Japanese automaker Toyota Motor Corp wants consumers to connect with mini talking robots. The talking robot called Kirobi Mini, whose name comes from "hope," is just as smart as a 5-year-old. The 4-inch-tall Kirobo Mini is small enough to be carried around. When people place the Kirobo Mini in their cars, it encourages safe driving by saying phrases like "Oops!" when the driver steps on the brakes suddenly, and "Don't leave me behind", when left in the vehicle. The Kirobi Mini comes equipped with Bluetooth, camera and microphone, and can connect to a smartphone, but needs to be installed with a software application.

Samsung Electronics Co. SSNHZ 0.00 % said Thursday that it will buy U.S. artificial intelligence company Viv Labs Inc., as the South Korean smartphone giant turns to the creators of Apple Inc. AAPL 0.04 % 's Siri service to beef up its own mobile software and services. The deal, for an undisclosed amount, is Samsung's fourth U.S. technology company acquisition in a little more than two years, underscoring the technology player's new willingness to look outside the company to spur innovation, particularly in areas like software, where it has traditionally been weak. The aim for Samsung is to pack its phones with more eye-popping features to help its premium devices stand out from a pack of competitors, including Apple's iPhones. After its acquisition last year of mobile payments startup LoopPayfor about 160 million, Samsung adopted the Burlington, Mass.-based company's technology to launch Samsung Pay, a mobile payment service that rivals Apple Pay. Samsung is looking to follow a similar model with San Jose, Calif.-based Viv Labs, which was founded four years ago by a team that includes Siri co-creators Dag Kittlaus and Adam Cheyer.

Samsung Electronics Co. is joining the race to create the smartest digital assistant by acquiring Viv, a Silicon Valley start-up launched by the same entrepreneurs who sold Siri to Apple. The deal announced Wednesday provides Samsung with technology to compete against Google Inc., Amazon.com Inc., Microsoft Corp. and Apple Inc. in the increasingly important field of programming computers to learn and respond as if they were human. The specialty, also known as artificial intelligence, has hatched a flock of voice-activated digital concierges -- such as Siri, Amazon's Alexa, Microsoft's Cortana and Google's Assistant -- that work in personal computers, smartphones and Internet-connected speakers. Samsung plans to implant Viv into phones, televisions and a wide range of other devices. The South Korean company did not disclose how much it paid for the start-up.

From Siri creator Dag Kittlaus comes Viv, a product that aims to be the next generation personal assistant. Kittlaus sat down with USA TODAY's Ed Baig to talk about Viv and where he thinks its headed. Samsung plans to make its range of smartphones smarter with its acquisition of Viv, an AI virtual assistant platform started by the man who created Siri. SAN FRANCISCO -- Samsung Electronics just accelerated into the voice-assistant fast lane. The South Korean electronics company, which has been grappling with extended fallout from its recalled Galaxy Note 7, announced Wednesday that it was buying Viv, the machine-learning virtual assistant company started by Siri founder Dag Kittlaus.

Samsung, the largest maker of televisions and smartphones in the world, is buying Viv Labs, a high-profile artificial intelligence startup founded by the inventors of Apple's Siri voice assistant, the South Korean electronics conglomerate said Wednesday. The move is a major land grab in the battle for cutting-edge artificial intelligence taking place among tech giants. Samsung, which has lagged in such services, is now positioned to add intelligent, Siri-like voice capabilities to its vast collection of home and mobile electronics. "We have a unique opportunity to take advantage of AI, and show the rest of the industry what the smart, connected world can look like," Jacopo Lenzi, Samsung's Senior Vice President of Business Development and Strategic Acquisitions, said in an interview. The companies declined to disclose the purchase price of the deal.

Samsung said in a statement it plans to integrate the San Jose-based company's AI platform, called Viv, into the Galaxy smartphones and expand voice-assistant services to home appliances and wearable technology devices. Technology firms are locked in an increasingly heated race to make AI good enough to let consumers interact with their devices more naturally, especially via voice. Alphabet Inc's Google is widely considered to be the leader in AI, but others including Amazon.com, Apple and Microsoft have also launched their own offerings including voice-powered digital assistants. Samsung, the world's top smartphone maker, is also hoping to differentiate its devices, from phones to fridges, by incorporating AI.

To infer multilayer deep representations of high-dimensional discrete and nonnegative real vectors, we propose an augmentable gamma belief network (GBN) that factorizes each of its hidden layers into the product of a sparse connection weight matrix and the nonnegative real hidden units of the next layer. The GBN's hidden layers are jointly trained with an upward-downward Gibbs sampler that solves each layer with the same subroutine. The gamma-negative binomial process combined with a layer-wise training strategy allows inferring the width of each layer given a fixed budget on the width of the first layer. Example results illustrate interesting relationships between the width of the first layer and the inferred network structure, and demonstrate that the GBN can add more layers to improve its performance in both unsupervisedly extracting features and predicting heldout data. For exploratory data analysis, we extract trees and subnetworks from the learned deep network to visualize how the very specific factors discovered at the first hidden layer and the increasingly more general factors discovered at deeper hidden layers are related to each other, and we generate synthetic data by propagating random variables through the deep network from the top hidden layer back to the bottom data layer.

Machine learning, which involves programs that get more accurate with experience, is fundamentally different from any kind of computing that's come before. "There's always been a simple division of labor: machines do number crunching, and humans make decisions," says Pradeep Dubey, an Intel Fellow at the company's Intel Labs division. Machine-learning programs--and in particular the high-profile deep-learning subset that can teach themselves--are different. These programs have the potential to discover new drug compounds or identify consumer trends without human intervention. For Dubey and others at Intel, it was clear that they needed to find a way to make machine-learning programs work well on Intel's architecture.

Source(d), a Madrid, Spain-based startup that uses artifical intelligence to identify the most suitable developers for respective jobs, raised 6m in funding. Backers included Xavier Niel, Otium Venture and Sunstone Capital. The company intends to use the funds for commercial expansion in Europe and the United States and continued improvement of the artificial intelligence algorithms. Founded in March of 2015 by CEO Eiso Kant, Jorge Schnura and Philip von Have, source{d} develops deep learning (artificial intelligence) algorithms to identify, qualify and present developers to companies, by analyzing their code. By basing their approach on technical understanding, the process guarantees that the needs of their clients are met and the developers fit better with their technical challenge.

Last week IBM announced they had entered into a definitive agreement to acquire strategic consultancy Promontory Financial Group. Promontory is not exactly a household name, but they are one of the very top tier of global banking consultancies, with a particular focus on regulation and compliance. IBM cite a McKinsey figure of 270 Billion costs related to compliance, which consists of direct compliance spend of 99 Billion, with the remainder accounted for with other forms of compliance leakage (fines, damage to goodwill etc.). For clarity we must state that there is no public data available for this figure, but it seems in-line with other research that is available. In many ways the figures are somewhat irrelevant, if we look at, for example, the destruction to shareholder value that can occur when a financial institution is not in compliance with relevant rules and regulations.