This post is authored by Sachin Chouksey, Principal Software Engineering Manager, and Darwin Schweitzer, Senior Program Manager, at Microsoft. Building analytics solutions can consume a lot of time. Customers who wish to build intelligent solutions on Microsoft's advanced analytics platform today, for instance, need to navigate through a multitude of options, thanks to the broad array of services available as part of the Cortana Intelligence Suite. This buffet of options could present a learning curve for newer customers who may not be sure where to start, or what the optimal architecture might be, or how to glue different services together. To address the above challenge, we offer Cortana Intelligence Solutions, a set of pre-built solutions that are based on commonly encountered design patterns and which customers can quickly deploy and test.

Researchers at Microsoft have published details of new speech recognition technology that they say transcribes conversational speech as well as a human does. "We've reached human parity," says Microsoft's chief speech scientist Xuedong Huang in a statement. "This is an historic achievement." The system's word error rate is reported to be 5.9 percent, which Microsoft says is "about equal" to professional transcriptionists asked to work on speech taken from the same Switchboard corpus of conversations. It uses neural language models that group similar words together, allowing for efficient generalization. Microsoft plans to use the technology in Cortana, its personal voice assistant for Windows and the Xbox One, as well as speech-to-text transcription software.

Investigators hunting for debris from missing Malaysia Airlines Flight 370 are about to be joined by a mechanical teammate. In the Australian Transport Safety Bureau's weekly operational update on the MH370 search released Wednesday, officials revealed they were installing a robot on one of the two vessels scanning the ocean floor for wreckage. The Associated Press called it a "drone." The Dong Hai Jiu 101 was in Fremantle this week being set up with the Remora III, a remotely operated vehicle with video cameras and high-tech sensors. Its mission is to "reacquire and investigate, through video imaging, a range of sonar contacts which have been identified during previous deep tow operations," according to the bureau.

RTB House, a technology company specializing in retargeting scenarios, has come up with a brand new model that relies on deep learning (currently the most promising subfield of AI-oriented research) to craft digital features that recognize the attitude, intention and intent of internet users. It allows for accurate estimation of the conversion probability, which in turn makes personalized retargeting more efficient than before. The model can even be applied to users who haven't clicked ads, a long-sought after feature of digital marketers. Users take hundreds of small steps when visiting advertiser's website. The model developed by RTB House uses deep learning to identify every one of these footprints, in order to find patterns in decision-making.

If you could implant a device in your brain to enhance your intelligence, would you do it? A new company has just invested 100 million into developing such a device, and is being advised by some of the biggest names in science. The company, Kernel, was launched earlier this year by entrepreneur Bryan Johnson. He says he has spent many years wondering how best to contribute to humanity. I think it's the most precious and powerful resource in existence," says Johnson. His goal is for human intelligence to expand and develop in the same way that artificial intelligence has in recent years. The first experiments planned will be on memory. Johnson is working with Theodore Berger, at the University of Southern California in Los Angeles, who is looking at the hippocampus – a brain region key for memory. Berger is currently studying people with epilepsy, who already have electrical implants in their brains to treat their seizures. Rather than using these implants to stimulate the brain, Berger's team have been using them to record brain activity instead, to tell us more about how our memory works. Once we learn how a healthy brain functions, we should eventually be able to mimic it, says Johnson. By electrically stimulating the same pattern of activity, the team think they should be able to restore memory in people with memory disorders. Berger has already had some success with animals, and has started experiments in people. Kernel will be starting new human studies in the coming months, says Johnson. "The idea is that if you have loss of memory function, then you could build a prosthetic for the hippocampus that would help restore the circuitry, and restore memory," says Johnson. People with memory disorders, for example due to a traumatic experience or ageing, are intended to be the first people to test such a prosthesis. "The first super-humans are those who have deficits to start with," says Johnson. But Johnson then plans to develop this prosthesis to enhance memory, and potentially other functions, in healthy people. He envisions a future in which it is normal for people to walk around with chips in their brains, providing them with a cognitive boost as they go about their everyday business. The 100 million – from Johnson's own pocket – will be spent on developing such a device. Ideally, it will be as tiny and easy to implant as possible, while being able to record or stimulate multiple neurons. The team are also working on ways to develop personalised algorithms – a set of rules that dictate normal brain function for an individual. Johnson hopes that memory enhancement will just be the start. "If we can mimic the natural function of the brain, and we can truly work with neural code, then I posit the question – what can't we do?" says Johnson. "Could we learn a thousand times faster?

The findings suggest that about a quarter of all police departments in the US have access to face recognition technology. That police are using face recognition technology is not a problem in itself. In a world with a camera in every pocket, they would be daft not to. But face recognition can be used far more broadly than fingerprint recognition, which means it carries a higher risk of tagging innocent people. Fingerprints are difficult to work with.

Investigators eager to uncover the genetic basis of autism could now have hundreds of promising new leads thanks to a study by Princeton University and Simons Foundation researchers. In the first effort of its kind, the research team developed a machine-learning program that scoured the whole human genome to predict which genes may contribute to autism spectrum disorder (ASD). The results of the program's analyses -- a rogue's gallery of 2,500 candidate genes -- vastly expand on the 65 autism-risk genes currently known. Researchers have recently estimated that 400 to 1,000 genes underpin the complex neurodevelopmental disorder. This newest research provides a manageable, "highly enriched" pool from which to pin down the full suite of ASD-related genes, the researchers said.

Editor's note: At the ISC conference next week in Frankfurt, Andrew Ng, chief scientist at Baidu, will present the keynote address and Bryan Catanzaro, research scientist at Baidu's Silicon Valley AI Lab, will participate in the Analyst Crossfire Panel. Speech recognition has expanded accessibility, natural language processing helps answer user questions, and image recognition offers more intuitive search results. It's not surprising that AI is transforming internet companies. We believe the AI revolution will transform many other industries as well, from transportation to healthcare. AI research has been going on for decades, so you may ask "what has changed to make AI so useful today?"

From alarm's snooze in the morning to watching television at night, and all the activities in between – human life is increasingly influenced by machines. Today, machine learning has transformed devices with static pre-programmed software into smart machines driven by Artificial Intelligence (AI), giving them the ability to learn by themselves based on gathered data. Machine learning focuses on developing computer programs that can teach themselves to grow and update the program embedded in a device by analyzing incoming data. Defined as the science of getting computers to act without being explicitly programmed, Machine learning is aiding human life by paving the path towards smart technologies such as self-driving cars, practical speech recognition, and effective web search. It has also improved the concept of understanding human genome in the field of biotechnology.

Big data is a big deal, but problems within the data can skew results and lead to problematic choices. To help keep data -- and the decisions based on it -- clean, researchers at Columbia University and the University of California at Berkeley have developed new software. ActiveClean analyzes prediction models to determine which mistakes (e.g., typos, outliers and missing values) to edit first, updating the models in the process, according to Columbia. "Big data sets are still mostly combined and edited manually, aided by data-cleaning software like Google Refine and Trifacta or custom scripts developed for specific data-cleaning tasks," university officials said. "The process consumes up to 80 percent of analysts' time as they hunt for dirty data, clean it, retrain their model and repeat the process. Cleaning is largely done by guesswork."