Governments are paying growing attention to the potential of artificial intelligence – the simulation of human intelligence processes by machines – to enhance what they do. To explore how public authorities are approaching the use of AI for tasks related to public finances, Global Government Fintech – the sister title of Global Government Forum – convened an international panel on 4 October 2022 for a webinar titled'How can AI help public authorities save money and deliver better outcomes?'. The discussion, organised in partnership with SAS and Intel, highlighted how AI is already helping departments to deliver results. But also that AI remains very much an emerging and, to many, rather nebulous field with many hurdles to clear before widespread use. "Discussions of artificial intelligence often bring up connotations of an Orwellian nature, dystopian futures, Frankenstein…" said Peter Kerstens, advisor, technological innovation & cyber security at the European Commission's Financial Services Department.

He overcame surrender and did not despair despite his projects having been rejected, at the beginning of his career, but eventually became an entrepreneur in technology across Middle East-wide through his company "WideBot," which specializes in artificial intelligence "AI" and its influential role in customer relationship management (CRM) and digital business management. He is "Mohamed Nabil," a 35-year-old, from Alexandria who graduated from the Faculty of Computer and Information Science, Mansoura University in 2007. Immediately after graduation, he began to think seriously about how to start his own business, he had already set up companies, some companies have failed miserably and some have succeeded, but it was not a great and overwhelming success. During Mohamed's struggle, he supported him and stood by his side, Ahmed was his college friend, and he is also with his technical co-founder. And their work on that idea took about two years, they presented their idea to more than one large supermarket in Egypt and abroad, but unfortunately, it was not successful enough and the idea of their project was very new to the market.

Artificial intelligence (AI) may be a distant and little-known subject for some people, but the reality is that it is much closer than many people believe. Through Artificial Intelligence, it is possible to combat violence against women; assist lawyers, law firms, and departments with document analysis and monitoring of changes in legislation; assist clients with financial matters; make farmers have better productivity; help the elderly to have a better quality of life, among thousands of other things. AI advancements will be no less significant. For example, AI will soon be able to accelerate drug discovery and green energy research. According to Andrew Ng, one of the world's leading AI experts, AI's advancement can add more than $10 trillion to the global economy by 2030. Many people fail to recognize that this isn't necessarily a bad thing or something to be afraid of.

Not only does Starbucks go through mounds of coffee beans to satiate its raving fans, but they also have mounds of data that they leverage in many ways to improve the customer experience and their business. With 90 million transactions a week in 25,000 stores worldwide the coffee giant is in many ways on the cutting edge of using big data and artificial intelligence to help direct marketing, sales and business decisions. When Starbucks launched its rewards program and mobile app, they dramatically increased the data they collected and could use to get to know their customers and extract info about purchasing habits. The mobile app has more than 17 million and the reward program has 13 million active users. These users alone create an overwhelming amount of data about what, where and when they buy coffee and complementary products that can be overlaid on other data including weather, holidays and special promotions. Here are just some of the ways that Starbucks uses the data it collects.

In tech, this was officially the year we saw artificial intelligence engines leading consumer product lines. Most notable was the role AI played in Google's portfolio. Many products launched with Google Assistant built in, but it wasn't until the end of 2017 that we realized the role AI would play in driving Google's marketing. From its smartphones to its laptops and smart speakers, even its new earbuds, Google Assistant and its contextual abilities quickly became the reason to bring home a Google product. The Google Assistant exists in this array of devices. It was Forbes that initially pegged 2017 as "The Year of Artificial Intelligence."

While artificial intelligence (AI) has become widespread, many commercial AI systems are not yet accessible to individual researchers nor the general public due to the deep knowledge of the systems required to use them. We believe that AI has matured to the point where it should be an accessible technology for everyone. We present an ongoing project whose ultimate goal is to deliver an open source, user-friendly AI system that is specialized for machine learning analysis of complex data in the biomedical and health care domains. We discuss how genetic programming can aid in this endeavor, and highlight specific examples where genetic programming has automated machine learning analyses in previous projects.

BEIJING, May 25, 2017 (GLOBE NEWSWIRE) -- Gridsum Holding Inc. ("Gridsum" or the "Company") (NASDAQ:GSUM), a leading provider of cloud-based big-data analytics, machine learning and AI solutions in China, today announced that, as a part of its strategic evolution, it has consolidated all of its artificial intelligence ("AI") activities strategically, technically and organizationally into a new division called the Gridsum Prophet. Gridsum is a first mover in China in big data intelligence. Since 2005, the Company has utilized a distributed big-data computing architecture, developed and implemented sophisticated natural language processing ("NLP"), and leveraged machine learning directed toward large enterprise clients. During that time, from serving large enterprise customers, the Company has accumulated deep domain knowledge and expertise as well as a massive amount of data that fuels its machine learning algorithms. Since this early inception, the Company has continued to stay at the forefront through focus and investment, hiring and training extraordinary engineers and architects and, importantly, playing an active and leading role in the AI academic and developer communities.

Google began rolling out a feature that gives searchers in the United States the potential to access more relevant and in-depth responses to answers without leaving the page. The concept is built on something the company calls "knowledge graph," which ties together words to create relationships. There are a multitude of sources behind this data. The search results page displays a variety of content related to keyword queries, bringing up a list of facts, photos, and landmarks, as well as quick links to other popular uses for the search term. Think of a Web beneath the user interface layer of the Internet that ties together all information across the Web. Rob Garner, vice president of strategy at agency iCrossing, said Google's knowledge graph takes another step in the company's long transition to develop an artificial intelligence engine -- semantic search.

Today, we are just beginning to scratch the surface of what is possible with artificial intelligence (A.I.) and how individuals will interact with its various forms. Every single aspect of our society -- from cars to houses to products to services -- will be reimagined and redesigned to incorporate A.I. A child born in the year 2030 will not comprehend why his or her parents once had to manually turn on the lights in the living room. In the future, the smart home will seamlessly know the needs, wants, and habits of the individuals who live in the home prior to them taking an action. Before we arrive at this future, it is helpful to take a step back and reimagine how we design cars, houses, products, and services. We are just beginning to see glimpses of this future with the Amazon Echo and Google Home smart voice assistants.

Bumping a prospect's talk-time from 22% to 33% delivers a sharp increase in win-rates If pricing comes up 3–4x in a call, consider it a buying signal Top sales professionals typically discuss pricing late in the call (40–49 minutes in on average) When your prospect responds to your timeline question with the word "probably," consider it a good thing When prospects respond to your timeline question with the phrase "We need to figure out X," you've got your work cut out for you When you sooth your prospect's fears with risk-reversal language (such as "you can cancel at any time"), win-rates on average increase 32% Conversation-level sales coaching leads to higher win-rates, more revenue, and shorter sales cycles Bumping a prospect's talk-time from 22% to 33% delivers a sharp increase in win-rates