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) …
This is his seminal paper originally published in 1959 where Samuel sets out to build a program that can learn to play the game of checkers. Checkers is an extremely complex game - as a matter of fact the game has roughly 500 billion billion possible positions - that using a brute force only approach to solve it is not satisfactory. Samuel's program was based on Claude Shannon's minimax strategy to find the best move from a given current position. In this paper he describes how a machine could look ahead "by evaluating the resulting board positions much as a human player might do".
Results: A total of 10 688 adult patient samples representing 40 untreated primary tumor types and 26 adjacent-normal tissues were used for training. Demographic data were not available for all data sets. Among the training data set, 5157 of 10 244 (50.3%) were male and the mean (SD) age was 58.9 (14.5) years. An accuracy rate of 99% was obtained for primary epithelioid mesotheliomas tested (125 of 126). The remaining 85 mesotheliomas had a mixed etiology (sarcomatoid mesotheliomas) and were correctly identified as a mixture of their primary components, with potential implications in resolving subtypes and incidences of mixed histology.
Overview The goal of artificial intelligence is to enable the development of computers to do things normally done by people -- in particular, things associated with people acting intelligently. In the case of cybersecurity, its most practical application has been automating human intensive tasks to keep pace with attackers! Progressive organizations have begun using artificial intelligence in cybersecurity applications to defend against attackers. However, on it's own, artificial intelligence is best designed to identify "what is wrong." What today's enterprise needs to know is not only "what is wrong" in the face of a breach, but to understand "why it's wrong" and "how to fix it!"
Could Apple be about to release the HomePod 2, a smaller version of its Siri smart speaker? That's a question we've been asking ourselves for a while now now – and while Apple's iPhone X launch event on September 12, 2018 didn't reveal what the next HomePod will look like, the HomePod 2 could finally be on the horizon. Nearly a year has passed since then, and the iPhone 11 launch saw no mention of the new Apple HomePod Mini – so, everything is pointing to a 2020 release date. The speculation is that the next version of the HomePod, the Apple HomePod 2, may be a more compact version of the original, with the name Apple HomePod Mini being rumored. According to a Bloomberg report in July 2018, Apple may have been looking to release the HomePod 2 sometime in early 2019, which would make sense based on the release date of the original HomePod – of course, it never actually materialized.
Foundation today announces general availability of the newest, fastest, most powerful BeagleBoard.org Built on our proven open source Linux approach, BeagleBone AI fills the gap between small single board computers (SBCs) and more powerful industrial computers. Leveraging the Texas Instruments Sitara AM5729 processor, developers have access to powerful machine learning capabilities with the ease of the BeagleBone Black header and mechanical compatibility. BeagleBone AI makes it easy to explore how artificial intelligence (AI) and machine learning can be used in everyday life. Through BeagleBone AI, developers can take advantage of the TI C66x digital-signal-processor (DSP) cores and embedded-vision-engine (EVE) cores on the Sitara AM5729 processor.
The professional world has changed a lot in the last decades. Now, many workers are remote or freelance contractors that get hired and paid on a per-project basis. Thanks to the nomadic nature of the digital workforce, the technology that these employees use is entirely different from the last generation's -- and the evolution of this technology does not seem to be slowing down any time soon. Below, 15 members of Forbes Technology Council explore some of the cutting-edge technology trends that already are or will soon be transforming the workplace, and how companies can adapt to make the most of these changes. Embracing a "remote-first" culture at workplaces will be a key factor in companies' success in the coming decade.
Unlike in the pre-internet era, when trading in the stock or commodities market involved a phone call to a broker -- a move which often meant additional fees for would-be traders -- the rise of trading apps placed the ability to trade in the hands of ordinary users. However, their popularity has led to their abuse by cybercriminals who create fake trading apps as lures for unsuspecting victims to steal their personal data. We recently found and analyzed an example of such an app, which had a malicious malware variant that disguised itself as a legitimate Mac-based trading app called Stockfolio. We found two variants of the malware family. The first one contains a pair of shell scripts and connects to a remote site to decrypt its encrypted codes while the second sample, despite using a simpler routine involving a single shell script, actually incorporates a persistence mechanism.
Last month data scientists, analysts, executives, engineers, developers, and AI researchers from a wide range of industries flew in the city of seven hills, San Francisco, California. Each one of over 1000 attendees was super pumped to share and learn emerging trends that are transforming data and businesses. I was one of them and I would like to share some key takeaways with the data science community around the globe. In my opinion, at Strata Data Conferences one could see a perfect intersection of cutting-edge science and evolving business models. The conference featured more than 300 speakers, 10 keynotes, 10 tutorials, and 150 technical sessions.
AI could improve operational consistencies and enhance equipment utilization, Navis survey shows. Global container terminals are expected to embrace automated decision making powered by artificial intelligence (AI) as they pursue ways to improve operational consistencies and enhance equipment utilization, a new survey shows. The findings indicate that container terminals, regardless of their AI maturity, are increasingly aware of the possibilities of automated decision-making, according to supply chain technology provider Navis LLC. The Oakland, California-based firm said its TechValidate customer survey included responses from nearly 60 Navis customers, representing a cross-section of container terminals around the world using various degrees of automation. In addition to the 86% who cited operational consistency and equipment utilization as the most important benefits of automated decision-making, port operators also named other goals.
The AI market is possibly one of the toughest to keep track of, as the pace of change is relentless. Making predictions is even harder for this market, as one tends to follow what is known as Amara's Law, overestimating the potential of a technology in the short term and underestimating it in the longer term. Nevertheless, Tractica has identified 10 key predictions that cover various aspects of the ever-evolving AI market, based on our ongoing research and analysis including extensive primary research and interviews. Key trends to watch in the AI market in 2019 will include the commercialization of promising technologies, the growth of new application markets, changes in hardware architectures and infrastructure to support AI deployments, and continuing evolution of business models and public policy issues. Tractica's 10 key predictions for AI in 2019 include the following: This Tractica white paper identifies 10 key predictions for the AI market in 2019 and provides supporting details and examples behind each prediction.