John McCarthy, artificial intelligence pioneer, playing chess at Stanford’s IBM 7090
John McCarthy used an improved version of the Kotok program to play correspondence chess against a Soviet program developed at the Moscow Institute of Theoretical and Experimental Physics (ITEP) by George Adelson-Velsky and others. In 1967, a four-game match played over nine months was won 3-1 by the Soviet program.
Source: Chessprogramming.org
In 2018, the total transaction value of M&A deals announced in the global TMT sector reached $630 billion, up 23% from 2017 and significantly ahead of other markets in both 2017 and 2018, according to GlobalData’s Deals Database.
GlobalData’s latest thematic report, Mergers & Acquisitions in Technology Media and Telecoms (TMT), reveals the most notable deals over the last five years, identifies their key thematic drivers, and predicts potential future acquisition targets.
What is the state-of-AI in July 2019? Recent surveys, studies, and forecasts illustrate future expectations and current realities regarding the impact of AI on jobs; the conditions, challenges, and benefits of AI adoption; and bits of data related to data or AI fuel.
$142,859: Average salary of machine learning engineer, May 2019 [Indeed]
29.1%: Increase in AI job postings on Indeed over the last 12 months, down from 57.9% increase from May 2017 to May 2018 [Indeed]
20%: Percentage of job seekers (11,000) that fear they will one day lose their job to AI [Ziprecuiter]
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In December 2014, I asked whether we were at the beginning of “the end of the Hadoop bubble.” I kept updating my Hadoop bubble watch (here and here) through the much-hyped IPOs of Hortonworks and Cloudera. The question was whether an open-source distributed storage technology which Google invented (and quickly replaced with better tools) could survive as a business proposition at a time when enterprises have moved rapidly to adopting the cloud and “AI”—advanced machine learning or deep learning.
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The Harvard Data Science Initiative (HDSI) and the MIT Press just launched Harvard Data Science Review (HDSR), a “premier research journal, a leading educational publication, and a popular magazine.”
The inaugural issue of HDSR includes contributions from internationally renowned scholars and educators, as well as leading researchers in industry and government, such as Christine Borgman (UCLA), Rodney Brooks (MIT), Emmanuel Candes (Stanford University), David Donoho (Stanford University), Luciano Floridi (Oxford/The Alan Turing Institute), Alan M. Garber (Harvard), Barbara J. Grosz (Harvard), Alfred Hero (University of Michigan), Sabina Leonelli (University of Exeter), Michael I. Jordan (University of California, Berkeley), Andrew Lo (MIT), Maja Matari? (University of Southern California), Brendan McCord (US Department of Defense), Nathan Sanders (Warner Media), Rebecca Willett (University of Chicago), and Jeannette Wing (Columbia University).
Sample articles in the first issue:
Featured articles on AI:
You will find more infographics at Statista
From BuzzFeed:
The recent discourse about AirPods, whether they’re good or bad, or neutral themselves but separating everyone from the physical, echoes what the original Walkman inspired. “With the advent of the Sony Walkman came the end of meeting people,” a CBS Records vice president complained to the Post. “It’s like a drug: You put the Walkman on and you blot out the rest of the world.” George F. Will defended the Walkman because it separated you from the walkabout realities of everyday life! According to an academic paper, a French interviewer asked young people “whether they are losing contact with reality,” “whether the relations between eyes and ears are changing radically,” “whether they are worried about the fate of humanity.” Allan Bloom’s argument about the decline in college education, The Closing of the American Mind, features a throw-yourself-down-the-stairs grotesque of a teenage boy, toward whom the entire world has now been oriented, wearing a Walkman.
“We have entered the age of the urban hermit,” Walter Shapiro wrote in ’82, lamenting the end of the boom box and calling the Walkman “a potent symbol of an antisocial electronic future.”
Privacy policy
It seems that no week passes by without yet another revelation of how the most successful tech companies play with our data. When your business is driven by data, you are driven to ignore possible data leaks, to question the rights of your users to their own data, and to use double-speak whenever the question of data privacy arises.
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2019 salaries of data scientists–managers (Burtch Works)
Earlier this month, Salesforce announced the acquisition of data visualization and analytics leader Tableau for $15.7 billion and Google announced the acquisition of data discovery and analytics platform Looker for $2.6 billion. Both acquired companies will beef up the acquiring companies’ Data Science as a Service (DSaaS) capabilities, providing their enterprise customers with a wide range of easy (or easier) to use tools that “democratize” data preparation, integration, analysis, and presentation.
With self-service data science, all business users that do not have statistical analysis background and don’t know how to code can make data-driven decisions, instead of relying on expensive and hard-to-find data scientists.
How expensive? The average annual base salary for an experienced data scientist in a management position is currently $257,443 according to Burtch Works.
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AI optimists drive enterprise adoption
US federal government contract obligations and AI-related investments grew almost 75% to nearly $700 million between fiscal 2016 and 2018 [Federal News Network].
85% of US CEOs and business leaders are AI optimists; 87% are investing in AI initiatives this year; 82% expect their businesses will be disrupted by AI to some extent within the next three years; 29% said AI will disrupt more than half of their business; 47% see China as the biggest obstacle to the advancement of AI in the US; 33% say employee trust is one of the greatest barriers to AI adoption [EY].
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