It is never easy to predict what society and technology will look like in the coming decades, but one futurist used the imaginations of children to come up with ideas. Futurist Brian David Johnson spoke to kids aged 8-13 as part of a study into their vision of life in the 2050s for the Institution of Engineering and Technology (IET). 'The current generation of young minds is nothing like we've seen before', Johnson explained, saying they were born and grew up constantly connected. Every child he spoke to was optimistic about the future, with many showing'jump-out-of-their-seat' levels of excitement about'what is to come' as they reach adulthood. He used the conversations he had with the children and their parents to formulate predictions about the future of smart homes, food and personal virtual assistants. Futurist Brian David Johnson spoke to children aged 8-13 as part of a study into their vision of life in the 2050s for the Institution of Engineering and Technology (IET).

Session-based recommendation has received growing attention recently due to the increasing privacy concern. Despite the recent success of neural session-based recommenders, they are typically developed in an offline manner using a static dataset. However, recommendation requires continual adaptation to take into account new and obsolete items and users, and requires "continual learning" in real-life applications. In this case, the recommender is updated continually and periodically with new data that arrives in each update cycle, and the updated model needs to provide recommendations for user activities before the next model update. A major challenge for continual learning with neural models is catastrophic forgetting, in which a continually trained model forgets user preference patterns it has learned before. To deal with this challenge, we propose a method called Adaptively Distilled Exemplar Replay (ADER) by periodically replaying previous training samples (i.e., exemplars) to the current model with an adaptive distillation loss. Experiments are conducted based on the state-of-the-art SASRec model using two widely used datasets to benchmark ADER with several well-known continual learning techniques. We empirically demonstrate that ADER consistently outperforms other baselines, and it even outperforms the method using all historical data at every update cycle. This result reveals that ADER is a promising solution to mitigate the catastrophic forgetting issue towards building more realistic and scalable session-based recommenders.

Natural Language Processing is among the hottest topic in the field of data science. Companies are putting tons of money into research in this field. Everyone is trying to understand Natural Language Processing and its applications to make a career around it. Every business out there wants to integrate it into their business somehow. Because just in a few years' time span, natural language processing has evolved into something so powerful and impactful, which no one could have imagined.

In the near future, you'll be able to launch and navigate Android and iOS apps using Alexa voice commands. Today, Amazon released a bunch of new developer tools. The most interesting might be Alexa for Apps, which allows developers to add Alexa functions to their Android and iOS apps. Amazon has tested the tool with companies like TikTok, Uber, Yellow Pages and Sonic. So already, you can ask Alexa to start your TikTok recording or open the Sonic app so you can check the menu.

Salesforce has quietly shuttered Einstein Voice Assistant and Einstein Voice Skills as it shifts focus towards its newly released Salesforce Anywhere app. The Einstein Voice Assistant first launched in beta last year. It's an extension of the company's Einstein Voice platform and allowed users to interact with the Salesforce platform via a mobile app or smart speaker device. Salesforce claimed the AI helper was more advanced than other digital assistants on the market, such as Alexa and Cortana, as it could be taught to recognise a company's specific jargon and acronyms. Einstein Voice Skills, which debuted in beta last November, enabled developers and admins can build custom voice-powered apps for employees to replace any type of manual data entry or manual Salesforce navigation.

The potential for the Internet of Things to lead to distortion in market competition is troubling European Union lawmakers who have today kicked off a sectoral inquiry. They're aiming to gather data from hundreds of companies operating in the smart home and connected device space -- via some 400 questionnaires, sent to companies big and small across Europe, Asia and the US -- using the intel gleaned to feed a public consultation slated for early next year when the Commission will also publish a preliminary report. In a statement on the launch of the sectoral inquiry today, the European Union's competition commissioner, Margrethe Vestager, said the risks to competition and open markets linked to the data collection capabilities of connected devices and voice assistants are clear. The aim of the exercise is therefore to get ahead of any data-fuelled competition risks in the space before they lead to irreversible market distortion. "One of the key issues here is data. Voice assistants and smart devices can collect a vast amount of data about our habits. And there's a risk that big companies could misuse the data collected through such devices, to cement their position in the market against the challenges of competition. They might even use their knowledge of how we access other services to enter the market for those services and take it over," said Vestager.

AI isn't the end-all-be-all when it comes to conversational experiences like Amazon's Alexa. In fact, manual solutions to problems are sometimes superior to automated, AI-driven fixes. That's according to Amazon Alexa AI director of research science Janet Slifka, who spoke during a session today at VentureBeat's Transform 2020 conference. "If someone calls customer service and says something to the effect, 'Alexa doesn't understand me,' in many cases, we can be faster to the customer with a manual fix," Slifka said, describing her team's work in triage. "In some cases, it's almost required when you need words to enter the lexicon. You're probably not going to wait until you rebuilt and deploy a statistical model when a new word gains prominence, like'Brexit.'"

Google Assistant users in India using KaiOS feature phones will now have access to Google Lens, a year after the capability first expanded to India. Now, anyone who owns a feature phone or other device built on the KaiOS operating system will be able to use Google Assistant to identify any text in the image and read it out loud or translate it to another language. Google first debuted Lens three years ago in the U.S. and brought it to India in 2019. Lens combines machine vision to see any text in an image, then applies the voice AI to read the words out loud in the original language or any number of other tongues. It can even define the words in the food label, graffiti, or, as in the example image, a street sign.

Conversational interfaces are powered primarily by natural language processing (NLP), and a key subset of NLP is natural language understanding (NLU). While NLU is a subset of NLP, NLP doesn't always involve NLU. The terms NLP and NLU are often used interchangeably, but they have slightly different meanings. Developers need to understand the difference between natural language processing and natural language understanding so they can build successful conversational applications. Natural language processing is a subset of AI, and it involves programming computers to process massive volumes of language data.

TierPoint, a leading provider of secure, connected cloud and data center solutions at the edge of the internet, announced it will host the third annual BraveIT conference as a virtual event, the morning of September 16 and afternoon of September 17, with title sponsor support from Dell Technologies, Nutanix, and VMware. The opening keynote will be delivered by Tom Gruber, who led the design team responsible for Siri, the intelligent assistant. The closing keynote will be delivered by Dan Doctoroff, formerly the Deputy Mayor of New York City and now CEO of Sidewalk Labs, a leader in the development of smart cities. And, back by popular demand from last year's conference, Major General Brett Williams, USAF (Ret.) will help enterprise teams assess their Cyber IQ. Tom Gruber was cofounder, CTO, and head of design for the team that created Siri in 2011, bringing AI to the mainstream user experience.