So, rather than looking for a reward in the game world, the algorithm was rewarded for exploring and mastering skills that led to it discovering more about the world. This type of approach can speed up learning times and improve the efficiency of algorithms, says Max Jaderberg at Google's AI company DeepMind. Its algorithm learned much more quickly than conventional reinforcement learning approaches. Imbibed with a sense of curiosity, Pathak's own AI learnt to stomp on enemies and jump over pits in Mario and also learned to explore faraway rooms and walk down hallways in another game similar to Doom.
In its simplest form, the answer is we need a platform that can integrate a wide variety of data sources: not just utility-owned data (eg asset location, asset type, smart meter data), but also external data sources such as weather patterns, customer-sited solar input and so forth. Now, we're working to turn these fault current indicators into smart line sensors that enable the smart grid to communicate the location of the fault instantaneously. The GOSI project set out to demonstrate real-time data integration and visualisation for distributed energy resources, evaluate benefits and use cases of a single-interface software platform – to provide a single software interface as a tool for distribution operators and engineers/power quality end users. The project developed key data, system, and user experience learnings through integrating more than 20 data sources into a single visualisation tool allowing users to view complex data sources in ways that were not possible through current solutions.
Today, with massive amounts of data and computational power easily available, this old idea, rebranded as "deep learning," is once again seducing thinkers, visionaries and practitioners all over the world, promising real artificial intelligence Artificial neural networks (ANNs) are a comparatively old family of artificial intelligence techniques, dating back to the 1950s. Some tasks intelligent algorithms typically perform are: automated language translation, text understanding and generation, converting speech to text and automated recognition of objects depicted in images. Machine learning refers to the family of intelligent algorithms able to make informed, non-trivial decisions of a specific kind, such as converting an image of a handwritten letter into a sequence of words. For example, if we carefully train a deep neural network to classify images, we will find out that the first layer trained itself to recognize very basic objects like edges, the next layer is able to recognize collections of edges such as shapes, the third layer trained itself to recognize collections of shapes like eyes or noses, and a further layer will learn even higher-order features like faces.
Using proprietary robotics technology, Sally can dispense and accurately measure 21 different healthy ingredients, including romaine, kale, seared chicken breast, Parmesan, California walnuts, cherry tomatoes and Kalamata olives. The Chowbotics' robot precisely measures each salad ingredient, ensuring that the customer order contains the exact number of calories listed on Sally's digital menu. Chowbotics CEO and founder Deepak Sekar says that fast food restaurants with Sally serving up salads will attract more health-conscious patrons, as her recipes with their healthy ingredients contain far fewer calories than the typical 400 calorie options available at many quick-serve restaurants and salad bars. "Sally is the next generation of salad restaurant," Sekar told the San Francisco Chronicle.
Businesses can dabble on the edges of these, for example developing Alexa "skills" that allow Amazon Echo owners to interact with a company without having to dial its call center, or jump right in, using the various cloud-based speech recognition and text-to-speech "-as-a-service" offerings to develop full-fledged automated call centers of their own. At Build in early May, it offered production versions of services previously only available in preview, including a face-tagging API and an automated Content Moderator that can approve or block text, images and videos, forwarding difficult cases to humans for review. The systems are available either already trained for particular tasks or as blank slates that can be trained on your data, and include image, text and video analysis, speech recognition and translation. This offers integrations with Amazon's speech recognition and understanding services, allowing businesses to create more sophisticated interactive voice-response (IVR) systems.
Since the announcement of Google's AI machine learning algorithm – RankBrain – in 2015, one of the most discussed topics in SEO galleries is: With Google admitting RankBrain being one of the top three ranking factors, these discussions have become even more worthwhile. Since the beginning of the Internet, artificial intelligence has played a relevant role in the operation of search engines. The AI does change the way Google is ranking websites but SEO wise, the recipe of success is pretty much the same: Great content, Avoid keyword stuffing, Add related keywords to the content and title, strong incoming links from highly trusted websites. We will have to understand how AI works in order to optimize sites to rank well.
The last quarter of 2016 and the first quarter of 2017 have been a phase dedicated to Artificial Intelligence (AI). Applications for Artificial Intelligence in Fintech industry are likely to boom in next couple of years where the entire Fintech industry and Banking system would be adding these kinds of applications to their solution.
For many in B2B and B2C marketing, once they get past the rush of new technology, some are wondering how long it will take to automate the entire marketing process (including their job). Michelle is Act-On's Chief Marketing Officer, and oversees the company's brand, demand, and customer expansion marketing efforts. Michelle comes to Act-On with 17 years' experience helping market leading companies, including Salesforce and Oracle, connect customers with technology solutions to grow their business. Prior to her tenure at Salesforce, Michelle was a Senior Director at Oracle and a Senior Product Marketing Manager at Stellent (acquired by Oracle).
For the German AI Landscape Map, we created a list of over 600 European AI startups based on internal research mainly deriving from our network and Crunchbase. We've ended up with 81 German Artificial Intelligence startups, which made it onto our map. The European AI landscape is growing but it is still very much in its infancy. To further strengthen the European and German AI landscape we need to build strong startups in new sectors and markets.