At Geneia, a health care technology and consulting company, they use big data along with machine learning to help health care organizations deliver better patient care at a lower cost. "Geneia brings data in from a lot of different sources," said Lavoie. We've built Theon, a unified platform to integrate the data and allow us to apply machine learning techniques." Using machine learning, Geneia can match and determine missing values, as well as perform principal component analysis and look at patterns in the data – clusters that help them see trends and causality. "Machine learning allows us to see patterns in the data that we couldn't see before.

Benchmarks are an important tool for measuring performance, but in a rapidly evolving field it can be difficult to keep up with the state of the art. Recently Intel published some incorrect "facts" about their long promised Xeon Phi processors. Few fields are moving faster right now than deep learning. Today's neural networks are 6x deeper and more powerful than just a few years ago. There are new techniques in multi-GPU scaling that offer even faster training performance.

Hexaware Technologies Limited, a leading global provider of IT, Business Process and Consulting Services, and WorkFusion, the leading Smart Process Automation (SPA) provider, today announced a partnership to help enterprise operations leverage smart automation software to realize higher productivity, drive agility in generating new products and reduce operational cost. The combination of Hexaware's industry and process expertise, and WorkFusion's best-in-class automation software will provide customers the ability to rapidly deploy and scale transformational technology to achieve business goals. Hexaware has constantly strived to provide business value to its clients through significant cost savings and creating opportunities for revenue generation. This partnership aligns with Hexaware's'Shrink IT Grow Digital' strategy that has radically revolutionized digital transformation journeys of their customers. This strategy helps global firms dramatically reduce commodity operations and IT costs, while enabling realization of value from digital initiatives through solutions across industries such as Telecom, Banking & Financial Services, Healthcare & Insurance, Travel & Logistics, and Manufacturing & Consumer.

Pursuing its stated goal to make software smarter, Salesforce has made yet another acquisition, this time agreeing to buy BeyondCore, a San Mateo, Calif.-based data-analytics company. BeyondCore disclosed the sale in a blog post and Salesforce founder the CEO Marc Benioff confirmed it in a tweet, saying that BeyondCore will "enhance the AI capabilities of Analytics Cloud." Terms weren't disclosed, but BeyondCore has raised 9 million since its founding in 2004, according to CrunchBase. BeyondCore was already integrated into Salesforce as part of its upcoming version 7 release, BeyondCore said its post. The acquisition is Saleforce's seventh this year, marking a major increase in velocity -- it bought only 13 other companies between 2012 and 2015, per CrunchBase.

Think about software that can mine LinkedIn connections, send intros, ask for meetings, follow up, follow up, follow up, schedule meetings, and prepare notes for the sales rep handling the meeting before handing off. AI as part of your prospecting and sales process can do everything your entry level salesperson can do, and then some. What's more, AI can use data from thousands of data points and then decide which leads are the hottest, and most likely to close, putting those leads in front of the sales team first. AI can make everything about the sales process more precise, more data-driven, and more efficient.

Ford outlined a few of the ways it's aiming to ship driverless cars by 2021, and part of the plan involves acquisitions. CEO Mark Fields revealed at a press event in Palo Alto today that the automaker acquired SAIPS, an Israeli company focusing on machine learning and computer vision. It's also partnering exclusively with Nirenberg Neuroscience, to bring more "humanlike intelligence" to machine learning components of driverless car systems. SAIPS' technology brings image and video processing algorithms, as well as deep learning tech focused on processing and classifying input signals, all key ingredients in the special sauce that makes up autonomous vehicle tech. This company's expertise should help with on-board interpretation of data captured by sensors on Ford's self-driving cars, and turning that data into usable info for the car's virtual driver system.

Ford today announces its intent to have a high-volume, fully autonomous SAE level 4-capable vehicle in commercial operation in 2021 in a ride-hailing or ride-sharing service. This Smart News Release features multimedia. Ford has been researching autonomous vehicles for more than a decade, and intends to have a high-volume, fully autonomous SAE level-4-capable vehicle in commercial operation for ride sharing services in 2021. Ford currently tests fully autonomous vehicles in Michigan, Arizona and California, and will triple its autonomous test fleet this year to have the largest test fleet of any automaker. To get there, the company is investing in or collaborating with four startups to enhance its autonomous vehicle development, doubling its Silicon Valley team and more than doubling its Palo Alto campus.

Imagine the endless possibilities of learning from 2.5 quintillion bytes of data generated every day. Artificial intelligence (AI), which began its journey 60 years ago is well on its course to make this implausible scenario a reality. Artificial Intelligence, is slowly taking over our lives. From personal assistants like Siri in Apple products to stock trading to medical diagnosis, AI is able to learn from seemingly unstructured data, take decisions and perform actions in a way previously unimagined. Businesses too are undergoing digitization rapidly.

This essay originally appeared on MIT Sloan Management Review as part of their Frontiers Essay Series. Each essay is a response to this question: "Within the next five years, how will technology change the practice of management in a way we have not yet witnessed?" Artificial Intelligence is about to transform management from an art into a combination of art and science. Not because we'll be taking commands from science fiction's robot overlords, but because specialized AI will allow us to apply data science to our human interactions at work in a way that earlier theorists like Peter Drucker could only imagine. We've already seen the power of specialized AI in the form of IBM's Watson, which trounced the best human players at Jeopardy!, and Google DeepMind's AlphaGo, which recently defeated one of the world's top Go players, Lee Sedol, four games to one.