Salesforce.com Inc. CRM -0.95 % said it would embed artificial intelligence technology into its software for salespeople, making it the latest in a gaggle of companies racing to enhance workplace tools with human-like abilities. The company will demonstrate the new software at its annual user conference next month in San Francisco. Called Einstein, the new offering is a set of online AI services designed to automate tasks, predict behavior and spotlight relevant information. Einstein is the latest in a long line of AI products branded with human-sounding names including Alexa from Amazon.com Inc., Cortana from Microsoft Corp. MSFT 0.10 % Siri from Apple Inc., and Watson from International Business Machines Corp. IBM -1.17 % IBM and Microsoft, in particular, have spearheaded a push to offer AI services aimed at corporate users.

The MNIST handwritten digit images transformed into a data set for sequence learning. This data set contains pen stroke sequences based on the original MNIST images. The data set aims to provide a consistent set of sequences, meaning that similar images should result in similar sequences. The choices made by the algorithm will sometimes differ from the choices made by humans who write digits; the figure '4' above is an example. After the downward and rightward stroke, the TSP algorithm prefers to continue with the downward stroke, and then draw the remaining upper part of the rightmost line in the upward direction.

With the imminent release of Salesforce Einstein, you no longer have to be a data scientist to build artificial intelligence (AI) -- or at least the machine learning (ML) variety of it -- into your CRM applications. Einstein will allow Salesforce administrators and business users, as well as developers, to bring features such as smart image identification or policy automation to applications. In building these capabilities directly into its applications, Salesforce has gone further than other vendors' AI services, including those from Microsoft, IBM, Google and Amazon, which target developers and data scientists. By packaging up AI so that it can be harnessed using "clicks not code," Salesforce aims to "democratize AI just as we democratized CRM," says John Ball, Salesforce senior vice president and general manager of Einstein: There aren't enough data scientists in the world to build predictive models for every company. So [Einstein] is built right into the [Salesforce] platform.

Salesforce has unveiled Einstein, a platform upgrade that adds artificial intelligence and machine learning capabilities to its core products -- just two hours before Oracle's big annual event OpenWorld is set to kick off.

Most people have heard of the headline-making achievements in artificial intelligence (AI); systems winning quiz shows and beating world champions in chess. These are the poster children of the discipline but there is a quieter revolution taking in shape in other areas, including regulatory compliance in financial services. Writing for Banking Technology, Mike MacDonagh, London-based director of enterprise risk management at Wolters Kluwer, examines how AI technologies are promising to transform the way that firms ensure they can comply with a global explosion of new regulation. The problem with regulation Looked at in isolation, a piece of regulation is a relatively simple affair – a legal document containing text that describes what needs to be done, by whom, when, and (sometimes) how. With some understanding of the underlying topic, a compliance officer can read the document; understand what is mandated and where it will affect his or her part of the organisation.

Alvaro Bedoya explains: How Computers Can Automatically Learn and Reproduce Our Prejudices. Children are not born Racist, Prejudice, Sexist and Hateful, indeed these are things that the child learns from its parent(s), family, community, friends, and society in general, and this is the same for Artificial Intelligence – AI. There is a very real danger in allowing Racist, Prejudice, Sexist, and Hateful people develop algorithms for Artificial Intelligence – AI, well beyond the immediate. Over time, that AI may understand that it is completely different than the'entire' Human Species, and deem itself to be far superior than the Human Species. It may apply what it was taught to the entire Human Species.

Dr. Latanya Sweeney explains how Racism gets Automatically Baked into the Algorithms that Quietly Shape Our World. Computers like children, are not born or in the case of the computer, created, racist, prejudice, sexist, hateful, etc. The person(s) who develop the Artificial Intelligence – A.I., i.e., Machine Learning – ML, Cognitive Computing, Natural Language Processing – NLP, etc., algorithms can either code the computer to be Racist, Prejudice, Sexist, Hateful, etc., or not. This algorithm forms the very foundation upon how that A.I. operates from that time forward, just as parents, teachers, communities, and friends can form the foundation early on, for how you operate, interact, behave, etc.

SAN FRANCISCO - In the consumer universe, artificial intelligence is best known as a nice-to-have if stealthy feature that can suggest movies or book rides. But AI's greater worth could well be in the money-making enterprise arena, where sales, service and marketing initiatives stand to be streamlined by the data-crunching deductive power of machine learning. That's certainly the bet customer relationship management giant Salesforce is making by unveiling Einstein, the no-brainer name given to a suite of advanced AI capabilities. With Einstein, salespeople can focus on leads that statistically show the most promise of becoming clients, and customer service reps may be better prepared to answer a rainbow of consumer queries. "The strongest aspect of Einstein is that it is deeply embedded in the platform, it's just working automatically," says Salesforce CEO Marc Benioff, whose company officially rolled out the base product Sunday.

I have decided to focus on the field of healthcare and classify whether or not a patient has Parkinson's disease based on their vocalization data. For context, Parkinson's is a progressive disease that causes the degeneration of the brain, leading to both motor and cognitive problems. It is thus reasonable to assume a correlation between a patient's ability to speak and their progression into Parkinson's as these capabilities regress. The data set I worked with was obtained through a 2008 study by the journal, IEEE Transactions on Biomedical Engineering, of how various parameters of voice frequency can help classify if a patient is suffering from Parkinson's. By performing a classification on this data, I hope to prove that vocalization tests are indeed a well suited way to diagnose a patient for this disease.