InfoQ Homepage Artificial Intelligence Content on InfoQ
-
Grady Booch on the Future of AI
According to Grady Booch, most current AI systems are about pattern matching of signals at the edge and inductive reasoning, not true Artificial Intelligence. During his second day keynote at the 2018 QCon San Francisco, "Building the Enchanted Land", he explained his view that AI today is a "system engineering problem with AI components."
-
Protecting Artificial Intelligence from Itself
Applications using artificial intelligence can be fooled by adversarial examples, creating confusion in the model decisions. Input sanitization can help by filtering out improbable inputs before they are given to the model, argued Katharine Jarmul at Goto Berlin 2018. We need to start thinking of the models and the training data we put into them as potential security breaches, she said.
-
Baidu Announces "OpenEdge", an Open-Source Edge Computing Platform
Recently Baidu Inc. announced China's first open-source edge computing platform called OpenEdge - allowing developers to build light, secure and scalable edge applications. The OpenEdge platform brings processing power to "edge devices" like smart home appliances and wearables.
-
Facebook Open-Sources PyText for Faster Natural Language Processing Development
In a recent blog post, Facebook announced they have open-sourced PyText, a modeling framework, used in natural language processing (NLP) systems. PyText is a library built upon PyTorch and improves the effectiveness of promoting experimentation projects to large-scale production deployments.
-
The Future of Work Is Female
Jobs currently performed by the majority of women, where it’s more about adaptability, improvisation, emotional intelligence, and implicit knowledge, will predominate in the future, according to Agnieszka Walorska. Artificial intelligence and robotics will automate highly specialized jobs mostly performed by men.
-
Connecting Business Challenges and Emerging Technologies
Caragh O'Carroll spoke about three emerging technologies at Women in Tech Dublin 2018: Blockchain, robotic process automation, and artificial intelligence and machine learning. She explored how these technologies provide solutions to the challenges that businesses are facing.
-
Q&A with Christoph Windheuser on AI Applications in the Industry
Increased hardware power and huge amounts of data are making existing machine learning approaches like pattern recognition, natural language processing, and reinforcement learning possible. Artificial Intelligence is impacting the development process; it’s increasing the complexity of things like version control, CI/CD and testing.
-
QCon.ai San Francisco 2019: AI & ML Conference Focused on Software Engineers Announces Tracks
QCon.ai, the first conference from the people behind QCon and InfoQ focused solely on artificial intelligence and machine learning for the software engineer, announces the tracks for the 2019 conference.
-
AWS Marketplace Offers Machine Learning Algorithms and Model Packages
Amazon Web Services is offering machine learning algorithms and model packages on their AWS Marketplace. This was announced at AWS re:Invent Conference last week.
-
Microsoft Announces Container Support for Azure Cognitive Services
Microsoft has announced container support for Cognitive Services, which allows taking advantage of machine learning capabilities anywhere, whether it is in the cloud, on the edge or on-premises. With Azure Cognitive Services, organizations can start using various cognitive features, like vision, speech and text processing, without the need for a dedicated data scientist.
-
Google Introduces AI Hub and Kubeflow Pipelines for Easier ML Deployment
Google is launching two new tools, one proprietary and one open source: AI Hub and Kubeflow pipelines. Both are designed to assist data scientists design, launch and keep track of their machine learning algorithms.
-
Google Open-Sources Speaker Diarization AI Technology, Claims 92% Accuracy
In a recent blog post, Google announced they have open-sourced their speaker diarization technology, which is able to differentiate people’s voices at a high accuracy rate. Google is able to do this by partitioning an audio stream that includes multiple participants into homogeneous segments per participant.
-
Google Open-Sources BERT: A Natural Language Processing Training Technique
In a recent blog post, Google announced they have open-sourced BERT, their state-of-the-art training technique for Natural Language Processing (NLP) . Google has decided to do this, in part, due to a lack of public data sets that are available to developers. In addition, optimizations have been made to Cloud TPUs to reduce the amount of time required for training NLP.
-
Building Human Interfaces with Artificial Intelligence
AI helps us to build human interfaces based on speaking and writing, instead of using a keyboard or mouse; it allows humans to stay human. The biggest challenges are finding ways to tell systems what answers are unsatisfactory to help them learn, be transparent in what data is recorded and retained, and ensure that diversity and inclusion is part of our training data to prevent bias in AI systems.
-
Introducing EmoPy: An Open Source Toolkit for Facial Expression Recognition
In a recent blog post, Angelica Perez shared information about a new open source project for an interactive film experience. The project is called EmoPy and focuses on Facial Expression Recognition (FER) by providing a toolkit that allows developers to accurately predict emotions based upon images passed to the service.