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) …
Haunted house stories are having a moment. Or it could be Netflix's fault--its release of The Haunting of Bly Manor has reinvigorated the discourse about what makes a good haunted house story and whether or not Mike Flanagan, the horror director who, between Bly Manor and Hill House and Doctor Sleep seems to be veritably obsessed with them, really has what it takes to make one that feels both scary and fascinating. Haunted houses are special because houses are special. They keep us safe--until they don't--and are both entirely familiar to us and entirely unfamiliar, as anyone who's had to deal with serious home repairs could tell you. People have intimate relationships with the places where they live.
How is Machine Learning helping to develop TB drugs? Many biologists use machine learning (ML) as a computational tool to analyze a massive amount of data, helping them to recognise potential new drugs. MIT researchers have now integrated a new feature into these types of machine learning algorithms, enhancing their prediction-making ability. Using this new tool allows computer models to account for uncertainty in the data they are testing, MIT researchers detected several promising components that target a protein required by the bacteria that cause tuberculosis (TB). Although computer scientists previously used this technique, they have not taken off in biology.
Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) say they've created an autonomous river vessel -- Roboat II -- that's capable of carrying passengers across fast-moving bodies of water. It's the latest addition to a fleet of autonomous boats developed by CSAIL, MIT Senseable City Lab, and the Amsterdam Institute for Advanced Metropolitan Solutions (AMS) over the last five years. As MIT's Rob Matheson explained in a recent blog post, the Roboats -- rectangular hulls packing sensors, thrusters, microcontrollers, cameras, and other hardware -- emerged from the ongoing project. The goal is to create robot fleets that can ferry people and goods through Amsterdam's 160 canals and self-assemble into bridges to help reduce pedestrian congestion. Roboat II measures 2 meters long (6 feet) and can carry up to six passengers at a time.
The researchers used detailed satellite imagery from NASA, and deep learning--an advanced artificial intelligence method. Normal satellite imagery is unable to identify individual trees, they remain literally invisible. Moreover, a limited interest in counting trees outside of forested areas led to the prevailing view that this particular region had almost no trees. This is the first time that anyone counted trees across a large dryland region.
Recent advances in AI and ML, while not actually close to real AGI, have made a feeling that AGI is close, as surprisingly fast for many years. Artificial Intelligence is something that's been around quite a while. Since its development into the public consciousness through sci-fi, many have expected that one day machines will have "general intelligence", and considered diverse practical, ethical and philosophical implications. In all actuality, AI has been the discussion of standard pop-culture and sci-fi since the first Terminator film turned out in 1984. These motion pictures present an example of something many refer to as "Artificial General Intelligence".
What are the Benefits of Ensemble Methods for Machine Learning? Ensembles are predictive models that combine predictions from two or more other models. Ensemble learning methods are popular and the go-to technique when the best performance on a predictive modeling project is the most important outcome. Nevertheless, they are not always the most appropriate technique […]
Not to be outdone by Facebook and Microsoft, both of whom detailed cutting-edge machine learning language algorithms in late October, Google this week open-sourced a model called MT5 that the company claims achieves state-of-the-art results on a range of English natural processing tasks tasks. MT5, a multilingual variant of Google's T5 model that was pretrained on a dataset covering 101 languages, contains between 300 million and 13 billion parameters (variables internal to the model used to make predictions) and ostensibly has enough capacity to learn over 100 languages without significant "interference" effects. The goal of multilingual AI model design is to build a model that can understand the world's over 7,000 languages. Multilingual AI models share information between similar languages, which benefits low-resource languages and allows for zero-shot language processing, or the processing of languages the model hasn't seen. As models increase in size, they require larger datasets that can be laborious and difficult to create, which has led researchers to focus on web-scraped content.
The Earth is losing forests at an alarming rate. The United Nations Food and Agriculture Organization estimates that 420 million hectares of forest have been lost to agricultural use (largely cattle ranching, soya bean and oil palm farming) since 1990. Between 2015 and 2020, some 10 million hectares were destroyed each year. The Amazon rainforest, for example, lost an area the size of Yellowstone (3,769 square miles) in 2019, and saw deforestation rates spike 30 percent to their highest point in a decade. What's more, Climate change-induced wildfires, as we've seen recently in Australia and in California, have been especially destructive.
MIT has upgraded its autonomous boat fleet with the Roboat II, a vehicle sailing down the canals of Amsterdam that is able to carry passengers. On Monday, MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Lab published an update on the project, which aims to develop maritime autonomy applications if not for the sea -- for now -- at least for smart cities and more urban environments. Five years after creating the first prototype, CSAIL and Senseable have added a new boat to the fleet -- the Roboat II. The two-meter boat utilizes four propellers to move down waterways and is equipped with similar algorithms, sensors, and mapping technology to autonomous land vehicles. The algorithms map waterways and plot paths between a series of "goal points" according to the team.