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) …
IBM today announced the launch of its new Deep Learning as a Service (DLaaS) program for AI developers. With DlaaS, users can train neural networks using popular frameworks such as TensorFlow, PyTorch, and Caffe without buying and maintaining costly hardware. The service lets data scientists train models using only the resources they need, paying only for GPU time. Each cloud processing unit is set up for ease-of-use and prepared for programming deep learning networks without the need for infrastructure management from users. Users can choose from a set of supported deep learning frameworks, a neural network model, training data, and cost constraints and then the service takes care of the rest, providing them an interactive, iterative training experience.
Deep-Learning-as-a-Service, unveiled at IBM's annual IT industry conference in Las Vegas, seeks to lower barriers to deploying AI and deep-learning tools, a complex and painstakingly repetitive process that requires large amounts of computing power, the company said. The new service allows companies to upload data in Watson Studio, IBM's cloud-native platform for data scientists, developers and business analysts. There, they can create deep-learning algorithms for datasets – known in AI parlance as a "neural network" – using a drag-and-drop interface to select, configure, design and code the network. IBM also has automated the repetitive process of fine-tuning deep-learning algorithms, with successive training runs started, monitored and stopped automatically. For many firms, the complexity of creating smart algorithms from scratch has kept them from leveraging AI to parse massive stores of data for business value, the company said.
A report by IDC, which follows the tech industry, estimates that worldwide spending on artificial intelligence (AI) could increase at an annual pace of 50% through 2021, hitting $57.6 billion in revenue at the end of the forecast period. Several companies are scrambling to integrate AI into their products and services to make sure they don't miss out on this opportunity. For investors in the AI boom, Microsoft (NASDAQ:MSFT) is one such company to consider, thanks to its tangible progress in this space. Here's how AI is impacting Microsoft now, and what it means for the company's future. Microsoft has already started reaping the benefits of AI in areas such as cloud computing and productivity software and services.
Microsoft has announced that its next major update to Windows 10 will include Windows ML, the company's new AI platform. Windows ML will let developers use machine learning systems running in their apps, which could result in faster artificial intelligence. "Every developer that builds apps on Windows 10 will be able to use AI to deliver more powerful and engaging experiences." Windows ML will allow Windows devices to perform AI evaluation tasks to enable real-time analysis of large local data like images and videos. Through Microsoft's Cloud AI platform, developers will also be able to build affordable end-to-end AI solutions which can reduce operational costs.
Winjit has been catering various sectors and business verticals with its smart and innovative platforms. 'PredictSense' is no different and is ready to make an impact in the coming years. When it comes to developing machine learning platforms, it could be a real challenge as it demands an expert for it. From choosing the right algorithm to having an in-depth knowledge of tools and techniques, is a must. This challenge is addressed by'PredictSense', which allows the developer to build easy machine learning solutions even without indepth knowledge.
Earlier this week Google and Verily Life Sciences shared the latest advance in computer vision to identify signs of heart disease. With an accuracy of 70 percent, early results from the AI trained on retinal scan images from more than 200,000 patients is as precise as methods that require blood tests for cholesterol, said Google Brain product manager Lily Peng.
December 21, 2017: Business Wire India NVIDIA brought together the best minds in research, academia and industry across Hyderabad, Chennai, Mumbai, Pune, Delhi and Bangalore 42 speaker sessions from leading experts in fields such as computer vision, sensor fusion, software development, regulation and HD mapping provide expertise NVIDIA today completed its first edition of Developer Connect 2017 in Bangalore. The six-city developer roadshow witnessed over 5,000 attendees who experienced some of the highest quality workshops and demonstrations of AI and deep learning tools, designed to meet the challenges big data presents. Attendees got a closer look at NVIDIA's DGX systems, as well as the opportunity to learn more about its new Volta architecture. Both the DGX-1 and DGX Station were on display to demonstrate the full power of these AI supercomputers. The concluding segment witnessed prominent speakers from organizations such as Ola, Cognitive Computing, Microsoft, Hewlett Packard Enterprise Labs, Shell India, Sony India and Aditya Imaging Information Technologies provide their views.
WIRE)--Veritone, Inc. (NASDAQ:VERI), a leading provider of artificial intelligence (AI) insights and cognitive solutions, today announced the general availability of its Veritone Developer application. The application empowers developers of cognitive engines, applications and application programming interfaces (APIs) to bring new AI ideas to life through simple integration with the Veritone aiWARE platform.
Amazon SageMaker is a fully managed service for developers and data scientists to quickly build, train, deploy, and manage their own machine learning models. AWS also introduced AWS DeepLens, a deep learning-enabled wireless video camera that can run real-time computer vision models to give developers hands-on experience with machine learning. And, AWS announced four new application services that allow developers to build applications that emulate human-like cognition: Amazon Transcribe for converting speech to text; Amazon Translate for translating text between languages; Amazon Comprehend for understanding natural language; and, Amazon Rekognition Video, a new computer vision service for analyzing videos in batches and in real-time.