The “Mayflower 400”, the world’s first intelligent ship, bobs gently in a light swell as it stops its engines in Plymouth Sound, off England’s southwest coast, before self-activating a hydrophone designed to listen to whales.
The 50-foot (15-metre) trimaran, which weighs nine tonnes and navigates with complete autonomy, is preparing for a transatlantic voyage. Read More
Monthly Archives: April 2021
Facebook details self-supervised AI that can segment images and videos
Facebook today announced that it developed an algorithm in collaboration with Inria called DINO that enables the training of transformers, a type of machine learning model, without labeled training data. The company claims it sets a new state-of-the-art among unlabeled data training methods and leads to a model that can discover and segment objects in an image or video without a specific objective.
Segmenting objects is used in tasks ranging from swapping out the background of a video chat to teaching robots that navigate through a factory. But it’s considered among the hardest challenges in computer vision because it requires an AI to understand what’s in an image. Read More
Healthcare’s AI Future: A Conversation with Fei-Fei Li & Andrew Ng
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models
We present PyTorch Geometric Temporal a deep learning frame-work combining state-of-the-art machine learning algorithms for neural spatiotemporal signal processing. The main goal of the library is to make temporal geometric deep learning available for researchers and machine learning practitioners in a unified easy-to-use framework. PyTorch Geometric Temporal was created with foundations on existing libraries in the PyTorch ecosystem, stream-lined neural network layer definitions, temporal snapshot generators for batching, and integrated benchmark datasets. These features are illustrated with a tutorial-like case study. Experiments demonstrate the predictive performance of the models implemented in the library on real world problems such as epidemiological forecasting, ridehail demand prediction and web-traffic management.Our sensitivity analysis of runtime shows that the framework can potentially operate on web-scale datasets with rich temporal features and spatial structure. Read More
An A.I. Finally Won an Elite Crossword Tournament
Nearly 1,300 people spent this past weekend racing to fill little boxes inside larger boxes, ever mindful of spelling, trivia, wordplay, and a ticking clock. They were competitors—newcomers, ardent hobbyists, and elite speed solvers—in the American Crossword Puzzle Tournament, the pastime’s most prestigious competition. And most of them got creamed by some software.
The annual event, normally set in a packed hotel ballroom with solvers separated by yellow dividers, was virtual this year, pencils swapped for keyboards. After millions of little boxes had been filled, a computer program topped the leaderboard for the first time. Read More
Fingerspelling
Online game to learn sign language. Fingerspelling.xyz combines advanced hand recognition technology with machine learning to teach sign language. Read More
Deep Learning-Based Autonomous Driving Systems: A Survey of Attacks and Defenses
The rapid development of artificial intelligence,especially deep learning technology, has advanced autonomous driving systems (ADSs) by providing precise control decisions to counterpart almost any driving event, spanning from anti-fatigue safe driving to intelligent route planning. However, ADSs are still plagued by increasing threats from different attacks, which could be categorized into physical attacks, cyber attacks and learning-based adversarial attacks. Inevitably, the safety and security of deep learning-based autonomous driving are severely challenged by these attacks, from which the countermeasures should be analyzed and studied comprehensively to mitigate all potential risks. This survey provides a thorough analysis of different attacks that may jeopardize ADSs, as well as the corresponding state-of-the-art defense mechanisms. The analysis is unrolled by taking an in-depth overview of each step in the ADS workflow,covering adversarial attacks for various deep learning models and attacks in both physical and cyber context. Furthermore, some promising research directions are suggested in order to improve deep learning-based autonomous driving safety, including model robustness training, model testing and verification, and anomaly detection based on cloud/edge servers. Read More
#adversarial, #cyberGetting AI to Scale
Most companies are struggling to realize artificial intelligence’s potential to completely transform the way they do business. The problem is, they typically apply AI in a long list of discrete uses, an approach that doesn’t produce consequential change. Yet trying to overhaul the whole organization with AI all at once is simply too complicated to be practical.
What’s the solution? Using AI to reimagine one entire core business process, journey, or function end to end, say three McKinsey consultants. That allows each AI effort to build off the previous one by, say, reusing data or enhancing capabilities for a common set of stakeholders. An airline, for example, focused on its cargo function, and a telecom provider on its process for managing customer value.
Scaling up AI involves four steps: (1) Identify an area where AI will make a big difference reasonably quickly and there are multiple interconnected activities and opportunities to share technology. (2) Staff the team with the right people and remove the obstacles to their success. (3) Reimagine business as usual, working back from a key goal and then exploring in detail how to achieve it. (4) Support new AI-based processes with organizational changes, such as interdisciplinary collaboration and agile mindsets. Read More
Why ‘deepfake geography’ presents significant risks — and how researchers are detecting it
“Seeing is believing.” It’s an aphorism that used to be a lot more true than it is today, now that computers can easily produce all manner of fake images and altered recordings. Many of us have seen the photos of celebrities who don’t exist and videos of lip-synching politicians. These “deepfakes” have raised real concerns about what is and isn’t true in our newsfeeds and other media.
This problem even extends to the maps and satellite images that represent our world. Techniques such as “location spoofing” and deepfake geography present significant risks for our increasingly connected society.br>
Because of this, a team of researchers at University of Washington are working to identify ways to detect these fakes, as well as proposing the creation of a geographic fact-checking system. Read More
Optoelectronic intelligence
General intelligence involves the integration of many sources of information into a coherent, adaptive model of the world. To design and construct hardware for general intelligence, we must consider principles of both neuroscience and very-large-scale integration. For large neural systems capable of general intelligence, the attributes of photonics for communication and electronics for computation are complementary and interdependent. Using light for communication enables high fan-out as well as low-latency signaling across large systems with no traffic-dependent bottlenecks. For computation, the inherent nonlinearities, high speed, and low power consumption of Josephson circuits are conducive to complex neural functions. Operation at 4 K enables the use of single-photon detectors and silicon light sources, two features that lead to efficiency and economical scalability. Here, I sketch a concept for optoelectronic hardware, beginning with synaptic circuits, continuing through wafer-scale integration, and extending to systems interconnected with fiber-optic tracts, potentially at the scale of the human brain and beyond. Read More
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