficult to predict the future of science, industry, and healthcare, but believed that data, data, and even more data would play a central role in shaping it in 2022, and now takes a look at whether or not that has been the case.

AI commentator Gil Press has a modest proposal for the US to emulate the internet and create healthcare open data infrastructure and set standards for its machine readability, as part of The Yuan’s ongoing Open Medical Data series.

Gil Press examines the impact of artificial intelligence on the healthcare sector in the first quarter of 2022 and how far it has come, asserting that a shift in orientation is called for if the field is to advance from automation to augmentation, and from an emerging technology to a mature one.

Gil Press presents the third in a series of articles this week on The Yuan platform predicting the evolution of artificial intelligence in 2022. He acknowledges it is difficult to predict the future of science, industry, and healthcare, but believes data, data, and even more data, will play a central role in shaping it in 2022.

Gil Press breaks down into bite-sized pieces a new pioneering report by The Yuan, Evomics Medical, and Deep Pharma Intelligence on the groundbreaking work being unearthed in the healthcare and pharmaceutical sectors because of access to real-world data and real-world evidence.

‘It’s good to talk,’ was a popular meme for British Telecom back in the monolog 1990s, but now is more relevant than ever in the digital age. Conversational artificial intelligence solutions have come to the fore, interacting in complex conversations, and providing personalized responses, thus easing the heavy burden on healthcare systems worldwide.

The development of new drugs is a slow, exhaustive, and expensive process that can last over ten years, and often ends in failure. Gil Press investigates the deployment of new AI technologies, techniques, and quantum computing (QC) to transform the procedure to make it faster, easier, and cheaper.

Digital Health is possibly the most prominent of the technology-driven trends the COVID-19 pandemic has drastically accelerated. The concepts of remote patient monitoring, understanding the social determinants of health, and continuous patient data collection and analysis for early detection, ongoing interaction and intervention, and the use of AI to do all that and more are not novel.

As the post-pandemic “new normal” takes hold in the US and the country learns to live with COVID-19, the potential for using AI to address some of the long-term deficiencies of the healthcare system in the US has never been greater. Recent progress in AI capabilities, the lessons learned during the pandemic, and new entrepreneurial endeavors, are coalescing into a renewed focus on providing the right treatment at the right time in the most appropriate setting.