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) …
Many companies are swimming in data, and they are spending millions to collect more. But even with new tools and algorithms to analyze and make predictions based on consumer data, it's often still not being used effectively. Customer Analytics for Growth is for business leaders who want to cultivate an analytics-based mindset throughout their organization, and gain a deep understanding of emerging AI technologies that are rapidly changing businesses today. In Customer Analytics for Growth, you will explore the upside -- and the downside -- of complex data models, and understand the importance of transparency in data collection and analysis. A distinctive highlight of Customer Analytics for Growth is engaging in discussions with expert practitioners from a range of industries who have experience with both business-to-consumer and business-to-business customer models.
AI and Big Data in Cancer: From Innovation to Impact, a new conference from Elsevier, a global information and analytics business specializing in science and health, will bring together experts from all aspects of cancer research and the digital medicine value chain to understand how to translate artificial intelligence and data-driven innovations into new clinical care practices for patients. These leaders, including 2018 Nobel Laureate for Medicine, Dr. James Allison, will share pragmatic insights on finding the right partners to move innovations successfully forward. "It is time to shift our conversation from'what-technology-can-do' to'what-medicine-needs' and to raise awareness of what else is necessary to translate an AI-enabled and data-driven innovation into a marketed product," said Dr. Lynda Chin, Conference Chair, Founder and CEO of Apricity Health and Professor at Dell Medical School at the University of Texas, USA. "Understanding what these hurdles are is the first step to overcoming them. "The aim of this conference is to bring innovators together with stakeholders, from patients, clinicians and developers to regulators, payers and investors, so they can network and identify collaborators who can help them accelerate the translation of their innovation into clinical practices," Dr. Chin said. "Insights from the program's 40 key opinion leaders will advance the emerging digital medicine industry, building bridges from computer to clinics," said Laura Colantoni, Vice President for Reference Content, Elsevier, and one of the main organizers for the conference. "We are particularly excited about establishing this conference as a venue for successful innovators, influential facilitators, regulators and payers, as well as investors to find, engage and collaborate with clinicians, researchers and patients to accelerate progress in this area.
Today's managers and executives need to oversee humans and machines in this age of AI and RPA, but should machines be managed as humans in a way that some suggest? As artificial intelligence and robotics process automation (RPA) usage continue to expand in enterprises, managers and executives need to learn how to supervise more than just human employees. They need to manage the human-machine workforce. Some suggest that intelligent machines should be managed like people. More specifically, they suggest that, like people, virtual employees should have a job title and key performance indicators (KPIs).
Snyk, a cybersecurity platform that helps developers find vulnerabilities in their open source applications, has raised $150 million in a round of funding led by New York-based private equity firm Stripes, with participation from Salesforce Ventures, Coatue, Tiger Global, BoldStart, Trend Forward, and Amity. This takes Snyk's total funding to $250 million from backers including Alphabet's GV and Accel, including a $22 million series B round in 2018 and a $70 million follow-on round just a few months ago. A Snyk spokesperson said that the company is now worth more than $1 billion, which is at least double the $500 million it was valued at back in September. Founded in 2015, London-based Snyk targets developers -- rather than cybersecurity personnel -- to help them find and fix flaws in their source code, as well as their containers and Kubernetes applications. The developer connects Snyk to a code repository in the likes of GitHub, GitLab, or Bitbucket, and Snyk then scans for vulnerabilities (or license violations), providing a description of the problem, noting where the flaw lies in the code, issuing a severity rating, and even suggesting a fix.
AI has the capacity to maximise the social, economic, and environmental benefits of big data sources for decision-making. Researchers, governments, companies, non-governmental organisations, and citizen groups are actively experimenting, innovating, and adapting AI tools to tackle policy relevant problems. Research and development are needed to properly design sound theoretical methods and applied tools for generating policy relevant information, implementing policy objectives, designing more effective policies, or measuring their impact while mitigating potential risks.
Once you've got your data lake established, you can provide various functions in your enterprise such as business analysts, solution architects and data scientists with secure and appropriate access to your entire catalogue of data. With a choice of analytics tools, such as HD Insights from Azure, you can empower these teams to effortlessly process massive amounts of data and use a range of open sources tools for analytics. You can then extend these tools to generate valuable insights from historical and real-time data, creating machine learning models to conduct automated key driver and root cause analysis as well as forecasting predicted business outcomes.
Data science jobs are one of the highest paying jobs of this decade. The democratization of analytics tools along with the rise in reading resources has drawn more attention towards this thriving sector. In India, data science jobs are on a rise as every company from startup to industry leaders are incorporating algorithmic solutions into their workflows. In this article, we bring you top 10 data science jobs in Bengaluru -- the Silicon Valley of India. This job is for those who like to write smart algorithms and deal with complex problems that require a mix of AI/ML, big data, computer vision, NLP and a dash of probability and statistics to solve.
This seems like an obvious one, but with so many potential areas for AI exploration, starting with the right projects--and stakeholders--is crucial for long-term success. First and foremost, the process of identifying and selecting use cases shouldn't be driven by technology alone. That is, you don't want to think about AI solely in terms of where you can apply natural language processing, for example, or how you can leverage a labeled data set. Instead, ask where you seek to increase productivity or derive new value. Going through the questioning exercise above with the various leaders who may own or touch AI, such as the chief information officer, chief digital officer, chief data scientist, and other specialists (see #3), will enable you to identify where to start.
Yes, companies use AI to automate various tasks, while consumers use AI to make their daily routines easier. But governments–and in particular militaries–also have a massive interest in the speed and scale offered by AI. Nation states are already using artificial intelligence to monitor their own citizens, and as the UK's Ministry of Defence (MoD) revealed last week, they'll also be using AI to make decisions related to national security and warfare. The MoD's Defence and Security Accelerator (DASA) has announced the initial injection of £4 million in funding for new projects and startups exploring how to use AI in the context of the British Navy. In particular, the DASA is looking to support AI- and machine learning-based technology that will "revolutionise the way warships make decisions and process thousands of strands of intelligence and data."
Birds do not collide when they fly in flocks. We may wonder how they do not and how they flock in a self-organized and well-orchestrated movement. It is a collective intelligence that is encapsulated within the interactions between the birds and the environment. The cohesive self-organized movement of a biological swarm such as flocking birds is commonly studied. Such phenomena have had successful applications in robotics and autonomous vehicles, and it has attracted a renewed interest from the Artificial Intelligence and the Predictive Analytics communities.