The role of Analytics in Digital Transformation


Today every industry is talking about Digital Transformation and affected by technologies like the Internet of Things, Blockchain, Microservices and Cloud. Every company like Apple, Nike, and Nestle, better known for their brand products have now become Technology Company. However, for every technology the powerhouse behind the success is Analytics. Look at the latest trend of Internet of Things – Sensor technology can emit data every second or millisecond and with help of Cloud, storing this humongous data is like a piece of cake. Only storing this data is not going to add any value to the business, unless it is analyzed for actionable real-time insights.

How an A.I. 'Cat-and-Mouse Game' Generates Believable Fake Photos


The woman in the photo seems familiar. She looks like Jennifer Aniston, the "Friends" actress, or Selena Gomez, the child star turned pop singer. She appears to be a celebrity, one of the beautiful people photographed outside a movie premiere or an awards show. That's because she's not real. She was created by a machine.

Google Cloud AutoML could make AI more accessible to SMBs, non-experts


Artificial intelligence (AI) technology may be more easily accessible through Google Cloud's new AutoML service, the tech giant said in a blog post Wednesday. Cloud AutoML helps tech professionals build custom machine learning (ML) models, using techniques like transfer learning and learning2learn, the post said. While Cloud AutoML requires limited ML experience, the service could help businesses, especially SMBs, overcome talent shortages and cost barriers and utilize the emerging technology. "Our goal was to lower the barrier of entry and make AI available to the largest possible community of developers, researchers and businesses," Google Cloud AI's Fei-Fei Li and Jia Li said in the post. Even for larger businesses that have both the talent and budget to work with AI, they may not have the time to create machine learning models, the post noted.

Ep 4 - 12/18/17 - Changing AI and Machine Learning Landscape


Patrick and Ryan discuss NVIDIA's new Titan V machine learning card, Tesla's move to build its own AI hardware, the possibilities for Synaptics under-screen fingerprint sensor, and more. Subscribe to stay up to date with The Tech Analysts!

Google introduces Cloud AutoML for employing machine learning without experts


Machine learning has become essential to digital marketing because it allows the generation of predictive models from past data. And these predictions are what enable marketers to target the right offer at the right time; they also help systems recognize things in the real world. Today, Google Cloud is taking another step toward making machine learning accessible to every level of business. It is introducing its Cloud AutoML service, which provides access to custom machine learning models that the company says can be trained "with minimum effort and machine learning expertise." This complements the Google Cloud Machine Learning Engine, released last year, that lets developers with machine learning expertise create models for any kind of data.

Ethical AI happens before you write the first line of code


As internally developed artificial intelligence systems move from lab to deployment, the importance of creating unbiased, ethical systems is greater than ever. The challenge is that there is not a simple solution for companies to build ethical consideration into AI algorithms. But there are key things you can do early on that help. A machine learning algorithm can't tell you whether a decision is ethical or whether it will irreparably damage morale within your organization. It hasn't spent years honing its business intuition, the intuition that tells you that even though a recommendation looks right on paper, it will be poorly received by your client base.

A Law Enforcement A.I. Is No More or Less Biased Than People


Some people champion artificial intelligence as a solution to the kinds of biases that humans fall prey to. Even simple statistical tools can outperform people at tasks in business, medicine, academia, and crime reduction. Others chide AI for systematizing bias, which it can do even when bias is not programmed in. In 2016, ProPublica released a much-cited report arguing that a common algorithm for predicting criminal risk showed racial bias. Now a new research paper reveals that, at least in the case of the algorithm covered by ProPublica, neither side has much to get worked up about.

Questioning AI: what can scientists learn from artificial intelligence? – Science Weekly podcast


In October 2017, researchers at Google DeepMind published a paper on an artificial intelligence (AI) program called AlphaGo Zero. Unlike previous incarnations of AlphaGo, this updated version mastered the game of Go through self-play alone. Talking about the achievement, lead researcher David Silver explained that AlphaGo Zero had invented "its own variants which humans don't even know about or play at the moment." And it's here that a new and exciting use for AI comes to light. Could it be that AI might teach humans about the world around us?

AI, Automation Stand Out At NRF's Trade Show


Several new innovations that change the way retailers manage inventory and consumers purchase products were on display at the National Retail Federation's annual trade show, The New York Times reported. The convention floor included displays of alert systems programmed to identify heavy-spending customers, smart shelves that can track inventory in real time and robots for supply chain applications. During the three-day event, retail industry leaders discussed artificial intelligence, Big Data and automation. Drawing more than 600 exhibitors, the convention featured sessions with leaders from Walmart, Best Buy, Neiman Marcus and other big-name merchants. According to technology on display, certain consumers will soon be able to test-drive or purchase vehicles without any human contact, using their mobile phones at a garage that doubles as a vending machine.

Key U.S. science panel backs lower drunken driving threshold and higher alcohol taxes

The Japan Times

WASHINGTON – A prestigious scientific panel is recommending that states significantly lower their drunken driving thresholds as part of a blueprint to eliminate the "entirely preventable" 10,000 alcohol-impaired driving deaths in the United States each year. The U.S. government-commissioned, 489-page report by a panel of the National Academies of Sciences, Engineering and Medicine released Wednesday throws the weight of the scientific body behind lowering the blood-alcohol concentration threshold from 0.08 to 0.05. All states have 0.08 thresholds. A Utah law passed last year that lowers the state's threshold to 0.05 doesn't go into effect until Dec. 30. The amount of alcohol required to reach 0.05 would depend on several factors, including the person's size and whether the person has recently eaten.