Cloud accounting software startup Smacc has raised 3.5 million in Series A funding from Cherry Ventures, Rocket Internet, Dieter von Holtzbrinck Ventures, Grazia Equity, and a number of angel investors. The Potsdam-based company uses AI to automate the accounting and financial processes for small and medium sized enterprises. The company's proprietary technology uses machine learning to continuously improve the automation process and provide real time financial transparency. Customers' financial data is secured with "state-of-the-art" encryption, according to the startup, and stored in data centres in Germany. "The capital from the financing round will be used to expand our proprietary technology platform and further accelerate growth," said cofounder Janosch Novak.

Cozmo is a 179 artificially intelligent robot that can recognize faces and react to human gestures. SAN FRANCISCO – At first glance, the palm-sized toy on the table looks unexceptional, an odd cross between a bulldozer and a forklift. Except that the toy is snoring. Suddenly, it wakes up, motors over to its human inquisitor and lets out a happy squawk as its digital eyes go wide. Made by Anki, the start-up that has found success with its self-driving Anki Drive racing cars, Cozmo goes on sale today for 179 with orders shipping this fall.

Artificial intelligence will take over the world! "There's very smart people, whether it's Elon Musk or Jeff Bezos or Bill Gates or Stephen Hawking, who have said, 'Oh my gosh, this is really dangerous,'" Hawkins said. Hawkins stressed that Numenta is specifically trying to reverse engineer only part of the human brain: The neocortex, which is what lets us learn and create a model of the world based on our environments and experiences. You can listen to Recode Decode in the audio player above, or subscribe on iTunes, Google Play Music, TuneIn and Stitcher.

In this week's Brain Boost: Adidas' robots, AI and humans, and getting started with crowdfunding. Adidas' Robots Robotic manufacturing is going beyond cars for the first time. Adidas, the German sportswear company, announced that the first ever robotic reproduced shoe line will be available to customers in 2017 and, though Adidas is not aiming for full robotic automation, it is looking to learn more about the possibilities of robotic manufacturing, starting with this for a series of shoes. AI Humans However, on the other side of the Atlantic, the 2016 Exponential Manufacturing Conference wrapped up and one of the world's foremost data scientists, Professor Sandy Pentland of MIT, says that artificial intelligence is best used in collaboration with humans. Professor Pentland says that one of the most common challenges to large organizations is delivering the right information to the right people at the right time and he's proposing that software developers use artificial intelligence programs to predict who needs what data when and where and then use the internal computing systems to deliver key figures, best practices, etc. at the right time to the right people.

The factory floor is a marvel of automation. With a press of a button, the whole place can seem to run itself. But although today's factories use automated workflows, process change is still mostly manual. When demands arise in an industrial environment, managers and engineers must interrupt the automation to update the processes that make the machines go. Now, thanks to machine learning algorithms, it's becoming possible for smart software to scrutinize data from a variety of sources -- sensors on machines or changes in supply chains, for instance -- and redesign processes in real time.

Better, faster, more productive... these used to be words to describe what we wanted from our internet broadband connection. Now they describe what we expect not only from all our products and services but also from each other. The expectations that we have from the world and the world has from us are dynamic, ever-changing and transforming at speed. AI is all around us. Complicated and repetitive tasks are better performed by computer algorithms and mechanisms than by the human mind.

Microsoft envisions Cortana doing much more than reminding us to pick up toilet paper on the way home from work. Back in 2014, we Windows Phone fans could barely contain ourselves as we eagerly awaited Cortana's arrival on Windows Phone 8.1. At the time, like many writers, I had a vision of what Cortana would mean for Microsoft and mobile computing. So, well, I wrote about it. Alas, time has moved on, and that initial fervor that fueled the "Cortana conversations" of many Windows phone fans has transitioned through other topics. The Lumia 950 and 950 XL had their time in the limelight. HoloLens enters and re-enters the conversation. Windows 10 updates are a consistent topic, further fueled by Gabe Aul's passing of the torch to Dona Sarkar as the new face for the Insider Program.

CVPR 2016 -- CEVA, Inc. (NASDAQ: CEVA), the leading licensor of signal processing IP for smarter, connected devices, today introduced CDNN2 (CEVA Deep Neural Network), its second generation neural network software framework for machine learning. CDNN2 enables localized, deep learning-based video analytics on camera devices in real time. This significantly reduces data bandwidth and storage compared to running such analytics in the cloud, while lowering latency and increasing privacy. Coupled with the CEVA-XM4 intelligent vision processor, CDNN2 offers significant time-to-market and power advantages for implementing machine learning in embedded systems for smartphones, advanced driver assistance systems (ADAS), surveillance equipment, drones, robots and other camera-enabled smart devices. CDNN2 builds on the successful foundations of CEVA's first generation neural network software framework (CDNN), which is already in design with multiple customers and partners.

Deep learning is the new big trend in machine learning. It had many recent successes in computer vision, automatic speech recognition and natural language processing. The goal of this blog post is to give you a hands-on introduction to deep learning. To do this, we will build a Cat/Dog image classifier using a deep learning algorithm called convolutional neural network (CNN) and a Kaggle dataset. This post is divided into 2 main parts. The first part covers some core concepts behind deep learning, while the second part is structured in a hands-on tutorial format. In the first part of the hands-on tutorial (section 4), we will build a Cat/Dog image classifier using a convolutional neural network from scratch.

Some of the behemoths giving a tough race to Google are Amazon, Apple Inc., Facebook, and Microsoft. A common platform on which they're all competing is a digital assistant to help with daily needs. Some of their AI-powered virtual assistants are Facebook's M, Apple's Siri, Microsoft's Cortana, Amazon's Echo and Allo's Google Assistant. While Amazon's Echo is a device solely serving as a virtual assistant, both Facebook's M and Allo's Google Assistant start at a disadvantage with the user first needing to install the app to exercise the luxuries of a digital assistant. One of the unique features of Allo is the Smart Reply built in, giving users the option of searching for restaurants, movie tickets, and information regarding flight delay without moving out of the chat.