If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Livongo is the leading Applied Health Signals company, partnering with over 800 clients to serve more than 250,000 members. One of Livongo's unique strengths is the suite of tools that enable our members to monitor not only their behaviors, but also their bodies -- for example, their blood glucose, blood pressure, and weight. These data streams provide vital clues into where each member is on their journey towards living a healthier and happier life -- and how Livongo can best provide support and guidance in an adaptive, just-in-time fashion. This role is focused specifically on furthering Livongo's ability to do more with our devices and their data streams, including: The Transformative Name in Healthcare: The transformative industry forces in Community, Content and Commerce are now household names. As Amazon is to Commerce, Livongo is to Healthcare.
Artificial Intelligence and Machine Learning have been making our lives easier for quite some time. Today, we're going to talk about Python For AI & Machine Learning. Though the community keeps discussing the safety of its development, at the same time it is working relentlessly to grow the capacity and abilities of AI and ML. The demand for AI is at its peak, as it is highly used in analysing and processing large volumes of data. Due to the high volume and intensity of this work, it cannot be handled and supervised manually. AI is used in analytics for data-based predictions that enable people to come up with more effective strategies and strong solutions. FinTech applies AI in investment platforms to conduct market research and make predictions about where to invest funds for greater profits. The travel industry utilises AI to launch chatbots and make the user journey better. Python Web App Examples are proof of that. Due to such high processing power, AI and ML are absolutely capable of providing a better user experience, that is not only more apt but also more personal, making it more effective than ever.
Autonomous truck startup TuSimple today announced a strategic agreement with the Traton Group, a Munch, Germany-based Volkswagen Group subsidiary. As a part of it, TuSimple plans to launch a development program to operate an autonomous hub-to-hub route between Södertälje to Jönköping in Sweden using Scania trucks manufactured by Traton. As for Traton, the company says it has taken a minority stake in TuSimple and will work with the startup to develop driverless systems for Traton-branded trucks, with the goal of testing self-driving truck fleets on roads throughout Sweden, Germany, and other European countries. Some experts predict the coronavirus outbreak will hasten the adoption of autonomous delivery solutions like TuSimple's. A study published by CarGurus found that 39% of people won't use manually driven ride-sharing services post-pandemic for fear of insufficient sanitation.
Limited access highways have been accepted as a mechanism to optimize transport for many years. According to the Transportation Research Board (TRB), limited access highways offer greater capacity; improved safety; reduced fuel consumption; less pollution; more positive impacts on motorists; and more positive impacts on neighborhoods. From the point-of-view of autonomy, limited access highways offer use-models with a significant reduction in complexity. Not surprisingly, many of the initial applications for autonomy have focused on highways. In passenger cars, the focus has been on functionality such as advanced cruise control with underlying capabilities such as lane-keeping and of course collision avoidance.
Artificial intelligence (AI) is increasingly being recognized as the future of customer service. This way of thinking has only been accelerated by the ongoing pandemic as needs for efficiency, agility and productivity continue to rise. But what about robotic process automation (RPA), which is conventionally thought of as a "human replacement"? I'm here to tell you that RPA is a burgeoning application that's leveraging AI, especially AI-driven analytics, to automate tasks. When combined, the two can be used as business and innovation accelerators that not only improve the employee experience, but the customer experience as well, leading to improved customer loyalty, brand reputation and overall bottom-line results.
The development of the internet over the last few decades has resulted in a massive increase in the production of data and the unprecedented availability of computing power for corporate applications. Machine Learning and artificial intelligence (AI) techniques have been fuelled by these revolutions to emerge from being purely academic topics of investigation to be the basis for a new wave of products and services for the digital age. The paradigm-shifting opportunities presented to corporates by this emerging technology range from the ability to expose and extract insights and patterns from data lakes to replacing human beings in critical decision-making scenarios. However, with these opportunities also come novel risks and concerns that must be considered when contemplating the development and deployment of AI and machine learning agents. These include understanding how their trustworthiness may be measured, the ethics and policies required for their deployment and the cybersecurity implications of their widespread adoption.
Elderly people living today are fitter and healthier than they were 30 years ago, according to a study by Finnish researchers. As a result of better nutrition, hygiene and healthcare people between 75 and 80 now walk, on average, almost 1mph faster than they did in 1990. The oldest members of society also have greater leg and grip strength in the modern era, as well as improved reaction speed, verbal fluency, reasoning and memory. Finnish researchers compared data on 500 people born between 1910 and 1914, who were tested between 1989 and 1990, with 726 people born in 1938 or 1939 and tested in 2017 and 2018. The same tests were administered to both groups and assessed physical state as well as cognitive function.
The human microbiome consists of a community of trillions of micro-organisms, such as bacteria, fungi, viruses, and live all over the body including on the skin, in the mouth and along the digestive tract. A balanced microbiome is important for an individual's health and wellbeing, including proper functionality the digestive and immune systems. The human microbiome is constantly evolving and has been observed to change with age. The presence of unusually early microbiome aging patterns, relative to chronological age, could potentially signal altered susceptibility for age-related diseases. Conversely, a "young" microbiome might offer clues on how to decelerate the aging process1.
AI Alignment through anthropology: How social science can steer AI towards better outcomes Guest article by Anna Leggett, Senior Research Consultant, and Morgan Williams, Junior Consultant, Stripe Partners. If an advanced AI system were instructed to make paper clips, or to fetch coffee, we would not want it to
On Tuesday the 7th of July we virtually welcomed 10 professionals from across different industries involved with human resources, innovation, and management strategy for our first Risk Classification Framework Workshop. Organisations are searching for the right approach to evaluating AI systems for the potential harms they could cause. At the Institute for Ethical AI (IEAI), we have been exploring the potential of using a risk-based governance approach to provide appropriate oversight for systems that use probabilistic reasoning. An essential part of risk-based governance is understanding what causes higher risk and how changes in technology or governance can mitigate those risks. We have been running a series of workshops to gather the views of professionals on how to approach classifying risk.