Question Answering

When dealing with audio files a lot of work is required to index them properly so that is easy to lookup for them when needed. In this example we'll show how to use IBM Watson Speech to Text to recognize speech from audio files stored on Box and enrich their metadata with the extracted text. Go to Service Credentials and copy the username & password values, we're going to use them soon. In less then 1 minute you can have this up and running by using the project Blueprint, a pre-built template to help you get started with proven integration solutions. To get started with the Blueprint just click here.

I am trying to reproduced result from the paper "DYNAMIC COATTENTION NETWORKS FOR QUESTION ANSWERING" (https://arxiv.org/abs/1611.01604). I have implemented the code in pytorch but it is overfitting. In the paper it is mention that the authors use dropout for regularization. I added dropout and it helps a bit but not too much. I am also curious if it is possible to get feedback on my model code.

The Australian Department of Defence is using what Matt Smorhun, Assistant Secretary for the ICT Strategy Realisation Branch at the Department of Defence, said was only the second on-premises instance of Watson globally. Speaking at the CeBIT Australia conference in Sydney on Wednesday, Smorhun said the department decided to invest in a secret, classified version of IBM's Watson platform, instead of spending valuable time working out how to do artificial intelligence, cognitive learning, and advanced analytics on its own. The next wave of IT innovation will be powered by artificial intelligence and machine learning. We look at the ways companies can take advantage of it and how to get started. He said Defence decided to "just buy this thing" and then work out how it was going to fit into the organisation later.

Recently I've been working on a customer service chatbot based on IBM Watson Assistant (formerly known as "IBM Watson Conversation Service") for a large Austrian telecommuncation provider. The chatbot was trained to answer questions on the website and to lead the user to the right website section. It currently handles 60k-80k conversations per months and covers 25% of the customer service interactions. It happened several times that minor changes in the dialog design or training caused previously working dialogs to fail -- so we were in need of regression testing. With Botium it was possible to generate test cases from the IBM Watson Assistant workspace and setup automated testing within some minutes.

Watson services on IBM Cloud are a set of REST APIs. This makes them quite simple to be used as a piece of a solution within an application. It also means they need to be integrated with various other parts of the solution to allow your users to interact with your instance of Watson. With the launch of Watson Assistant, integrating with other channels (Facebook, Slack, Intercom) has never been easier. Building a skill for Alexa is possible with Watson.

I have been writing code for a number of years now, but was finally bitten by the AI bug in 2016. A thrill of excitement ran through me as I ran demos of applications that were powered by AI. Seeing the potential and value of how AI could change our lives, I was convinced that AI was the future, only to find out later that I was wrong. AI had been a part of my life all along. It had worn several clothes like People You May Know on Facebook, autocorrect while I typed on my phone, Siri, and so many others.

Use streaming IoT data to uncover insights that help you better understand equipment health. Gain real-time visibility into manufacturing and supply chain processes; and monitor overall plant performance, product quality and vehicle safety issues to mitigate or avoid costly product recalls.

The graph represents a network of 3,453 Twitter users whose tweets in the requested range contained "ibm watson", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 06 May 2018 at 03:42 UTC. The requested start date was Sunday, 06 May 2018 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 5,000. The tweets in the network were tweeted over the 12-day, 10-hour, 28-minute period from Sunday, 22 April 2018 at 00:01 UTC to Friday, 04 May 2018 at 10:30 UTC.

Technology giants IBM and Salesforce are expanding their strategic partnership by bringing together their artificial intelligence and cloud computing platforms to help companies connect with customers and collaborate more effectively with deeper insights. Salesforce has named IBM as a preferred cloud services provider and IBM has named Salesforce as its preferred customer engagement platform for sales and service, the companies said in a release. "This expanded partnership builds on the combined power of Watson and Einstein to help enterprises make smarter business decisions," said Ginni Rometty, IBM's chairman, president and chief executive officer. Watson and Einstein are the artificial intelligence platforms of IBM and Salesforce respectively. As a part of this extended strategic partnership, IBM will build newIBM WatsonQuip Live Apps, bringing the power of Watson and Quip together.

Qoints has launched an influencer marketing tool that uses the artificial intelligence of IBM's Watson to unearth the best influencers for your brand. The Qoints AI Social Discovery tool is a self-service tool that helps marketers deal with the problem of finding the right influencers for marketing campaigns. Locating the right micro influencers (those with 5,000 to 50,000 followers) is key to making influencer marketing effective and affordable. But it's a tedious process to manually search for the right influencers. Demand for influencers is growing, as they've been shown to generate higher levels of trust, engagement and purchase intent from their followers (in comparison to celebrity influencers), according to Toronto-based Qoints.