Salesforce is announcing today the launch of its Einstein artificial intelligence (A.I.) platform that's implemented into several of the company's existing cloud services: Sales Cloud, Service Cloud, Marketing Cloud, Analytics Cloud, App Cloud, Commerce Cloud, Community Cloud, and IoT Cloud. The company is also announcing the formation of Salesforce Research, a unit that will do research in deep learning, natural language processing, and computer vision that can be used to improve Salesforce products. The unit is led by Salesforce chief scientist Richard Socher, formerly cofounder and chief executive of A.I. startup MetaMind, which Salesforce acquired earlier this year. In a press briefing in San Francisco this week, Socher declined to say how many people were part of the team, although he did say that some of Salesforce's 175 data scientists have joined the newly organized division. The product enhancements will have an impact on Salesforce's direct competitors.

In fairly short order, robots have begun taking over in the corporate world. This is nothing like the feared "singularity," that prophesied (if dubious) moment when machines become smarter than humans and then, to prove it, commence wiping us out. But robots are indeed infiltrating finance departments, some other functions, and operational areas in a number of industries. For the most part, robots are being deployed to automate repeatable, standardized, or logical tasks historically handled by people. In finance and accounting, think procure-to-pay, order-to-cash, and record-to-report processes.

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 OpenWorld event kicked off. As Salesforce CEO Marc Benioff previously hinted, Einstein is an AI wrapper around Salesforce's existing products that collects and analyzes all the data stored in Salesforce to push out recommendations, so the user can close deals faster or build a larger group of leads. For example, sales representatives using Sales Cloud will get a list of leads on the side based on "Lead Score," a number representing who's more likely to buy your product. It also gives suggestions on when to make a follow-up call or alerts when a contact has been unresponsive for a long time. "The great thing about machine learning is you can actually measure it," Salesforce's general manager of Einstein, John Ball, said at a press briefing held last week.

As the price-performance ratio of artificial intelligence improves, business software companies are building deep learning and other new tools into mainstream products, extending the reach of automation into once-human realms and giving people a powerful decision-support system. Salesforce.com Inc. said it would add an AI-based component called Einstein to its sales software. "The new offering is a set of online AI services designed to automate tasks, predict behavior and spotlight relevant information," the WSJ's Rachael King reports. Other companies from Microsoft Corp. to International Business Machines Corp. are investing heavily into the development of AI-powered platforms for business users. AI is taking off after years of promise, and the market is expected to grow to 16.5 billion in 2019 from 1.6 billion in 2015 with a compound-annual growth rate of 65.2%, the WSJ says.

We have already seen how artificial intelligence makes a difference in our lives. Whether it is through the use of an autonomous car, or a smart appliance, or a robotic vacuum, AI is here to stay and is very helpful. But, the question that many people are asking is, "Are we ready as a society to integrate robots into our world and effectively treat them like one of us?" – Soon artificial intelligence will be everywhere including in education, health care, security, and entertainment. A project hosted by Stanford University entitled, "Artificial Intelligence and Life in 2030" is the first product of many to come as part of the One Hundred Year Study on Artificial Intelligence (AI100). Every five years the AI100 is responsible for issuing a report that evaluates the status of AI technologies and how they could potentially impact the world.

Salesforce.com founder Marc Benioff has done his part to revolutionize the software industry, and he's far from done. Back when Benioff was a top executive at Oracle in the 1990s, salespeople stored client and prospect data on proprietary machines that required expertise to use. Marketing teams had separate tools as did customer support representatives. Data was siloed, limiting the capabilities of analysis and business intelligence software. Fast forward two decades and Benioff hast turned that model on its head.

They hope that their method will be used for post-approval surveillance of drugs that have already received FDA approval but still carry a risk of toxicity. For instance, one diabetes drug that was on the market was flagged by PrOCTOR and when it was investigated further, it did indeed reveal that it had been taken from the market in Europe.

A man in a wheelchair was struck and killed by a hit-and-run driver in a Pomona neighborhood on Sunday night, police said. Officers found the victim, whose identity has not been released, suffering from fatal injuries on a sidewalk in the 900 block of West Holt Avenue at 11:12 p.m., according to the Pomona Police Department. Paramedics pronounced the man dead. The driver fled before the officers arrived in the area, police said. The department's Major Accident Investigation Team is investigating the incident.

I really enjoyed the style of the author, truly demystifies complex topics. I have many books on Machine Learning and Neural Networks but I always get lost and hit a wall. I purchased "Python Machine Learning" which starts describing similar topics at the beginning but then the book just moved too fast for me. I didn't know the why and how. But Tariq's book was amazing, the author really takes his time to explain things mixing text with illustrations to make a point.

This holistic approach allows retailers to develop a more nuanced understanding of customers based on multiple perspectives. A machine learning platform would recognize that the woman who purchased luxury perfume only did so because of a steep discount, and could factor that into their data analysis. Retailers that have a wide variety of information about customers can serve them much more effectively, because they can target individual shoppers with highly personalized discounts and offers, through the right channels at the right time.