AI News, BOOK REVIEW: 10 predominant Artificial Intelligence trends in 2019

A Cancer Vaccine is Being Developed in Dogs; Humans May Be the Next to Receive it

Cancer vaccines have long been a topic of debate, because cancer is an incredibly complex disease, making the creation of a vaccine–let alone one able to cover multiple cancers–seemingly impossible.

According to Thamm, cancer is the predominant cause of death in adult dogs, who spontaneously develop tumors as they get older, in a process similar to the way humans often develop cancer.  On a molecular level, many human and canine cancers are comparable as well, largely due to the fact that we live in the same environments.

Thamm told CNN that there are three potential outcomes: that cancer will be delayed, appear at a lower incidence, or that the vaccine has no effect.  This model has actually worked in the past: the cancer drug known as Imbruvica was tested in dogs before it was fine tuned for humans.  However, even if the vaccine does work in canines, the team will have quite the battle achieving clearance to run a similar clinical trial in humans.

Artificial Intelligence and Marketing | Skoda Minotti

The purpose of a marketing solution is to directly address a specific business-related challenge.

AI has become a driving force in popular culture over the past 10 or so years, and it’s also made its way into the marketing world by helping to usher in a future of marketing automation.

For example, in 2010, IBM launched Watson, a SaaS-based digital marketing automation platform that uses behavioral data from any source to create campaigns across email, web, mobile push, SMS, social and group messaging.

Big Data can be used to identify the needs and wants of clients and customers by providing insights into key areas like engagement, retention, loyalty, marketing optimization and performance.

It can also include objective metrics that measure the quality of marketing processes in areas such as marketing operations, resource allocation, asset management and budgetary controls.

AI like Watson can help tease out more insightful data by automating processes to gain efficiencies, and provide indisputable proof that the data used by the AI system is useful.

Every business wants to provide the best client experience possible, but human interactions with those experiences have created a flawed system with the potential for inaccuracy and delays.

AI can take the data held by an organization about its client and their experiences, and help create a consistent, accurate and holistic representation of that data for process improvement analysis.

Chatbots are a perfect example of an AI-based conversation agent designed to simulate human interactions, and eliminate frustrating delays and errors typically found in real-time client service.

Artificial intelligence

TheWorld Intellectual Property Organization’s (WIPO)first report of a series calledWIPOTechnology Trends, an extensive study of patent applications and other scientific documents, offers clues to the next big thing in AI.

Rather than treating ‘AI’ as a single homogeneous discipline (see our guide to AI terminology), the WIPO report divides it into AI techniques, AI functional applications and AI application fields , offering a finer-grained analysis.

AI techniques are advanced forms of statistical and mathematical models used in AI, including machine learning, logic programming, ontology engineering, probabilistic reasoning and fuzzy logic.

The other top areas are natural language processing (14 per cent of all AI-related patents) and speech processing (13 per cent), although applications related to robotics and control methods are also emerging fast (WIPO Technology Trends 2019, p.

AI plays the most important role in transportation (15 per cent of all AI-related patents), telecommunications (15 per cent), and life and medical sciences (13 per cent).

Just recently, the UK IP office has published a similar report on AI patenting trends which is in line with the WIPO’s findings and confirms that the next big thing in AI investment and development is indeed in these areas (see our blog post on the UK report).

Currently, two-thirds of AI patents are filed at a single office, while 9 per cent are filed in five or more jurisdictions, and just 0.6 per cent are filed at more than 10 offices.Patent applications will likely become more international, not least because of the Patent Cooperation Treaty (PCT) system, which allows filing in multiple jurisdictions (including Europe) through a single application (WIPO Technology Trends 2019, p.

The sub-category of neural networks is highly relevant for machine learning, and – according to the report – the largest portfolios explicitly naming this technology belong to Siemens and State Grid Corporation of China (SGCC) with 677 and 650 patent families, respectively.

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