Elon Musk revealed the Model 3 in March, revealing details of the 35,000 base model including a sub-six second 0-60 time and a minimum 215 mile range. The basic picture of the Model 3 inspired a pre-order frenzy unlike anything seen previously in the car world, but now Musk has dropped what he referred to earlier as Part 2 of the Model 3 unveiling after a lengthy pause, as promised, and it's a doozy. Musk announced that all Tesla cars being produced as of today, including the Model 3, will have everything they need onboard to achieve full Level 5 self-driving in the future. The news means that every Tesla vehicle, including the Model S and X as well as Model 3 cars made after today will eventually be able to achieve full autonomous driving, with what Tesla refers to as "a safety level substantially greater than that of a human driver" via nothing more than a software update at some point in the future. The hardware required to make this possible includes a sensor loadout complete with eight surround optical cameras, which can see up to 250 meters out from the vehicle on all sides, and a dozen ultrasonic sensors to assist the optical system.

Does it seem like your virtual personal assistant (VPA) knows everything about your life? Microsoft's Cortana can give you reminders, track packages, send emails or texts, keep track of your flights and even remind you to say happy birthday to your cousin next time she calls. According to Satya Nadella, CEO of Microsoft, developers made deliberate design decisions with customers in mind as the company moves into the world of artificial intelligence (AI). "When it comes to AI, the fundamental vision I have is that AI will be infused into everything," Mr. Nadella said in the Mastermind Interview at Gartner Symposium/ITxpo 2016 in Orlando. "The currency going forward is going to be how to build trust in technology so that people and organizations are comfortable using more technology, and I think that's one of the pressing issues of our time," he said.

Over the past few years, cloud computing has been evolving at a rapid rate. It is becoming the norm in today's software solutions. Forrester believes that that cloud computing will be a 191 billion market by 2020. According to the 2016 State of Cloud Survey conducted by RightScale, 96% of its respondents are using the cloud, with more enterprise workloads shifting towards public and private clouds. Adoption in both hybrid cloud and DevOps have gone up as well.

Artificial intelligence (AI) is already becoming entrenched in many facets of everyday life, and is being tapped for a growing array of core business applications, including predicting market and customer behavior, automating repetitive tasks and providing alerts when things go awry. As technology becomes more sophisticated, the use of AI will continue to grow quickly in the coming years, as explored in a new eMarketer report, "Artificial Intelligence 2016: What's Now, What's New and What's Next" (eMarketer PRO customers only). In its most widely understood definition, AI involves the ability of machines to emulate human thinking, reasoning and decision-making. A May 2015 survey of US business executives by Narrative Science found that 31% of respondents believed AI was "technology that thinks and acts like humans." Other conceptions included "technology that can learn to do things better over time," "technology that can understand language" and "technology that can answer questions for me."

Weber Shandwick's report AI-Ready or Not: Artificial Intelligence here we come!, released this week, shows that top global marketers believe AI will have an even bigger impact on comms than social media. Gorkana asks Weber and other agencies, including Firefly, Hotwire PR and Babel, what they think about the AI'revolution'. According to Weber Shandwick's report, AI is defined as the following: "[AI] is a field of technology designed to create computers, machines and software that are as smart as humans, and which are able to perform the same tasks that normally require human intelligence." It surveyed 150 chief marketing officers across the UK, US and China and more than half of them (55%) expect AI to have'a greater impact on marketing and communications than social media ever had'. Nearly six in ten (58%) of respondents believe that within the next five years companies will need to compete in the AI space to succeed. Furthermore, 68% of the CMOs reported that their company is currently selling, using or planning for business in the AI area.

The question is especially relevant for logistics providers. One study finds that ocean carriers will lose at least 5bn this year, in large part due to a glut of unneeded capacity. Clearly they need to do a better job of matching supply and demand, and the age of Big Data offers a tempting solution to the problem. But Big Data can also lead to Big Chaos, unless providers have a means of sifting through that mass of information and interpreting it properly. That's where artificial intelligence and machine learning come in.

Much of the internet appears to be broken. A distributed denial of service (DDoS) attack has taken down systems run by Dyn, Inc, one of the largest providers of internet services in the world. And as a result it seems to be causing problems for a variety of websites – including Reddit, Spotify and Twitter. Dyn runs domain name servers or DNS. They work as a phone book or map to the internet, making sure that when someone writes an address into their computer or phone, it can be directed to the right place and show the right information.

If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" After reading above papers, you will have a basic understanding of the Deep Learning history, the basic architectures of Deep Learning model(including CNN, RNN, LSTM) and how deep learning can be applied to image and speech recognition issues. The following papers will take you in-depth understanding of the Deep Learning method, Deep Learning in different areas of application and the frontiers. "Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding."

G Suite, the office productivity suite formerly known as Google Apps for Work, has made key technology improvements we can expect to see in cloud-based customer relationship management (CRM) platforms. After all, sales teams no longer use CRM in a silo because sales is increasingly a data-driven game. Companies are integrating their CRM platforms with productivity tools, project management solutions, and other back-end data sources to gain a competitive advantage. Here are three ways G Suite is a CRM trend in the making. With Salesforce trying to democratize artificial intelligence in the CRM world, it's well past time for other cloud vendors to start applying machine intelligence to common productivity and data use cases for all of us to have a more integrated platform future for our customer data.