Round-up: New APIs and SDKs from enterprises hope AI will help understand you

aicircuitbrainimage.pngMobile and cloud services now have extensive capabilities. In addition to analyzing digital content, these services can harness ambient data such as temperature, location, user movements, schedule, user habits and engagement. As a result, developers need to be able to leverage these new capabilities and sources of data to create more advanced apps.

To stand out from the crowd in the app-universe, developers need to create smarter apps. These apps need to have increased precision and relevance, become more personal, enable the use of many more information sources and to link to other devices or apps, and allow more adaptive user experience. All of these more complicated features require the use of one or many AI technologies.

Several companies are now coming up with new software development kits and APIs for developers to take AI to next level. The future of technology is a sea of opportunity for artificial intelligence and application development, especially for cloud computing and mobile devices.

MindMeld API – serve up information before you’ve even asked for it

The MindMeld API is the world’s first developer platform and cloud-based service designed to power a new generation of intelligent applications. The platform makes it easy for developers to build powerful search and content discovery capabilities into the emerging class of mobile, wearable, and intelligent apps. In just three simple steps, developers can begin infusing contextually driven search results into any website, app, or device in minutes.

Designed by Expect Labs, the API indexes the connected site or database and knowledge of the graph. The main feature of the MindMeld API system is that it collects and takes into account all possible clues to catch the context, which helps eliminate ambiguity. To do this, it can analyze text, audio (supports speech recognition), geographical coordinates and many other factors.

To use MindMeld API, Developers need to point the MindMeld API to website or database, and it will automatically crawl and index the content and build a custom knowledge graph from data. Then a few lines of code into the app will start sending real-time contextual signals from users to the MindMeld platform. Developers then use the API to retrieve search results and recommendations based on the search query or question.

MindMeld uses natural language processing to understand your context and then serve up relevant information before you’ve even asked for it. The new API allows developers to add a highly-customizable layer of intelligence to their apps.

The AI company is using the MindMeld API to power a wide range of functionality including context-driven intelligent assistants for mobile applications, improved website and app search using contextual cues in addition to keywords, advanced real-time communication and collaboration applications, and voice- and context-driven dashboards for sales support, help desk, telemedicine, online education, and other knowledge worker applications.

Expect Labs believe that the API has a lot of promising applications. For example, if you implement such a system in the technical support service, it will automatically prompt the contact center operators the right answer. A news sites can use it, for example, as a basis for recommendations video service. It can also be used as a third-party alternative to advanced search functionality like Google Now and Siri.

Linkify SDK – Delivering relevant information on demand to users

Performing a web search on mobile devices is often a daunting task, including switching between multiple applications or tabs in a single window. To make mobile search easy, Linkify announced general availability for cutting-edge SDK that enables mobile app developers to harness advances in semantic augmented reality.

The new SDK supports both the Android and iOS platforms. Linkify offers developers a different approach to mobile search that delivers users relevant results faster. Instead of submitting a traditional word-based query via a search engine, Linkify’s technology is able to recognize, extract and convert “things of interest” to a user and connect them with relevant information from the web.

The machine learning algorithm finds keywords and turns them into links. When the user clicks on this link, a window appears with the results of search engines or sites like Wikipedia. This means that they do not need to open new tabs or go to your browser or other application. In addition to improving the experience of use, Linkify can help developers in two other ways. First, it encourages people to stay longer in the application. Secondly, Linkify enables developers to monetization using Google AdSense, allowing them to integrate contextual advertising in search results.

One of the key functions SDK is a machine learning algorithm, developed by Studio Ousia, which precisely defines the keywords and create the appropriate links. This means that developers do not need to pull out the words one by one, and that creating links to the most relevant keywords, Linkify encourages more people to click on them. The company’s goal is to improve the experience of mobile navigation with touchscreens, as well as products for mobile search, using augmented reality supported by Semantic Web.

Pitney Bowes APIs – Visualize spatial data

Companies need BI tools and expertise to manage and integrate APIs, leverage location intelligence and customer data and then seamlessly extend their services to reach their customers via the cloud and mobile devices. Pitney Bowes has become one of the first companies to add APIs that can be used for a variety of purposes, focused primarily on analyzing spacial data to derive business intelligence.

Pitney Bowes and IBM recently announced a collaborative partnership to develop new localization services in hybrid cloud to help enterprises to establish deeper connections with customers, regions and networks.

The APIs to be used in IBM’s BlueMix is a new development environment to accelerate the adoption of hybrid clouds, combining third-party solutions and open technologies. For its part, the business intelligence APIs of Pitney Bowes provides full functionality to provide businesses with the ability to visualize spatial data. Using advanced extremely accurate location data, insurers can improve their decisions about insurance policies, telecommunications providers can better analyze the coverage of its network and retail companies can provide more relevant to consumers promotions.

AlchemyAPI – API based on deep-learning techniques

AlchemyAPI provides advanced cloud-based and on-premise text analysis infrastructure that eliminates the expense and difficulty of integrating natural language processing systems into your application, service, or data processing pipeline.

The company’s recently released first-of-its-kind deep learning based Taxonomy and Sentiment Analysis APIs that allow ad networks and publishers to transform all of their content into valuable ad inventory. Unlike competing taxonomy products, AlchemyAPI’s classifier uses deep-learning-based technology that takes advantage of three converging forces to improve the accuracy of how computers understand language – algorithmic breakthroughs, massive compute capability and large amounts of publicly available data.

The API is more accurate when processing short, challenging texts such as poorly written tweets, mixed sentiment passages, and slang. For instance, an application focused on identifying content discussing personal lending practices can narrow its classification into sub topics that target decisions with finer resolution.

PlaceMe APIs – Track your activities

PlaceMe app, which sits in the background of your mobile phone, uses every sensor in your handset to track your activities, location and environment and keeps a record of everywhere you’ve been. What that means is that, apps using PlaceMe APIs can precisely determine someone location because of the way data is combined.

Developers who are using the SDK are in the categories of dating, fitness and health apps that want to track your exercise and make recommendations, and shopping apps that make suggestions based on your location and your likes and favorites.