The internet is always speculating and wondering about what's to come, in terms of access modes, once mobile and screens have ceased to be the latest shiny new thing. The theory is that artificial intelligence (AI) is going to be the next evolution; and precisely because of that prediction about AI (plus its other uses), we witnessed an unprecedented technology gold rush in 2017. The craze about AI had people investing millions of dollars into new products and services, and hand-wringing skeptics forming think tanks to postulate about the end of the world. But, for all of the speculation, what did AI actually do in 2017? And, what's it poised to do in the coming year?

Getting up from the toilet after a satisfying bowel movement, you walk right over to the sink and start washing your hands. "Alexa, flush my toilet," you say while reaching for your toothbrush. Your mirror starts displaying your schedule for the day, the weather update and latest news. Suddenly, there's a ping -- your toilet has detected an anomaly in your stool and recommends you increase your fiber intake. A dispenser built into your medicine cabinet whirs and spits out a fiber supplement.

Ben Lorica, O'Reilly's chief data scientist, has posted slides and notes from his talk at last December's Strata Data Conference in Singapore, "We need to build machine learning tools to augment machine learning engineers." Lorica describes a new job emerging in IT departments: "machine learning engineers," whose job is to adapt machine learning models for production environments. These new engineers run the risk of embedding algorithmic bias into their systems, which unfairly discriminate, create liability, and reduces the quality of the recommendations the systems produce. He presents a set of technical and procedural steps to take to minimize these risks, with links to the relevant papers and code. It's really required reading for anyone implementing a machine learning system in a production environment.

Semiconductor giant MediaTek announced several new products and partnerships at CES 2018. These include a partnership with Alibaba AI Labs, new chips for UHD Smart TV platforms, portfolio of Wi-Fi chipsets for IoT devices, solutions for smart home devices, and AI solutions for cross platform devices. Partnership with Alibaba AI Labs At CES 2018, MediaTek announced a strategic partnership with Alibaba's AI division. Under this partnership, the companies will work on smart home standards, customised IoT chips, and AI smart hardware. The partnership also revealed a Smartmesh connectivity solution in China that will help increase adoption in smart home settings. Smartmesh will enable smart home devices to pair with Tmall Genie, Alibaba's voice-controlled virtual assistant.

Artificial intelligence (AI) and robots have slowly but steadily made their way into a variety of industries spanning fast food to the financial sectors. This expansion is projected to continue and is forecasted to replace a considerable amount of jobs. A Forrester report notes that AI can replace as many as six percent of jobs by 2021. A PwC reports notes that many jobs across the globe will be affected by the 2030s, including 38 percent of U.S. jobs; 35 percent of jobs in Germany; 30 percent of U.K. jobs, and 21 percent of occupations in Japan. There is no doubt that AI and robots can replace frontline workers who complete routine tasks.

Whether you fear it or embrace it, the A.I. revolution is coming--and it promises to have an enormous impact on the world economy. PwC estimates that artificial intelligence could add $15.7 trillion to global GDP by 2030. To identify which private companies are set to make the most of it, research firm CB Insights recently released its 2018 "A.I. 100," a list of the most promising A.I. startups globally (grouped by sector in the graphic above). They were chosen, from a pool of over 1,000 candidates, by CB Insights' Mosaic algorithm, based on factors like investor quality and momentum. China's Bytedance leads in funding with $3.1 billion, but 76 of the 100 startups are U.S.-based.

About this course: This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models. OBJECTIVES This course teaches participants the following skills: Identify use cases for machine learning Build an ML model using TensorFlow Build scalable, deployable ML models using Cloud ML Know the importance of preprocessing and combining features Incorporate advanced ML concepts into their models Productionize trained ML models PREREQUISITES To get the most of out of this course, participants should have: Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience Basic proficiency with common query language such as SQL Experience with data modeling, extract, transform, load activities Developing applications using a common programming language such Python Familiarity with Machine Learning and/or statistics Google Account Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google services are currently unavailable in China).

Women in Saudi Arabia need a male guardian to be granted citizenship, but the country is also the first in the world to grant citizenship to a female robot, named Sophia. Perhaps Elon Musk's fears of robots overtaking humans are not unfounded. But as artificial intelligence is keenly debated at the highest levels of say, Satya Nadella of Microsoft and Facebook's Mark Zuckerberg, what does it mean for India? The country, which embraced smartphones like no other, has shown remarkable openness to artificial intelligence as well. Look at Sriram Rajamani, managing director of Microsoft Research Labs India, who never really believed machines could one day possess intelligence this superior.

International Business Machines Corp. was once again awarded the largest number of U.S. patents in 2017, as the company pushes into blockchain and artificial intelligence technologies. IBM, No. 11 in the B2B E-Commerce 300, received 9,043 patents in 2017, breaking the record it set in 2016, the company said Tuesday. A lot of the research that IBM conducts may not translate to immediate business gains, and it could take years before patents turn into a product that pays off. The company also invests in exploratory research unrelated to business lines and goals. Despite winning the most patents for the 25th straight year, IBM is struggling to turn itself around.

NEW DELHI: Chinese handset maker Huawei on Friday unveiled EMUI 8.0 -- its custom Operating System (OS) based on Android Oreo platform that promises to boost productivity with Artificial Intelligence (AI) capabilities. The EMUI 8.0, already available on Honor View 10, will be rolled out on devices such as Honor 8 Pro, Honor 9i, Honor 7X and Honor 8 Lite soon. "The update significantly cuts down on the number of steps needed to achieve the desired function through its smart applications like navigation dock and smart screen. It enables the user to reach 90 per cent of the core functions in a single-click," Huawei said in a statement. The custom OS engages in low-memory management by allocating resources in a way to provide more space to ensure holistic experience coupled with AI capabilities.