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) …
When my business partner and I launched our company in the mid-1990s, we debated whether to install an automated phone system. It seemed to be the wave of the future, and we were intrigued by the prospect of it saving us the expense of hiring a receptionist. We eventually decided against it because of the frustrations we'd experienced on the other end of such systems. As a startup, the last thing we wanted to do is frustrate our clients and vendors by making them use a complicated telephone tree. In some circumstances, there's just nothing that can replace a human being.
Unless the intelligence community changes the way it defines intelligence and adopts cloud computing, it will wind up behind adversaries, private interests, and even the public in knowing what might happen, according to a new report from the Center for Strategic and International Studies. Intelligence collection to predict broad geopolitical and military events has historically been the job of well-funded and expertly staffed government agencies like the CIA or the NSA. But, the report argues, the same institutional elements that allowed the government to create those agencies are now slowing them down in a time of large publicly-available datasets and enterprise cloud capabilities. The report, scheduled to be released Wednesday, looks at a hypothetical "open-source, cloud-based, AI-enabled reporting," or OSCAR, tool for the intelligence community, a tool that could help the community much more rapidly detect and act on clues about major geopolitical or security events. The report lists the various procedural, bureaucratic, and cultural barriers within the intelligence community that block its development and use by U.S. spy agencies.
What started as a pile of loose post-it notes ideas has transformed into our latest series and we are very excited to announce "New voices in AI"! What is "New voices in AI"? It can be hard to be heard over the sheer volume of AI research being generated every day. This is especially true for those starting out in the field so here at AIhub we wanted to lend a hand. Therefore in this series we amplify the voices of PhD students, early career researchers, and those in the field of AI with a fresh perspective.
Did you miss a session from the Future of Work Summit? In 2019, San Francisco-based AI research lab OpenAI held a tournament to tout the prowess of OpenAI Five, a system designed to play the multiplayer battle arena game Dota 2. OpenAI Five defeated a team of professional players -- twice. And when made publicly available, OpenAI Five managed to win against 99.4% of people who played against it online. OpenAI has invested heavily in games for research, developing libraries like CoinRun and Neural MMO, a simulator that plops AI in the middle of an RPG-like world. But that approach is changing.
AI in recruitment is a fast-growing trend that is changing how we find work. With 43% of HR professionals already using AI and more planning to in the future, job seekers need to know how to use it to their advantage. In our ultimate guide to AI for talent management, we'll explain what AI is all about and how you can use it to help your job search. AI means technology that does things automatically using algorithms and machine learning. Recruiters are using AI to automate some of the high-volume recruitment processes.
Artificial Intelligence (AI) has been bandied around for the last few decades or so and, I'm sure, most of us are still wondering: What exactly is this? So, will we be faced with an army of Terminator-like humanoids who will reign terror across the world? Will we witness "I, Robot"-like humanoids attending to our homecare needs – you know, washing, ironing, cooking and the like? Nah, I already have a wife that's dutifully doing that. Okay, stop – I know I shouldn't go there – just one small footnote though: My wife, Sarah, isn't remotely domesticated, although she does cook once in a while!
While technical skill is undeniably important when approaching any data science effort, there is an art to data science and machine learning that doesn't seem to be discussed as often as pure technical skill is. These more soft skills help a seasoned data scientist navigate through numerous opportunities as seamlessly and efficiently as possible. The fact of the matter is that pretty much every data science effort has its own flair to it that poses unique challenges that may (or frankly, may not) be worth pursuing. Because applied data science always grounds itself in seeking a solution to a real world problem, having subject matter expertise about that real world problem is an absolute must. Of course, it's unreasonable to expect for a data scientist themselves to have that subject matter expertise themselves.
Chien Lu received a runner up award for best student paper at ACML 2021. In this interview, he tells us about the implications of this research, the methodology, and plans for future work. Our paper is entitled "Cross-structural factor-topic model: document analysis with sophisticated covariates." This paper proposes a novel topic model to analyze text documents with sophisticated covariates. Text data are usually accompanied by various numerical covariates in many real-world situations.
On your homepage at Artsted.com you say "to use AI to help identify tomorrow's blue-chip artists". Could you please expand on the use of AI? How does your technology work? So, it would be fair to say that our AI model is currently being tested as we are having more users join the platform and therefore more data to perfect it. The data to train the initial evaluations algorithm was taken from open-source auction house records (openly available auction results published directly on major auction house websites so we could match a market performance to a database of 400.000 artists. As a result, our proprietary algorithm (a unique algorithm, built entirely by our development team – based on the publicly sourced data) works the same way, reacting to the "trigger" data input, that artists provide, that the algorithm goes on to consider as significant for their career: an article in Artforum, a solo show in a mid-tier gallery, a selection for a biennial, an art prize shortlist are a few examples of the categories of data that influence the end result.
A few months back I came across a video that started off with a riddle: A boy, who is about to interview in a big company, is in the car with his father. The boy gets a call from the CEO of the company he is about to interview with, and when he answers the call, the CEO says "Good luck son, you've got this". Participants were asked how this was possible?. Do you have any guesses before reading further? Some of them guessed the CEO could be the grandfather, or it could be a pre-recorded call from the father, or the guy has two fathers, and some even guessed that the boy's name was'son'.