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) …
As you plan your agenda, artificial intelligence (AI) is undoubtedly a hot topic on your list. This year we have a lot of great technical content on AI, machine learning (ML), and deep learning (DL)--with over 200 breakout sessions, hands-on workshops, deep-dive chalk talks, and more. You'll hear success stories about machine learning on AWS firsthand from customers and partners such as Sony, Moody's, NFL, Intuit, 21st Century Fox, Toyota, and more. This year's re:Invent also includes the AI Summit, where thought leaders in the academic community will share their perspectives on the future of AI. Here are a few highlights of this year's lineup from the re:Invent session catalog to help you plan your event agenda.
But Mica, the company's artificial intelligence, really deserves attention. With "Mica", the augmented reality company Magic Leap has introduced the next evolution of virtual assistants. In contrast to Cortana, Alexa or Siri with their disembodied voices, Mica has an incredibly real avatar. She yawns, makes eye contact and interacts with the wearer using Magic Leap's augmented reality glasses. At the time of Alexa, Siri or Cortana we are used to having ubiquitous but disembodied vocal assistants.
Finance departments have been racing around for decades to try to keep up with the increasing quantity and complexity of information. But the data and workloads keep growing. APQC's recent annual survey, "Where Does the Time Go in Finance?" shows that in spite of significant success reducing costs, transaction processing takes up almost half of a finance department's time. This could be holding finance teams and their leaders back from taking on a more strategic role in emerging digital business models. As APQC put it: "This means that in an average work week, highly paid finance staff are spending the equivalent of Monday morning through lunchtime on Wednesday making sure that bills get paid, customers get accurate invoices, general accounting work gets done and fixed assets are accounted for, among many other tasks that keep the money moving through an organization."
Google Assistant might soon have its own list- and note-taking functions instead of leaning on third-party apps. The 9to5Google team has sifted through the Google search app's code to discover an unannounced "Lists and Notes" web app for Assistant that lets you jot down important information to sync across devices. It's extremely basic (you can't do much more than add titles), but there's a degree of polish that suggests it's not just an experiment. It's not clear if or when Google might put this app into service. Any such move might leave people scratching their head -- if you already use Google Keep or Google Tasks, why switch to this?
Morgan Stanley is one firm experimenting with how these new technologies can be applied to better manage clients' money. Artificial intelligence refers to the ability for computer science to be applied in ways that replace human intelligence. Financial firms -- ranging from big Wall Street names like Morgan Stanley to robo-advisors and start-ups -- are all taking a look at how tools such as algorithms, data mining and natural-language processing can help you become wealthier. Morgan Stanley formally launched its initiative -- called Next Best Action -- to its more than 15,000 financial advisors earlier this year. Including the firm's service employees, more than 20,000 have access to the tools.
GitHub is used by more than 30 million developers around the world and hosts repositories for some of the biggest ML-driven open source projects on the planet, but is perhaps less well known for the creation of AI-driven tools to help them do their jobs. VentureBeat sat down with GitHub senior data scientist Omoju Miller to talk about how one of the biggest homes for developers online is performing applied machine learning research to create more AI-driven services. At the GitHub Universe conference Tuesday, a number of major upgrades were made to GitHub and GitHub Enterprise services for businesses. Miller also spoke during the keynote address about Experiments, a new GitHub initiative to explore the use of AI and machine learning meant for developers. The first Experiments prototype named Semantic Code Search launched last month.
CES 2017 was set to be the biggest so far, with more exhibitors, products, and visitors than ever before in its 50 year history. But one signal sparked my interest above everything else: increasing focus on how technology brings value over technology per se. It was hard to find anything not labeled "smart" or "intelligent" this year. While just a year ago AI seemed futuristic, people now expect it … and expect it to work straight out of the box. This is because we've reached sufficient maturity in what I call the 4Cs of useful AI: computing, connectivity, cognition, and convergence.
Pattern recognition using machine learning methods is an area that exploded in recent years, given the increasing amount of available data. JAMIA has published an increased number of articles in this area in the past few years. Machine learning models to detect pulmonary nodules in CT scans are described by Grutzemacher (p. Developing new approaches to facilitate automation of clinical research is another area in which informatics has evolved considerably in the past few years. In particular, biomedical natural language processing and other methods to structure narrative text and voice recordings have motivated informatics research.
Text-based analytics, also known as text data mining, turns unstructured text into structured data that can be used in a multitude of ways by any business. Indian research firm MarketsandMarkets projects that the worldwide text-based analytics market will grow to 8.79 billion dollars by 2023, driven by major vendors like IBM and SAP. MarketsandMarkets continues that text analytics solutions empower users to perform quick data extraction and categorization with real-time insights from stored data and that the growing importance of insights generated from social media content to build effective marketing campaigns and enhance customer experience drives the market's growth. But while many companies are including text-based analytics to their roadmaps, the technology remains in the early stages of adoption. One reason for this is because companies are still struggling to master social media.