Artificial intelligence (AI) offers plenty of opportunities in the job market, as many AI companies try to solve real-world problems through this field of practice. AI's growth also comes with a wide range of options available to find the best majors for artificial intelligence. When it comes to what degree in artificial intelligence should you pursue, keep reading to learn how to choose a major for artificial intelligence and know the possible AI career paths that are open to you after graduating. A career in artificial intelligence provides tech professionals with competitive pay, job security, and continuous learning and development. The Bureau of Labor Statistics (BLS) reports that the average annual salary for computer and AI professionals is $126,830.

An integrated, comprehensive and exclusive B2B2E (business to business to enterprise) health benefits and wellness platform, ekincare works to solve health benefits problems making it a complete ecosystem with a unique model integrating healthcare, tech and insurance. Healthtech had a tipping point during the pandemic. Today, the sector has a massive opportunity towards making healthcare more inclusive and accessible. Corporates have made health and wellness initiatives their board-level priorities. The ultimate beneficiary is the end consumer and in the case of B2B (business to business), it is the employees and their dependents.

Andela exists to connect brilliance and opportunity. Since 2014, we have been dedicated to breaking down global barriers and accelerating the future of work for both technologists and organizations around the world. For technologists, Andela offers competitive long term career opportunities with leading organizations, access to a global community of professionals, and education opportunities with leading technology providers. For companies, Andela provides access to a global network of fully integrated team members that unlock their business' innovation and growth potential. At Andela, we are deeply passionate about creating long-lasting and transformative growth opportunities for all and doing it in an E.P.I.C. [andela.com/careers]

Stripe is a financial infrastructure platform for businesses. Millions of companies--from the world's largest enterprises to the most ambitious startups--use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP o the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. The Machine Learning Infrastructure organization provides infrastructure and support to run machine learning workflows and ship to production, tooling and operational capacity to accelerate the use of these workflows, and opinionated technical guidance to guide our users onto successful paths.

ActivTrak is a cloud-based platform that provides productivity insights into how teams work, improving employee and customer experience, while also enabling better business outcomes. At ActivTrak, we recognize the powerful link between these two concepts and we're on a mission to understand it more every day. Alongside 9500 paying customers, our team uses the platform internally to assess team and organizational performance, hone product features, develop best practices, streamline processes, invest in new innovations, and promote a culture of immediate feedback and transparency. We are a fast-growing, agile company with a forward-thinking, inclusive culture. Our teams are encouraged to collaborate daily to solve challenges, create and champion new ideas, and execute initiatives that help global customers and their modern workforces succeed by working better together.

New and continuously improving treatment options such as thrombolysis and thrombectomy have revolutionized acute stroke treatment in recent years. Following modern rhythms, the next revolution might well be the strategic use of the steadily increasing amounts of patient-related data for generating models enabling individualized outcome predictions. Milestones have already been achieved in several health care domains, as big data and artificial intelligence have entered everyday life. The aim of this review is to synoptically illustrate and discuss how artificial intelligence approaches may help to compute single-patient predictions in stroke outcome research in the acute, subacute and chronic stage. We will present approaches considering demographic, clinical and electrophysiological data, as well as data originating from various imaging modalities and combinations thereof. We will outline their advantages, disadvantages, their potential pitfalls and the promises they hold with a special focus on a clinical audience.

The last decade has seen the increasingly important, even dominant, application of deep learning (DL) in the field of various applications. Conventional machine learning methods have been the focus of intense investigations for years; however, they have limited capabilities, are biased to dataset selection, and are faced with an overwhelming challenge to integrate large, heterogeneous data sources. On the other hand, recent advancements in deep learning architectures, coupled with high-performance computing, have demonstrated significant breakthroughs in dealing with complexities by radically changing research methodologies toward a data-oriented approach. This Special Issue encourages authors, from academia and industry, to submit new research results about positioning and navigation models based on machine learning for complex systems. Manuscripts should be submitted online at www.mdpi.com

Ireland has appointed Dr Patricia Scanlon as its first AI Ambassador to facilitate the Government's AI adoption strategy launched last year. Patricia is the founder and former executive chairperson of the speech recognition tech firm called SoapBox Labs. Ireland's'AI – Here For Good' strategy focuses on how technology can be utilised in human-centric and ethical ways to improve the lives of its citizens. Dr Scanlon, a member of the Enterprise Digital Advisory Forum (EDAF), will work closely with the Department of Enterprise, Trade and Employment. She will work on demystifying AI and promoting the positive impacts it can have in areas such as transport, agriculture, health and education.

For humans, working with deformable objects is not significantly more difficult than handling rigid objects. We learn naturally to shape them, fold them, and manipulate them in different ways and still recognize them. But for robots and artificial intelligence systems, manipulating deformable objects present a huge challenge. Consider the series of steps that a robot must take to shape a ball of dough into pizza crusts. It must keep track of the dough as it changes shape, and at the same time, it must choose the right tool for each step of the work.

Much work has been done within artificial intelligence (AI) to better understand how the human brain works to make AI more efficient. When you use a search on Google or Amazon, or you type on a phone or tablet, a piece of technology known as predictive language model is being used. This AI-driven functionality is what allows technology to be able to predict the next word within a string of text. The most recent generation of these predictive language models also learns the underlying meaning of languages, such as question answering or story completion. Could these AI next-word prediction models provide insight into how the brain processes language? This is what a team of cognitive neuroscientists from MIT wanted to explore.