Reply is the place to meet an incredible variety of enthusiastic, passionate, ideas-driven people, who want to make a difference and an impact.Would you like to know more?
Artificial Intelligence has recently experienced a real boom in the interests of companies. With the advent of modern deep learning, we have gained a real insight into Ai-driven technologies in practice: from the creation of medical diagnoses, the identification of criminals in crowds to autonomous driving. But the history of AI began earlier than you might think.
Digitization and the triumph of smartphones have led to ever more compact and at the same time more cost-effective computing power – in addition to sensors and cameras, which are also declining in price, but more sophisticated. The increasing competition between established and new players is currently leading to more and more AI-specific chip innovations. In 2008, the world's first single-teraflop supercomputer cost USD 100 million and filled an entire room. Nvidia's Titan V, launched in 2017, is an AI processor chip with a capacity of 110 teraflops.
AI systems live on data. The more data an algorithm can analyze, the better it can recognize and understand patterns. The still growing spread of mobile devices, the progress of the Internet of Things or the beginning use of self-propelled cars, will massively increase the amount of available digital data.
The algorithms used today for speech recognition and natural language translation have evolved remarkably over the last decade: What used to take weeks with a previous algorithm is now often solved within hours with new statistical models, neural network designs and learning methods.
Virtual reality shopping is giving consumers the convenience of online shopping and the experience of being in a store at the same time – in order to experience stores, products and service in a whole new way. With the help of VR or AR applications customers will be able to try and test products – at home or in-store – more easily, and in a more personalized or gamified manner. Virtual reality technology will play a secondary role, while augmented reality apps will continue being the forefront, according to Stewart Rogers, author and analyst at VentureBeat. In his opinion, "dealers who don't discover mobile AR for themselves within the next six months will lose ground".
Mythic has developed a deep learning inference model. It is based on digital and analog calculations and is able to eliminate expensive processors while extending battery life by a factor of 50 (or more). The dimensions that this new design enables: Essential high-end desktop GPU compute functions can be handled by a module the size of a shirt button that can run for years like the performance of a watch battery.
A concrete application of AI can be found in the Signall Sign Language solution from SignAll, the world's first automated translation solution for sign language. The product is based on Computer Vision and NLP. The prototype is currently capable of translating part of an ASL user's vocabulary and generating text from the user's hands and gestures.
We are in a phase of digital transformation in which data not only accelerates decision-making processes, but also forms the basis for future decisions with the help of predictive analytics. Companies across multiple industries are using AI-as-a-Service solutions from both established vendors and start-ups and increasingly purchasing "out-of-the-box" AI-based enterprise tools to obtain Amazon-like personalization, Google-like search mechanisms, and IBM Watson-like predictive capabilities.
Dynamic Yield provides an end-to-end enterprise platform for personalization. It leverages an organization's existing customer data with additional data sources to create accurate and detailed customer profiles. The platform is used by more than 220 brands worldwide who want to take their personalization capabilities to a similar level as Amazon.
Google is also working to simplify the use of AI. With Google's Cloud AutoML, companies with limited expertise can create customized machine learning models with their own data and labels without writing a single line of code.
Human-machine interfaces are on their way to becoming more and more natural and to replace smartphones or tablets; "How Smart Speakers stole the show from Smartphones" was the Guardian's headline on this topic at the beginning of 2018. Tech giants in particular, but also newcomers are competing to be the developers of the "next platform". They use AI to increase the intuitiveness and intelligence of existing and new interfaces. Conversational user interfaces – especially voice-activated solutions – have experienced a massive increase in media attention and consumer acceptance in recent years, due to improved processing and understanding of natural language. However, progress is also being made in the area of emotionally intelligent and empathetic AI, which means that more and more home robots can be developed. One example is Amazon, which plans to launch its first home robot in 2019.
A very well-known example of the use of AI-supported voice-controlled interfaces is Google Duplex, which arranged a hairdresser appointment for a customer in a lifelike telephone call during I/O 2018. Xiaoice (pronounced Shao-ice) from Microsoft has also made it to a similar fame. The chatbot has 500 million followers, who can interact with Xiaoice. In addition to text chats, she is also capable of telephone conversations.
Olly, on the other hand, is the first home robot with an evolving personality that adapts to each individual user. This brain-inspired AI system, developed by Emotech's leading AI researchers and neuroscientists, is therefore capable of more than just executing commands.
Artificial Intelligence is well on the way to automating cognitive tasks in addition to repetitive manual tasks. Today, autonomous systems are not only used in factories, but more and more on our roads, in the air, on the water and in offices. Today, advanced AI-based systems are driving preventive plant maintenance and the optimization and automation of supply chain operations. And increasingly sophisticated and diverse robotic process automation tools are helping to automate everyday rule-based business processes, allowing companies to spend more time on higher-value work. According to Elon Musk, founder and CEO of Tesla, road traffic will also experience a revolution: "I think we will see how autonomy and artificial intelligence advance tremendously. My guess is that in probably ten years it will be very unusual for cars to be built that are not fully autonomous", says Musk.
UIPath develops a platform that enables the automation of robotic processes without specific know-how. The company thus offers development tools for the automation of complex processes in cloud or on-premise versions. The platform allows several robots to run on a single virtual machine.
Reuters relies on AI for journalism: Lynx Insight. The tool will help journalists analyze data, tell stories and even write sentences. This is not to replace reporters, but to support them with a digital assistant instead. Lynx Insight, which has been tested by dozens of journalists since the summer, is now being introduced to Reuters editorial staff.
Predictive analytics will have a massive impact on the condition of machinery and equipment. By combining sensors, IoT platforms and AI-controlled analysis tools, companies will not only be able to monitor their equipment, but also predict failures and outages.
Enhanced interfaces will increasingly close the gap in Artificial Intelligence between IQ-intensive interactions and EQ-driven experiences, allowing brands to engage with customers at a much deeper, personalised level.
Thanks to breakthrough advances in computer vision, computers can recognise things faster and see differences that people can't see. Businesses can use these features to gain better insight into consumers or analyse vast amounts of visual data.
Chatbots for customer service, AI process automation, and AI-driven decision making reduce the effort required for more everyday cognitive tasks. This allows employees and organizations to focus more on higher-value tasks and work that requires more imagination or creativity.
SONAR is an innovative, Data-as-a-Service Tool for quantified foresight.
It recognizes, compares and analyzes existing trends, and identifies new developments in real-time.