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) …
Artificial intelligence is learning to decipher damaged ancient Greek engravings. The AI seems to be better than humans at filling in missing words, but may be most useful as a collaborative tool, where researchers use it to narrow down the options. There are thousands of ancient inscriptions we already know about, with dozens more discovered every year. Unfortunately, many have become eroded or damaged over the centuries, resulting in segments of text being lost. Figuring out what the gaps could be is a difficult task, involving looking at the rest of the inscription and other similar texts.
If your timeline is being inundated with celebrity lookalikes, that's because a new viral app has taken off. Gradient Photo Editor allows users to upload a selfie or face photo and the app will use artificial intelligence to gradually turn them into a celebrity that they allegedly resemble. The photo editing app is just over a week old and has already amassed a huge celebrity following including the Kardashians and the record producer Diplo. The app's results sometimes miss the mark. One USA TODAY reporter's results included the Spanish soccer player Marc Bartra, rapper Tyler the Creator and Brazilian actress Giovanna Ewbank.
This group of tutorials via DSC looks good. And to get full access you need to join as a member, which I always recommend. If you like self-study, its a great era we live in, lots of free and detailed information. DSC is a great resource. All this material is available for free, and consists of content mostly created in 2019 and 2018, by various top experts in their respective fields.
With the emergence of ever-cheaper and robust hardware, 5G connectivity around the corner, and most importantly, a growing list of real world use cases, we can all agree that Internet of Things (IoT) solutions for enterprise are here to stay. But is that where it ends? Is the end goal of having interconnected devices simply because sounds like something that could be useful to have, perhaps to monitor some sort of reading in a production environment, or simply get timely updates in a supply chain process? IoT will play a much more important role in our future, primarily for the following reasons. Not only are IoT projects ultimately most valuable as big data projects (we are essentially collecting large amounts of data from these IoT devices after all), but ultimately, all IoT projects will apply machine learning (ML) and artificial intelligence (AI) to the data collected in order to truly move the game forward.
Google has discontinued selling its artificial intelligence-powered camera device called'Clips'. The device, which was launched in 2017 at a price of $249, uses machine learning to learn and recognise faces and automatically records short motion images of things it finds "interesting". Google said it has begun integrating'Clips' technology into the'Photobooth' feature starting with its Pixel 3.
"The #1 benefit AI brings to transportation is increasing public safety. AI can predict trends and events before they happen. As it relates to tollways, AI allows vehicles to enter and exit without the need to stop. Tollways take pictures of oncoming vehicles and leverage AI-based software engines to identify license plate numbers and bill the respective registered owner. Motorists are safer and no longer need to fuss over paying for a toll."
Personetics is the leading provider of customer-facing AI solutions for financial services and the company behind the industry's first Self-Driving Finance platform. Harnessing the power of AI, Personetics' Self-Driving Finance solutions are used by the world's largest financial institutions to transform digital banking into the center of the customer's financial life – providing real-time personalized insight and advice, automating financial decisions, and simplifying day-to-day money management. Serving over 65 million bank customers worldwide, Personetics has the largest direct customer impact of any AI solution provider in banking today. Personetics customers include 6 of the top 12 banks in North America and Europe and other leading banks throughout the world. Led by a team of seasoned FinTech entrepreneurs with a proven track record, Personetics is a rapidly growing company with offices in New York, London, Paris, Singapore, and Tel Aviv.
Autify, a Japanese software testing team backed by Alchemist Accelerator graduation, has raised a seed funding of USD 2.5M by Global Brain Corporation, Salesforce Ventures, Archetype Ventures, and other individual investors. Autify has launched its AI-powered software testing automation platform, globally. Including this round and the pre-seed funding, the total capital reached USD 3.07 million. The Japanese software team founded Locki Inc. in 2016. In 2018 the startup selected for the Alchemist Accelerator program in the US.
Booking.com is the world's largest online travel agent where millions of guests find their accommodation and millions of accommodation providers list their properties including hotels, apartments, bed and breakfasts, guest houses, and more. During the last years we have applied Machine Learning to improve the experience of our customers and our business. While most of the Machine Learning literature focuses on the algorithmic or mathematical aspects of the field, not much has been published about how Machine Learning can deliver meaningful impact in an industrial environment where commercial gains are paramount. We conducted an analysis on about 150 successful customer facing applications of Machine Learning, developed by dozens of teams in Booking.com, Following the phases of a Machine Learning project we describe our approach, the many challenges we found, and the lessons we learned while scaling up such a complex technology across our organization.