Personal healthcare experiences often spark pioneering cures, and Pinaki Dasgupta, CEO of Hindsait, is no exception. After two immediate family members weathered serious health issues, Dasgupta brought his digital expertise in manufacturing to the healthcare industry. His cloud-based startup is designed to help insurance companies and healthcare organizations reduce costs while boosting patient health by replacing manual reporting, preauthorization, and audits with AI-based automation. Pinaki Dasgupta, CEO of startup Hindsait, is convinced that using AI to augment people will revolutionize healthcare decision-making through evidence-based care. At last official count, healthcare spending in the U.S. alone totaled almost 18 percent of the country's gross national product (GDP), an astounding amount.

Almost every business leader I know has begun to -- or is pondering the best way to -- incorporate artificial intelligence (AI) into their 2020 growth plan. Clearly, AI is sweeping the globe and "helping to drive the next great economic expansion," as Deloitte noted in its 2019 international survey of AI's early adopters. Nearly two-thirds of the executives surveyed for the report said AI technology is "very" or "critically" important to the success of their businesses, and most said that AI will help them move ahead of competitors who have been slower to adopt the technologies. Large companies are all over it, using AI to win customer loyalty by creating highly personalized experiences. Can startups and other small firms use AI and advanced analytics effectively without wasting precious time and money on technologies that even the experts are still working to operationalize?

For CenturyLink, customer surveys play an important role in understanding the customer experience. But, in the past, without the ability to analyze the unstructured data in these surveys, customer service teams couldn't drill down to identify the nature and characteristics of issues. "Using unstructured data is really important for us because that's where the real detail -- the meat -- comes in," said Beth Ard, vice president of customer experience at the Louisiana-based network services provider. "When you do scoring, for example, you don't have enough actionable insight to make the changes that you need without it." Most business analytics processes require clean and well-structured data, but enterprises are increasingly managing unstructured data formats -- emails, chat transcripts, audio and video, and social media posts.

Sunny California seems to be the global pacemaker of major innovations in the IT and high–tech industries: The Internet giants Google, Facebook, Apple and Amazon, like many other tech companies, have their headquarters in Silicon Valley. The innovative start–up scene in the Bay Area is at the forefront of developments in artificial intelligence (AI) – closely followed by China. And where do we stand? How does the German economy manage to keep up in the race? Germany & Silicon Valley: Shaping a shared digital future" in Mountain View, leading voices from politics, business and science have conducted a global assessment of the current situation. We participated in the conference with the project "FutureWork360". The aim of the project is to use virtual reality to make our innovation laboratories accessible worldwide on an Internet platform and thereby promoting international networking. For three days, the Computer History Museum – not far from Google's headquarters – was transformed into a forum for the exchange of knowledge on AI. Leaders from the digital economy, research and politics came together to discuss how Germany and the Silicon Valley can work together to harness the tremendous opportunities of AI, robotics and other new digital technologies while effectively addressing the social, economic and political challenges they present. Because we are in the midst of a huge social upheaval – we are walking into a future in which AI–controlled machines think, make decisions and perform tasks, which we once thought were clearly "human". The USA is the breeding ground of digital talent among all countries with about 3000 PhD students per year in the field of AI (for comparison: in Germany there are about 170). Furthermore, five of the top ten and 134 of the 500 most powerful commercially available supercomputers are currently located in the US. The largest number of AI start–ups also gather there. Three–quarters of all internationally enforced AI patents were filed by US players, compared to only two percent from the German counterparts. The figures show how urgent it is for Europeans, and especially Germans, to catch up in the key technology of artificial intelligence. Christoph Keese, CEO of Axel Springer hy GmbH, summarizes the situation in his words: "We must finally wake up and stop investing so little in AI.

The global internet of things (IoT) in manufacturing market size was USD 27.76 Billion in 2018 and is projected to reach USD 136.83 billion by 2026, exhibiting a CAGR of 22.1% during the forecast period. The internet of things (IoT) in manufacturing comprises mechanical and electrical parts, advanced sensors, network connectivity architecture, controls, software applications, and smart devices that work together to collect and share real-time information between machines and humans. The internet of things (IoT) in manufacturing industry is gaining robust growth due to the rising adoption of AI (Artificial Intelligence) and other connected devices based on machine learning (M2M, M2P). Implementation of IoT technology in manufacturing industry is providing several organizations with new opportunities including digital transformations techniques and is enabling them to upgrade the current running operations by creating and tracking new business models. Furthermore, IoT solutions help in providing manufacturers a comprehensive vision to monitor complexities keep on arising at every intermediate point in the manufacturing process and assist in developing real-time adjustments.

AI Day poster sessions highlight current, top-level research in fundamental AI methodologies as well as AI applications in industry and society. Coffee is served during the poster sessions.

Cancer is the second leading cause of death worldwide[i], with an estimated 18.1 million new cases and 9.6 million deaths attributed to it in 2018[ii]. The search for more effective anti-cancer drugs is a global effort involving academia and industry. In our Computational Systems Biology group at the IBM Research lab in Zurich, we are building machine learning approaches that can potentially help to accelerate our understanding of the leading drivers and molecular mechanisms of these complex diseases, as well as the differences in tumor composition occurring across various cancer types. Our goal is to deepen our understanding of cancer to equip industries and academia with the knowledge that could potentially one day help fuel new treatments and therapies. At the 18th European Conference on Computational Biology (ECCB) and the 27th Conference on Intelligent Systems for Molecular Biology (ISMB) to be held from July 21 -25 in Basel, Switzerland, IBM will present significant, novel research that led to the implementation of three machine learning solutions aimed at accelerating and guiding cancer research.

One of the most important innovations in the present era for the development of highly-advanced AI systems has been the introduction of Reinforcement Learning (RL). It has the potential to solve complex decision-making problems. It generally follows a "trial and error" method to learn optimal policies of a given problem. It has been used to achieve superhuman performance in competitive strategy games, including Go, Starcraft, Dota, among others. Despite the promise shown by reinforcement algorithms in many decision-making problems, there are few glitches and challenges, which still need to be addressed.

Today, Mozilla and the German Ministry for Economic Cooperation and Development (BMZ) have announced to join forces in the collection of open speech data in local languages, as well as the development of local innovation ecosystems for voice-enabled products and technologies. The initiative builds on the pilot project, which our Open Innovation team and the Machine Learning Group started together with the organization "Digital Umuganda" earlier this year. The Rwandan start-up collects language data in Kinyarwanda, an African language spoken by over 12 million people. Further languages in Africa and Asia are going to be added. Mozilla's projects Common Voice and Deep Speech will be the heart of the joint initiative, which aims at collecting diverse voice data and opening up a common, public database.

Even if you don't have a chatbox on your website, you have definitely encountered one before. Facebook, eBay, Domino's Pizza, and Universal Studios are some of the big names that have their own chatbots. With the advancements in AI, mundane tasks like customer service can easily be handled by a chatbot. Some people reject the merit of chatbots stating that communicating with them feels very impersonal. According to the 2018 State of Chatbots Report by Salesforce, 69% of consumers said they preferred communicating with chatbots.