Over the past 4 years, Ford has made a concerted effort to move from also-ran status to vying for the lead in the race to produce automated vehicles. The latest move by the company is a 5-year, $1 billion investment in Pittsburgh-based Argo AI. The artificial intelligence startup will operate semi-independently while developing the virtual driver platform for the automated vehicles that Ford has promised to start producing by 2021. However, the deal seems less about acquiring technology today than acquiring new talent in the coming months and years. Argo AI was founded in late 2016 by Google self-driving car program veteran Brian Salesky and Peter Rander, who led Uber's automated car program until September 2016.

It's been a long time worry that when AI gains a certain level of autonomy it will see no use for humans or even perceive them as a threat. A new study by Google's DeepMind lab may or may not ease those fears. There are two unmistakable sides to the debate concerning the future of artificial intelligence. The researchers at DeepMind have been working with two games to test whether neural networks are more likely to understand motivations to compete or cooperate. They hope that this research could lead to AI being better at working with other AI in situations that contain imperfect information.

Salesforce has announced the unveiling of Service Cloud Einstein, a new customer service platform which includes a beefed-up AI engine and aims to add intelligence'to every service interaction'. The platform, which is a mix of the firm's current Einstein AI tool and Service Cloud, will be fully connected to CRM data across sales, commerce, and marketing departments, and offers a variety of features. Einstein Supervisor is a mix of several products, from Salesforce's Omnichannel Supervisor and the Service Wave analytics app, which gives managers real-time data and can predict customer satisfaction, to Einstein Case Management, which can escalate cases in real time and include relevant information, such as knowledge articles and videos, immediately on tap. Salesforce uses as an example of the former an appliance manufacturer, who finds an increase in calls about a specific product model. Using the data, and finding out all the issues come from products that were put together in one three month period at the same factory, other customers can be warned, potentially staving off a larger problem.

Recently, most industries are facing a significant change due to the improvement in technology. The automotive sector is one of the industries that are defined by the normal technological development. Various automotive companies have been working to release self-driving vehicles. The self-driving vehicles use the machine learning technology to substitute the human driver. The self-driving vehicle project is proving to bear fruit.

For the past couple of years, some very intelligent people, in fact some of the most respected intellects on the planet, have been outspoken in their alarm about the potential of Artificial Intelligence. It has been said by everyone from Elon Musk to Professor Stephen Hawking that AI is the one thing that has the potential to destroy human life. No not over zealous nationalists, not global warming and not religious fundamentalists will do us in… Technology will though. And if its not the death of us, it will leave us unemployed. I wanted to look into this further; as on a personal level I think AI is exciting.

Late last year, famed physicist Stephen Hawking issued a warning that the continued advancement of artificial intelligence will either be "the best, or the worst thing, ever to happen to humanity". We've all seen the Terminator movies, and the apocalyptic nightmare that the self-aware AI system, Skynet, wrought upon humanity, and now results from recent behaviour tests of Google's new DeepMind AI system are making it clear just how careful we need to be when building the robots of the future. In tests late last year, Google's DeepMind AI system demonstrated an ability to learn independently from its own memory, and beat the world's best Go players at their own game. It's since been figuring out how to seamlessly mimic a human voice. Now, researchers have been testing its willingness to cooperate with others, and have revealed that when DeepMind feels like it's about to lose, it opts for "highly aggressive" strategies to ensure that it comes out on top. The Google team ran 40 million turns of a simple'fruit gathering' computer game that asks two DeepMind'agents' to compete against each other to gather as many virtual apples as they could.

Musk explained what he meant by saying that computers can communicate at "a trillion bits per second", while humans, whose main communication method is typing with their fingers via a mobile device, can do about 10 bits per second. In an age when AI threatens to become widespread, humans would be useless, so there's a need to merge with machines, according to Musk. "Some high bandwidth interface to the brain will be something that helps achieve a symbiosis between human and machine intelligence and maybe solves the control problem and the usefulness problem," Musk explained. The technologists proposal would see a new layer of a brain able to access information quickly and tap into artificial intelligence. It's not the first time Musk has spoken about the need for humans to evolve, but it's a constant theme of his talks on how society can deal with the disruptive threat of AI.

NEW YORK - Wells Fargo & Co has created a team to develop artificial intelligence-based technology and appointed a lead for its newly combined payments businesses, as part of an ongoing push to strengthen its digital offerings. Wells Fargo's AI team will work on creating technology that can help the bank provide more personalized customer service through its bankers and online, the bank said on Friday. It will be led by Steve Ellis, head of Wells Fargo's innovation group. Well Fargo's AI focus comes as banks and other large financial institutions increase their investment in the emerging technology which seeks to train computers to perform tasks that would normally require human intelligence. Projects range from systems that can spot payments fraud or misconduct by employees, to technology that can make more personal recommendations on financial products to clients.

It could be a game show bonus question: Who is more likely to call his bank contact center, a plugged-in millennial in Brooklyn or a retiree fresh off the tennis court at The Villages in Florida? Surprisingly, that young, bearded, plaid-shirted hipster is placing calls to his bank at 1.7 times the rate of the 70-something slice-meister. Millennials may be fluent in Siri, but they are still on the learning curve for paying bills, depositing checks, transferring money and generally resolving issues with their accounts. They also visit the bank branch fairly frequently―and not for free coffee. Can this really be happening today?

If you're not sure whether algorithmic bias could derail your plan, you should be. Megan Garcia (@meganegarcia) is a senior fellow and director of New America California, where she studies cybersecurity, AI, and diversity in technology. Algorithmic bias--when seemingly innocuous programming takes on the prejudices either of its creators or the data it is fed--causes everything from warped Google searches to barring qualified women from medical school. It doesn't take active prejudice to produce skewed results (more on that later) in web searches, data-driven home loan decisions, or photo-recognition software. It just takes distorted data that no one notices and corrects for.