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) …
The technological buzz around the world is incomplete without AI and ML. Both of these technologies have revolutionized the world. When we talk about machine learning and artificial intelligence, many people associate it with some high tech work, but these technologies have made their way into our daily lives. Whether we talk about the voice assistant system or the infotainment system of our car, even our coffee machines now perform as per our will, and all this possible because of the development of AI and ML. Although most of us tend to use these words interchangeably, these are different.
Artificial intelligence (AI) is becoming an everyday piece of technology in modern homes. It is now not uncommon to find smart home devices such as Google Hubs and wearable technology such as Apple Watches in a typical home - each including a smart assistant (i.e. With the introduction of self-driving cars, this type of technology will soon touch almost every aspect of our lives. Currently, most AI technology relies heavily on the cloud, using a collection of data that is stored there. Unfortunately, this reliance on the cloud can lead to latency issues as the process of data traveling between data centers and the device can be affected by several factors.
Emerging technology is slowly finding a place in developing countries for its potential to plug gaps in ailing public service systems, such as healthcare. At the same time, cases of bias and discrimination that overlap with the complexity of algorithms have created a trust problem with technology. Promoting transparency in algorithmic decision-making through explainability can be pivotal in addressing the lack of trust with medical artificial intelligence (AI), but this comes with challenges for providers and regulators. In generating explainability, AI providers need to prioritise their accountability to patient safety given that the most accurate of algorithms are still opaque. There are also additional costs involved. Regulators looking to facilitate the entry of innovation while prioritising patient safety will need to look into ascertaining a reasonable level of explainability considering risk factors and the context of its use, and adaptive and experimental means of regulation. Artificial intelligence (AI) models across the globe have come under the scanner over ethical issues; for instance, Amazon's hiring algorithm reportedly discriminates against women, and there is evidence of racial bias in the facial recognition software used by law enforcement in the United States (US). While biased AI has various implications, concerns around the use of AI in ethically sensitive industries, such as healthcare, justifiably require closer examination. Medical AI models have become more commonplace in clinical and healthcare settings due to their higher accuracy and lower turnaround time and cost in comparison to non-AI techniques.
Parents want the best for their children. While the goal is apparent, figuring out how to do it is challenging. Parents want their kids to be healthy, happy, secure, smart, sociable, smart, athletic, etc. That is a lot to do considering that they have to balance it out based on how quality time they can make for their child, how much resources they can put in to child development, meeting socio-economic needs, etc. With everyone turning to artificial intelligent assistants for help, could there be an AI digital assistant for parents doing one of the most human of things: raising their children?
If you're in the beginning stages of your data science credential journey, you're either about to take (or have taken) a probability class. As part of that class, you're introduced to several different probability distributions, like the binomial distribution, geometric distribution and uniform distribution. You might be tempted to skip over some elementary topics and just scrape by with a bare pass. Because, let's face it--the way probability is taught (with dice rolls and cards) is far removed from the glamor of data science. When am I ever going to calculate the probability of five die rolls in a row in real life?
It takes a certain type of person to wait patiently on hold, listening to the same repetitive messages and piped music for 45 minutes before speaking to an actual human. But most of us are not that type of person, which is why Google this week introduced Hold for Me, a new phone app feature that helps users reclaim their time and mental health. Starting with the just-announced Pixel 5 and Pixel 4a 5G, U.S. customers who call a toll-free number and are put on hold can simply tag Google Assistant to take their place in the queue. Go about your day as normal; the AI-powered aide will notify you with a sound, vibration, and on-screen prompt as soon as someone is on the line and ready to talk. "That means you'll spend more time doing what's important to you, and less time listening to hold music," Google product managers Andrew Goodman and Joseph Cherukara wrote in a blog post.
The trailer for Sacha Baron Cohen's long-awaited sequel Borat Subsequent Moviefilm: Delivery of Prodigious Bribe to American Regime for Make Benefit Once Glorious Nation of Kazakhstan was released by Amazon this morning, and the biggest question it leaves is: Who's that playing Borat's daughter? The trailer has no credits, and there's no Internet Movie Database page for the film, but Amazon's press release says that the movie, to be released on Oct. 23 on Amazon Prime Video, is "starring Sacha Baron Cohen & Irina Nowak," which would seem to be that. The internet is surprisingly little help on this point. There's no Irina Nowak on IMDb, and the closest search return is an actress named Irina Novak, who's 39--far too old, assuming there's no Irishman-type de-aging budget involved. Baron Cohen used relative unknowns as his castmates in the first Borat, including character actor Ken Davitian as Azamat Bagatov and comedian Luenell Campbell as the sex worker whom Borat eventually marries, but even the latter had a previous bit part in Nash Bridges on her CV.
I started Practical Deep Learning for Coders 10 days ago. I am compelled to say their pragmatic approach is exactly what I needed. I started data science by learning Python, Pandas, NumPy, and whatever I needed in a short few months. I did whatever courses I need to do (e.g. Kaggle micro-courses) and whatever books I needed to read (e.g.
"Neural Networks From Scratch" is a book intended to teach you how to build neural networks on your own, without any libraries, so you can better understand deep learning and how all of the elements work. This is so you can go out and do new/novel things with deep learning as well as to become more successful with even more basic models. This book is to accompany the usual free tutorial videos and sample code from youtube.com/sentdex. This topic is one that warrants multiple mediums and sittings. Having something like a hard copy that you can make notes in, or access without your computer/offline is extremely helpful.