Welcome to the second of our monthly digests, designed to keep you up-to-date with the happenings in the AI world. You can catch up with any AIhub stories you may have missed, get the low-down on recent conferences, and generally immerse yourself in all things AI. You may be aware that we are running a focus series on the UN sustainable development goals (SDG). Each month we tackle a different SDG and cover some of the AI research linked to that particular goal. In February it was the turn of climate action.
You will receive 58 hours of applied instructor-led training. To earn the certification, you should attend a full batch of online training and submit a completed project for the flexi-pass learners or complete at least 85% of the course and submit one completed project for the self-paced learners. The machine learning certification course by Simplilearn is designed for learners with intermediate-level machine learning knowledge and skills in various roles, including business analysis, data analysis, information architecture, data science, machine learning, and others. To take this course, you need a college-level understanding of statistics and mathematics as well as Python programming knowledge. Simplilearn offers a blended learning approach that gives learners access to both live instructor-led training and recorded-videos.
The ability to make fast, data-driven decisions has never been more valuable as businesses grapple with the shift toward hyper-personalisation, driven by rapidly changing customer behaviours and expectations. The pandemic has accelerated the imperative for businesses to invest in Artificial Intelligence (AI) and Machine Learning (ML) so they can replace guesswork with data-powered certainty to reorient strategy and optimize operations for success in an uncertain future. Nevertheless, enterprises often struggle to integrate these technologies at scale and monetize the benefits. Stumbling blocks typically include challenges associated with cost, lack of investment protection, undefined business outcomes, lengthy timeframes from development to deployment, lack of expertise, and the complexities of the regulatory landscape. Gartner predicts that by 2022, at least 50% of ML projects will not be fully deployed into production.
In recent months, concerns about the economic impact of the pandemic have been closely tied with a spate of panicked automation headlines like, "Will Robots Take Our Jobs In A Socially Distanced Era??". Already we have seen that incorporating new technologies has led to a dramatic shift in the way industries operate worldwide. We are also witnessing a significant rise in interest for robotic process automation (RPA), intelligent automation and artificial intelligence among business leaders who realize that intelligent automation demonstrates strong transformative potential across all industries. Business leaders are accelerating the adoption of technologies they view as crucial to digital transformation efforts – like intelligent and robotic process automation – to help them thrive in this tumultuous business environment and beyond. Businesses are constantly met with new restrictions and 63% of business decision makers feel they are struggling to meet customer demands.
The United States is dangerously behind in artificial intelligence critical to its future including national security, according to a commission that includes a former head of Google and the future chief of Amazon. A report released by the National Security Commission on Artificial Intelligence called for the country to invest $40 billion to win a strategic AI competition with China. "America is not prepared to defend or compete in the AI era," ex-Google chief Eric Schmidt and former US deputy secretary of defense Robert Work said in a letter included with the 756-page report. "This is the tough reality we must face," the chairs of the commission said in the report released late Monday. The commission formed by Congress in 2018 is made up of technologists, national security professionals, business executives, and academic leaders including Oracle chief executive Safra Katz, an Andrew Jassy, who will take over head of Amazon later this year.
Objective: The goal of this article was to identify potential biomarkers for early diagnosis of sepsis in order to improve their survival. Methods: We analyzed differential gene expression between adult sepsis patients and controls in the GSE54514 dataset. Coexpression analysis was used to cluster coexpression modules, and enrichment analysis was performed on module genes. We also analyzed differential gene expression between neonatal sepsis patients and controls in the GSE25504 dataset, and we identified the subset of differentially expressed genes (DEGs) common to neonates and adults. All samples in the GSE54514 dataset were randomly divided into training and validation sets, and diagnostic signatures were constructed using least absolute shrink and selection operator (LASSO) regression.
Rising consumer awareness regarding risk management and implementation of big data solutions are driving the market for clinical risk grouping software. Scorecard & visualization tools, dashboard analytics, and risk reporting are the three product types of clinical risk grouping solutions. Scorecard & visualization tools segment dominated the market with the largest share due to its ability to predict payment processes accurately and project per-patient risk. The rising need to reduce healthcare costs through these two channels is expected to augment the growth of the segment during the forecast period. Hospitals, payers, ambulatory care centers, and long-term care centers, among others are the end-users of clinical risk grouping solutions, of which hospitals accounted for the largest market share in 2018.
Marking a significant shift in India's digital journey, the Union Finance Minister, Nirmala Sitharaman, has presented the first-ever digital budget for the upcoming fiscal year starting April 2021. Her budget speech touched upon "proliferation of technologies, especially analytics, machine learning, robotics, bioinformatics, and artificial intelligence." The budget has come at a time when the country is still struggling with the massive economic slowdown precipitated by COVID pandemic. However, despite this downturn, businesses have seen a significant push towards digitisation, including acknowledging the importance of artificial intelligence across industries. As a matter of fact, India is considered one of the fastest-growing digital markets globally.
According to a WHO prediction, by 2020, roughly 20% of India will suffer from some mental illness and 450 million people currently suffer from a mental illness, worldwide. These numbers are a wake-up call that psychology as an issue and psychologists as a profession must be taken seriously. Such helping professions are often considered as human channels. Unlike manual workers whose job responsibilities are being taken over by machines and AI bots, psychiatrists and counselors see no threat to their professions with the advancements of machine learning and artificial intelligence. According to an influential survey of the future of employment by Carl Benedikt Frey and Micheal Osborne who are Oxford economists, the probability that psychology could be automated in the future is only 0.43%.