FD Tech update

Facebook is working on products you’ll control with your voice

Social network Facebook announced that it is working on products that could benefit from an AI voice assistant. Facebook had an assistant called M that it had launched in the year 2015 that made use of human helpers to perform requests from users, but Facebook shut the project down in 2018.
Facebook CEO Mark Zuckerberg said: “I imagine there are going to be more products that we build where voice is going to be an important interface over the coming years. We’re working on a lot of different things around this.”

Twitter buys London startup that uses AI to detect fake news

Social networking service provider Twitter announced that it has taken over Fabula. Fabula is a London-based information technology and service provider that detects fake news on Twitter by using machine learning to examine behaviour including tweets likes, and retweets, to help the social network build up a picture of relationships and the type of interactions.
Parag Agrawal, Twitter’s chief technology officer, said: “This strategic investment in graph deep learning research, technology and talent will be a key driver as we work to help people feel safe on Twitter and help them see relevant information.”

Facebook approaches Robot Learning a little differently

Facebook helps its robots learn through self-supervised learning. The team at Facebook implemented this approach to let the robot figure out for itself what the best movements are to complete its goal. Facebook used this method to focus on the human being’s innate curiosity, which is a major contributor to a person’s ability to learn and process new ideas. Franziska Meier, an AI research scientist at Facebook, said: “Although it didn’t achieve the task, it gave us more data, and the variety of data we get by exploring like this is bigger than if we weren’t exploring.”

Google’s New ‘AI Workshop’ Offers Early Access To The Frontier Of AI Research

Tech giant Google has announced an opportunity for developers to explore pilot experiments based on some of Google’s frontier AI research called “AI Workshop.” Google defines its new AI Workshop as an opportunity for “customers, partners, researchers, and developers” to experiment with “new concepts, new techniques, and new applications at the furthest extents of science and technology” in order to “connect research and practice so that we can address enterprise AI challenges together.”
Google essentially aims at externalizing selected enterprise-relevant AI research in a way that Google’s own research teams building those tools can communicate directly with potential users to understand how those innovations might be used in the real world and what kinds of use cases the algorithms would need to cope with and to learn more about their limitations and strengths.

Google’s EfficientNets are better at analyzing images than existing AI models

Google has  announced that its EfficientNets is much more accurate at analysing images than its existing AI models. AI models make use of convolutional neural networks (CNNs) that scale network dimensions such as the width, resolution and depth for object recognition and facial detection, whereas EfficientNets provides up to ten times better efficiency by scaling each dimension using fixed sets of scaling coefficients.
Staff software engineer Mingxing Tan and Google AI principal scientist Quoc V. Le., said: “The conventional practice for model scaling is to arbitrarily increase the CNN depth or width, or to use larger input image resolution for training and evaluation. Unlike conventional approaches that arbitrarily scale network dimensions, such as width, depth, and resolution, our method uniformly scales each dimension with a fixed set of scaling coefficients.”

Google’s DeepMind AI Learns To Beat Human Players At ‘Quake III’

Google has announced that its DeepMind AI naturally learned the ability to win over human players at the game Quake III. The technology giant says that its DeepMind researchers were able to use advanced AI techniques to advance from absolute beginner to consistently beating human players in the game Quake III.
Both the players and the bots were provided with the same details about the game, but the bots were quick at learning the strategy and won more than fifty percent of the time. The advanced ability of the bots in remembering the layout of the game mostly contributed to their success.

Salesforce launches blockchain channel

San Francisco-headquartered cloud-based software company Salesforce announced the launch of its new low-code blockchain channel. This new low-code platform called Salesforce Blockchain enables organizations to share verified, distributed data sets across a trusted network of partners and third parties. Customers can now create and share a blockchain object using the same approach as they already do for any CRM data object in Salesforce without the need for writing code. This would also help organisations to create blockchain networks, workflows and apps to deliver entirely new customer experiences.

IBM debuts self-service AI-powered ad experience

Information technology group IBM announced the launch of Watson Ads Builder that makes use of AI to enable conversations between brands and consumers. It is a self-service advertising solution that uses AI designed to grant creative agencies and developers in building engaging, one-on-one conversations between brands and consumers across any digital property.
Jeremy Hlavacek, head of revenue for IBM Watson Advertising, said: “Consumer expectations are shifting, and people expect the ability to communicate with brands on demand. Watson Ads Builder can change where, when and how brands connect with consumers -helping marketers increase loyalty and purchase consideration.”

