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Artificial Intelligence Explained

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The scope of Artificial Intelligence is much broader, including technologies like Virtual Agents, Natural Language Processing, Machine Learning Platforms and many other. The main focus in GE is on making machines smarter, leveraging machine learning to create "digital twins" – a digital replica, or data-based representation of an industrial machine. Unfortunately, SalesForce's Connected Small Business Report notes that only 21% of small businesses are currently using business intelligence and analytics. World's top technology leaders Stephen Hawking and Elon Musk are on the sceptical side of this debate, while Microsoft, Apple, Google and many others are already eagerly taking advantage of the AI technology.


Where Major Corporations Like Salesforce And NVIDIA Are Investing In Artificial Intelligence

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Citi Ventures, Salesforce, Tencent Holdings, and NVIDIA GPU Ventures were frequently spotted in the deals we investigated, while VC firm Kleiner Perkins Caufield & Byers and private equity firm Warburg Pincus were common co-investors. The unicorn startup (valued at $1.2B) welcomed Roche Venture Fund -- the CVC arm of the healthcare company Roche -- into its ownership in its $175M Series C, which is the company's largest raise to date. At the heart of the platform is "Neuralytics" -- the company's big data, predictive analytics, and artificial intelligence engine -- which leverages sales interaction data from across the company's global network to make predictive and prescriptive recommendations (with the aim of shortening sales cycles and improving internal sales processes). In the startup's $100M Series C in Q3'15, IT firm Rackspace Hosting participated alongside CVC capitalG (formerly Google Capital) and follow-on investors Accel Partners and Warburg Pincus.


Salesforce creates AI tool for talking to databases

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While that may seem like an easy question, it can actually be deceptively difficult to train a machine learning system to perform such a task accurately. In addition to the system that Salesforce laid out, the company also released a new WikiSQL data set to the public that provides data scientists with a method of training systems to connect natural language queries with the contents of databases. Salesforce then worked with people through Amazon Mechanical Turk to label the natural language queries for training a machine learning system. That data set should help other machine learning teams create systems similar to Seq2SQL.


Meet These Incredible Women Advancing A.I. Research

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"Through making our large datasets and systems publicly available, we've enabled research groups around the world to make significant progress on building machines that can automatically answer questions about visual content," she highlights. When Thomas first started researching deep neural networks a few years ago, virtually no educational resources existed online. Suchi Saria, Assistant Professor at Johns Hopkins University, believes computational modeling of data from sensor platforms and electronic medical records presents "a tremendous opportunity for high impact work." Since receiving her PhD in Computer Science from Stanford, Shubha Nabar has built data products and data science teams at Microsoft, LinkedIn, and now Salesforce.


Understanding the Artificial Intelligence Hype Cycle, in 5 Stats

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We're witnessing an arms race that involves just about every major technology company, from martech giant Salesforce to the'Chinese Google' Baidu to old dogs like Microsoft. In Gartner's hype cycle, which ranks technologies based on how the market perceives them and how far away they are from mainstream adoption, machine learning is right at the tippy top. The research firm expects companies driven by insights (i.e., from data and AI) to significantly outperform those that don't or can't. Yet marketers should be happy that every martech giant is investing heavily in machine learning.


3 types of artificial intelligence, but only 2 are valid

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Current AI applications can be broken down into three loose categories: Transformative AI, DIY (Do It Yourself) AI, and Faux AI. Transformative AI turns data into insights and insights into instructions. While there is indeed a finite set of actions involved in driving, the data set the AI must process shifts every single time the passenger gets into the car based on road conditions, destination, route, oncoming and surrounding traffic, street lanes, street closures, proximity to neighboring vehicles, a pedestrian stepping out in front of the car, and so on. DIY AI is any artificial intelligence platform whose end goal is to make you, the user, more informed so that you can then do the remaining work yourself.


How Artificial Intelligence will impact professional writing

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An AI algorithm developed by researchers at Salesforce generates snippets of text that describe the essence of long text. These tools can help writers skim through a lot of articles and find relevant topics to write about. "Since new semantic technologies are now mature enough to read human language, journalists and professional writers can finally go back to writing for people," Cuofano says. "The next revolution (which is already coming) is the leap from NLP to a subset of it called NLU (Natural Language Understanding)," Cuofano says.


How Salesforce CEO Marc Benioff uses artificial intelligence to end internal politics at meetings

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He invites this version of Einstein, called Einstein Guidance, to his Monday morning staff meetings, where up to 30 top executives update him on their progress. Einstein Guidance is designed to do forecasting and modeling. And we then have a piece of Einstein now that we've not yet rolled out to our customers, called Einstein Guidance. Most CEOs likely will one day have a so-called AI executive listening in on meetings and keeping everyone honest with the data.


How Artificial Intelligence will impact professional writing

#artificialintelligence

An AI algorithm developed by researchers at Salesforce generates snippets of text that describe the essence of long text. These tools can help writers skim through a lot of articles and find relevant topics to write about. "Since new semantic technologies are now mature enough to read human language, journalists and professional writers can finally go back to writing for people," Cuofano says. "The next revolution (which is already coming) is the leap from NLP to a subset of it called NLU (Natural Language Understanding)," Cuofano says.


A new AI algorithm summarizes text amazingly well

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An algorithm developed by researchers at Salesforce shows how computers may eventually take on the job of summarizing documents. The system learns from examples of good summaries, an approach called supervised learning, but also employs a kind of artificial attention to the text it is ingesting and outputting. Kristian Hammond, a professor at Northwestern University, and the founder of Narrative Science, a company that generates narrative reports from raw data, says the Salesforce research is a good advance, but it also shows the limits of relying purely on statistical machine learning. A startup called Maluuba, which was acquired earlier this year by Microsoft, recently produced a system capable of generating relevant questions from text.