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Roland Meertens shows how one can get started deploying models without requiring any data, discussing foundational models, and examples of them, such as GPT-3 and OpenAI CLIP. → Read More
Monte Zweben, Roland Meertens discuss the challenges in building, maintaining, and operating machine learning models. → Read More
How AI, ML and Data Engineering evolved in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML. → Read More
How AI, ML and Data Engineering is evolving in 2021 as seen by the InfoQ editorial team. Topics discussed are deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML. → Read More
How AI, ML and Data Engineering is evolving in 2021 as seen by the InfoQ editorial team. Topics discussed are deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML. → Read More
Canonical released a minimal containerised version of Ubuntu 20.04 LTS specifically for IoT devices and embedded systems. Ubuntu Core is an operating system for industry and consumer devices. It is available for both x86 and ARM computers. Additional features compared to previous Core operating systems are secure boot, full drive encryption, and secure device recovery. → Read More
Researchers Ghose and Prevost created a deep learning algorithm which, given a silent video, can generate a realistic sounding synchronised soundtrack. They trained the neural network to classify the class of the sound to generate, and they also trained a sequential network to generate the sound. They thus could go from temporally aligned images to the generation of sound: a different modality! → Read More
Researchers from the university of Cambridge trained a robot to prepare an omelette and optimized the recipe to produce well-tasting dishes. To find the most objectively best recipe, the researchers turned towards Bayesian optimization techniques. They investigated two methods: sequential Bayesian optimization and batch Bayesian optimization. → Read More
Mozilla’s Mixed Reality group launches a cloud version of Mozilla Hubs, their social space for virtual reality gatherings. Organisations can now deploy and customize their own instance of Mozilla Hubs → Read More
These lighting talks cover several papers: Towards a Solution to the Red Wedding Problem, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, A Machine Learning Approach to Databases Indexes. → Read More
InfoQ released an Alexa Flash briefing that tells you the latest tech-news available on InfoQ.com. This flash briefing skill gives you an update on the latest trends in software, and summarizes it in less than two minutes. The skill is available wherever Amazon has English Alexa skills. → Read More
Researchers from Sony announced that they trained a ResNet 50 architecture on ImageNet in only 224 seconds. The resulting network has a top-1 accuracy of 75% on the validation set of ImageNet. They achieved this record by using 2.100 Tesla V100 Tensor Core GPUs from NVIDIA. Besides this record, they also got a 90% GPU scaling efficiency using 1.088 Tesla V100 Tensor Core GPUs. → Read More
ROS recently released their new version: ROS2. In this version RTIs DDS, an open-standard communication framework, is used to communicate between robots, sensors, and computers. This article describes how multi-platform communication can be set up easily with the newest version of ROS and the DDS protocol. → Read More
Today Jensen Huang, CEO of NVIDIA, gave a keynote at the GPU Technology Conference 2018 in Munich. He announced RAPIDS, an open-source CUDA accelerated toolkit that can help data scientists to faster process their data. They announced a partnership to work on medical imaging. They announced a self-driving car simulator that car manufacturers can use for verification of autonomous vehicles. → Read More
David Andrzejewski presented "Understanding Software System behavior With ML and Time Series Data". This article is a summary of his presentation and an overview on what to look out for. Know about the traditional approaches to time series, how to handle missing values, and know about possibly occuring seasonality in your data. Be careful about what threshold you set for anomaly detection. → Read More
At WWDC Apple released Core ML 2: a new version of their machine learning SDK for iOS devices. The new release of Core ML should create an inference time speedup of 30% for apps developed using Core ML 2. An important new feature of the Core ML SDK is Create ML. Developers can create and train custom machine learning models on their mac. → Read More
Enterprise AI has more prevalent nuances in the input data than in consumer AI or academia. The Achilles’ heel in this domain is Hindsight Bias. In layman terms, it is like Marty McFly (from Back to the Future) traveling to the future, getting his hands on the Sports Almanac, and using it to bet on the games of the present. Mayukh Bhaowal from Salesforce Einstein explains how to counteract it. → Read More
A pedestrian was killed on Sunday evening in Tempe, Arizona, by a self-driving car operated by Uber, the BBC reports. The firm confirmed that the vehicle was traveling in autonomous mode with a safety driver, the only vehicle occupant, behind the wheel during the crash. → Read More
Microsoft created a translation algorithm that translates Chinese sentences to English as well as human translators do. Translating Chinese sentences into English has been difficult in the past. Thanks to neural machine translation, a technique that created amazing results in the last couple of years, Microsoft got their machine translated sentences on par with human translated sentences. → Read More
Researchers created an algorithm that allows self-driving cars to predict lane-changes of the surrounding cars. The system works by using a deep-learning technique called Long Short-Term Memories (LSTMs). Although the most likely scenario on the highway is that every car stays in its own lane, their algorithm was able to slightly improve on this baseline prediction. → Read More