Siemens and SAS partner to deliver AI-embedded IoT analytics

Munich-headquartered automation company Siemens teamed up with SAS to help companies deliver AI-embedded IoT analytics. This partnership would let companies create new IoT edge and cloud-enabled solutions by implementing the use of SAS and open source streaming analytics through Siemens’ MindSphere.
Stephen Bashada, executive vice president and general manager of Siemens MindSphere, said: “SAS is a recognized world-leader in advanced analytics, machine learning, and artificial intelligence. We are excited to leverage their analytics in MindSphere. The combination of Siemens’ deep industrial domain knowledge with SAS’ deep analytics knowledge is a powerful step forward for IoT.”

Amazon’s new AI can process millions of documents in just a few hours

E-commerce giant Amazon has announced a new artificial intelligence feature for its web services called Textract. Textract possesses the ability to read millions of pages of documents in just a few hours. It can detect multiple document formats to properly and efficiently process information. This feature is designed to have the ability to recognize the various formats of documents from where it would be pulling the text, whether it’s from the tables or forms.
Swami Sivasubramanian, vice president of Amazon Machine Learning, said: “The power of Amazon Textract is that it accurately extracts text and structured data from virtually any document with no machine learning experience required.”

Hollywood is quietly using AI to help decide which movies to make

Los Angeles-based provider of AI driven decision support for the entertainment industry Cinelytic is providing a machine learning algorithm that can predict the success of a movie. This algorithm acquires historical data about movie performances over time, then cross references it with information about films’ themes and key talent. It then makes use of machine learning to tease out hidden patterns in the data. Its software lets customers input the cast of the movie, then swapping one actor for another to see how this affects a film’s projected box office.
Cinelytic Co-founder and CEO Tobias Queisser, said: “Say you have a summer blockbuster in the works with Emma Watson in the lead role. You could use Cinelytic’s software to see how changing her for Jennifer Lawrence might change the film’s box office performance. You can compare them separately, compare them in the package. Model out both scenarios with Emma Watson and Jennifer Lawrence, and see, for this particular film … which has better implications for different territories.”

CredoLab: Driving better credit decisions with machine learning

Singapore-based financial service company CredoLab developed bank-grade digital scorecards for banks, consumer finance companies, auto lenders, online and mobile lenders, insurance companies, and retailers. The company’s machine learning algorithm that’s developed on mobile device data and powered by AI, yields secure and customized scorecards developed on the credit outcome data, boosting users Gini coefficient.
Peter Barcak, co-founder & CEO, CreadoLab, said: “With the boom in technology using AI, we can now pull the plug on all the unfair vagueness that traditional credit scored was plagued with and open the credit industry to a wider pool of people who are just as creditworthy.”

Indian government to use fintech for flagship programmes

The new Indian Government is all set to make use of financial technology to revolutionise its flagship programmes. The development of fintech in Indian would result in creating opportunities for exponentially more personalized and faster customer experiences, significantly better insights, and automation of back-end workflows consisting of customer acquisition, KYC and on boarding, accounts and loans, customer service, brand management and risk & credit.
Sharing his outlook at the ASSOCHAM Fintech Summit, NITI Aayog CEO Amitabh Kant said: “India is the third largest and one of the fastest growing Fintech markets globally, attracting about $6 bn in investments since 2014. Industry reports estimate that India’s total fintech software and services market is expected to grow to $13bn with the software market alone set to touch $2.4 bn by 2020.”

Russia Raises $2bn for investment in AI

Russia’s sovereign wealth fund The Russian Direct Investment Fund (RDIF) has raised $2 billion from foreign investors. The amount that has been raised will be used to support domestic companies developing AI solutions. The funds for AI development were raised from “partners from large sovereign funds and global corporations from the Middle East and Asia,” RDIF representatives told Vedomosti. RDIF has also prepared for a meeting with President Vladimir Putin on AI advancement in Russia.

Comments are closed.