Artificial intelligence (AI) is steadily growing more sophisticated, particularly in regards to advanced decision making capabilities, making it increasingly appealing to corporations. It's quite simple for AI to predict a temporary employee's success in completing a single task. When developing artificially intelligent software, companies have been tasked with giving the software a human touch that encourages people to welcome AI into their business and personal lives. Specialising in cloud business management, Tithof leads Unit4's business, being responsible for developing new business, strategic account selling and continuing the successful partnerships with Agilyx, Connexxion and S1 Consulting within the region.

Artificial intelligence (AI) is steadily growing more sophisticated, particularly in regards to advanced decision making capabilities, making it increasingly appealing to corporations. A survey from Narrative Science shows that 62 per cent of organisations will be using AI technologies by 2018, while Gartner is predicting that three million employees worldwide will be supervised by AI in 2018. The question that remains is what will this transformation look like? While computers are capable of making intelligent decisions about financial trading, medical diagnoses and even flying planes or driving cars, several factors have kept businesses from adopting AI broadly. One of these is accessibility.

The company is launching Allo, it's AI-centric messaging app for iOS and Android that offers an early peek at some of its most robust artificial intelligence capabilities yet. First previewed during its I/O developer conference earlier this year, the app combines the best of Google's predictive and search superpowers along with an all-new personal assistant feature. At first glance, Allo looks very similar to many other messaging apps. You sign up with your phone number and, after verifying your identity, the app scans your address book to find people you may know who are also using the app. Beginning a one-on-one or group chat is fairly straightforward.

The company is launching Allo, it's AI-centric messaging app for iOS and Android that offers an early peek at some of its most robust artificial intelligence capabilities yet. First previewed during its I/O developer conference earlier this year, the app combines the best of Google's predictive and search superpowers along with an all-new personal assistant feature. At first glance, Allo looks very similar to many other messaging apps. You sign up with your phone number and, after verifying your identity, the app scans your address book to find people you may know who are also using the app. Beginning a one-on-one or group chat is fairly straightforward.

SHANGHAI--A Chinese man whose son was killed while driving a Tesla Motors Inc. TSLA -0.82 % vehicle applied to a local Beijing court to investigate whether the car's Autopilot driving system was engaged. In January, 23-year-old Gao Yaning died in a crash in the northeastern province of Hebei while driving a Tesla Model S. Six months later his father, Gao Jubin, filed a lawsuit accusing Tesla of exaggerating Autopilot's capabilities. At a court hearing Tuesday, he asked for an independent investigation of the cause of the crash. "The family insists the investigation should be done by a third party, rather than Tesla," said Cui Qiuna, a lawyer for the Gao family. The court will study the family's request.

In the 2016 Google Founder's Letter, CEO Sundar Pichai cited Google's long-term investment in machine learning and AI. "It's what allows you to use your voice to search for information," he explained, "to translate the web from one language to another, to filter the spam from your inbox, to search for'hugs' in your photos and actually pull up pictures of people hugging ... to solve many of the problems we encounter in daily life. It's what has allowed us to build products that get better over time, making them increasingly useful and helpful." In addition to using machine learning for its own products, Google has released several applied machine learning services -- for vision, speech, natural language, and translation -- and has open-sourced its TensorFlow scalable machine learning package. An additional service based on TensorFlow, the Cloud Machine Learning Platform, is still in a closed alpha test phase.

For all its promise of delivering a bold future, the green energy industry is still decidedly low tech when it comes to moving merchandise. Solar panels are still sold door-to-door, a slow and expensive process that has impeded the industry's growth. Now, a California startup thinks it has a solution, using sophisticated data science to find consumers likely to adopt solar power and let them know just how much they can save on their electric bills. PowerScout, a machine-learning-enabled eCommerce platform for solar energy, aims to eliminate marketing costs that, according to CEO Attila Toth, can exceed the cost of the actual equipment for some green-power vendors. "This is very absurd--very crazy," Toth says.

It's your nighttime routine: You drop your phone onto the nightstand charging pad, and it asks about your day. You tell it, talking to the virtual personal assistant just like you'd talk to a friend. Your phone's artificial intelligence knows you almost as well as you know yourself (maybe even better). So when it suggests ways to get through tomorrow's calendar, you trust its advice. AI is practically everywhere, and getting smarter all the time.

The 2016 is the year of Artificial Intelligence and chatbots are a very interesting testing environment for the upcoming massive adaption and commercialization of AI applications. This is a great summary and infographic about the #bots platform ecosystem! It s very interesting to see how fast consolidation in the market is happening (2 acquisition in the last 24 hours, Google - Api & Amazon - Angel.ai) and as usual in the tech industry, see that the most active acquirers are the best tech companies! Bots got really quickly overhyped, and this hype is driving developers to build bots without much thought for how useful they will be or who would use them. Big companies like Facebook are also pushing quick adaption to discourage new entrances in the market by promising (over promising) smart bots, interactive bots for communication between people and business and by exaggerating bots capacity. However as my friend Matt Schlicht said in his article: "Chatbots Suck Now But They Will Get Better" and the BOT ECONOMY is becoming one of the faster growing economy ever.

IBM and MIT announced a joint research partnership, with the aim of creating artificial intelligence that understands audio and visual data the way people do. At a high level, IBM Research and MIT's Department of Brain and Cognitive Sciences are forming the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension's (BM3C). There, researchers will work to develop cognitive computing systems that can overcome the technical challenges surrounding pattern recognition and predictions methods. As IBM explains, a human can watch a short video of an event and easily describe what is happening during the video and even predict the likelihood of subsequent events. For machines, this ability is currently impossible, IBM says.