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) …
Sir David Hand gave a brilliant plenary talk and set the stage for a great panel discussion by cautioning us to remember that thinking is required and to be aware of all the dark data out there -- the data that we don't see, but that we need to take into account. Dark Data: Why What You Don't Know Matters is his latest book (see a blog post about it; if you haven't read it, you can get a sample excerpt). The panelists included Cameron Willden, statistician at W.L. Gore, who supports engineers and scientists across many different product lines; Sam Gardner, founder of Wildstats Consulting, with more than 30 years of experience doing statistical problem solving for government and industry; and JMP's Jason Wiggins, a 20-year US Synthetic veteran with expertise in process optimization, measurement systems analysis and predictive modeling/data mining. We ran out of time before we could answer all the questions from the livestream audience, but our panelists have kindly agreed to provide answers to many of them, further sharing the wisdom from their collective experiences. The questions are grouped by topic -- there were so many, we are doing two posts.
The 2020 presidential election in the United States is just around the corner. This year, the election has been particularly controversial in part because of the ongoing COVID-19 pandemic and the restrictions the virus has placed on in-person gatherings. In a world in which connected devices and IoT (Internet of Things) technologies have enabled everything from autonomous vehicles to robotic surgery, it seems like there should be other options for casting votes besides sending paper ballots in by mail or turning them in by hand. However, concerns (both legitimate and overblown) about election-outcome accuracy and voter privacy have held the election process back in many ways from the digital revolution that has permeated almost everything else. Will 2020 be a pivotal year in changing how the American people and "the powers that be" feel about advancing the voting process?
Cross-validation is used to evaluate machine learning models on a limited data sample.It estimates the skill of a machine learning model on unseen data. The techniques creates and validates given model multiple times. We have 2–4 types of cross validation like Stratified, LOOCV, K-Fold etc. Here, we will study K-Fold technique. Let's split data 70:30, train model and test the given data-set to get accuracy.
The schedule is not yet finalized, so please keep in mind that workshop / demo times may change. Remoticon chat can be found on the project page, all are welcome to join the public chat! Hackaday Remoticon is the largest gathering of hardware hackers, builders, engineers, and enthusiasts on the planet. Because it's virtual, more of you can come! Remoticon is 20 workshops, 2 keynote talks, and some very fun extras like the SMD challenge, remote robot driving, show and tell, and more being planned.
As a technologist, I am gung-ho about the widespread application of technology across any domain including healthcare. In Season 1 of the You AI Podcast, I spoke with 15 medical doctors and we explored together where AI may drive the most impact in healthcare. In this session, I share the lessons that I learnt from those conversations with doctors and the underlying absorbing stories that helped me be more nuanced about where and how AI should be applied in Healthcare.
A cohort of researchers from world-renowned academic institutions such as the University of Oxford, University of Warwick, University of Montpellier and credible research labs, have invented a methodology of detecting Covid-19 (SARS-CoV-2) and other respiratory pathogens within mere minutes. This feat is made possible through the utilisation of image analysis and machine learning techniques, more specifically convolutional neural networks to classify microscopic viruses of respiratory diseases based on structural features unique to the viruses. It is entirely, understandable that some terms and phrases within this article might be unfamiliar to some readers, so, at some points in this article, some sections provide definitions to words and key terms used. Common types of pathogens are viruses, bacterias, fungi, prion, and parasites.
The premarket hours are back in the red again on Wednesday. But we're seeing plenty of penny stocks shine. The fact that most small-cap stocks are disconnected from the overall market trend is something I think is overlooked. While not all penny stocks will respond this way, many do. We saw this today with several of the breakout, midstream oil stocks that were moving hugely in after-hours trading on Tuesday evening.
One of the most well-known hesitations emerges among modern innovations such as artificial intelligence, machine learning, big data, data science, deep learning, and more. While they are closely interconnected, each has individual functionality. In the course of recent years, the fame of these technologies has risen so much that few organizations have now woken up to their significance on huge levels and are progressively hoping to actualize them for their business development. While the terms Data Science and Machine learning fall in a similar space, they have their particular applications and significance. There might be overlaps in these areas once in a while, yet basically, every one of these terms has unique uses of their own.
Artificial intelligence-based tools continue to be used by only a very small percentage of law firms, according to the ABA's 2020 Legal Technology Survey Report this month. Just 7% of respondents to the ABA Legal Technology Resource Center's survey reported that their firms use AI tech tools, a decrease of one percentage point from a year ago. Meanwhile, 23% of respondents said their firms were not interested in purchasing AI-based tools and nearly 34% said they did not know enough about AI to answer the question regarding their firms current or planned usage of such tools. Alexander Paykin, a Legal Technology Resource Center board member, says he thinks the legal industry has been slow to adopt AI-based tools because the available products have yet to demonstrate they can consistently produce the results vendors promise. He points to his experience with the AI-based legal research offerings he has tried out in recent years to back up his point.
The applications of artificial intelligence (AI) have become ubiquitous over the last decade, transforming the way we work, play, and interact with the world. AI systems recommend what you should watch on Netflix, recognize your biometric data for authentication, and assist you during "live" chats with customer service. These examples highlight common applications of AI systems, but AI can also promote security in our data and systems. The U.S. Chamber of Commerce's Cyber, Intelligence, and Supply Chain Security Division hosted a discussion today on the applications of AI in cybersecurity during its Now Next webinar series, and dove into how businesses can leverage AI in their security efforts. "Humans are great at intuition and creativity. The challenge in cyber is that you sometimes have very subtle signals pointing to anomalies, and you must move beyond human scale to see that drift from normality in complex enterprises. Moreover, you must understand those subtle signals and respond to them at machine speed. This is where the power of AI potentially provides the most value," said Albert Biketi, Vice President, Security Business at Splunk.