際際滷shows by User: HiveData / http://www.slideshare.net/images/logo.gif 際際滷shows by User: HiveData / Sat, 19 May 2018 01:09:57 GMT 際際滷Share feed for 際際滷shows by User: HiveData "Responsible AI", by Charlie Muirhead /slideshow/responsible-ai-by-charlie-muirhead/97566603 charliemuirheadceocognitionxhivesummitmay2018responsibleaiaukperspective-180519010957
From The Hive's 2018 Annual Summit.]]>
From The Hive's 2018 Annual Summit.]]> Sat, 19 May 2018 01:09:57 GMT /slideshow/responsible-ai-by-charlie-muirhead/97566603 HiveData@slideshare.net(HiveData) "Responsible AI", by Charlie Muirhead HiveData From The Hive's 2018 Annual Summit. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/charliemuirheadceocognitionxhivesummitmay2018responsibleaiaukperspective-180519010957-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> From The Hive&#39;s 2018 Annual Summit.
"Responsible AI", by Charlie Muirhead from The Hive
]]> 991 2 https://cdn.slidesharecdn.com/ss_thumbnails/charliemuirheadceocognitionxhivesummitmay2018responsibleaiaukperspective-180519010957-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Translating a Trillion Points of Data into Therapies, Diagnostics, and New Insights into Disease - by Atul Butte /slideshow/translating-a-trillion-points-of-data-into-therapies-diagnostics-and-new-insights-into-disease-by-atul-butte/97216217 201804hive2-180515210123
Lecture from The Hive's 2018 Annual Summit.]]>
Lecture from The Hive's 2018 Annual Summit.]]> Tue, 15 May 2018 21:01:23 GMT /slideshow/translating-a-trillion-points-of-data-into-therapies-diagnostics-and-new-insights-into-disease-by-atul-butte/97216217 HiveData@slideshare.net(HiveData) Translating a Trillion Points of Data into Therapies, Diagnostics, and New Insights into Disease - by Atul Butte HiveData Lecture from The Hive's 2018 Annual Summit. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/201804hive2-180515210123-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Lecture from The Hive&#39;s 2018 Annual Summit.
Translating a Trillion Points of Data into Therapies, Diagnostics, and New Insights into Disease - by Atul Butte from The Hive
]]> 344 4 https://cdn.slidesharecdn.com/ss_thumbnails/201804hive2-180515210123-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Digital Transformation; Digital Twins for Delivering Business Value in IIoT /slideshow/digital-transformation-digital-twins-for-delivering-business-value-in-iiot/92338901 digtwinsthehivepresentationpdf-180329171710
Presented by SVP & CTO of Rockwell Automation, Sujeet Chand on 3/28/18, hosted by TIBCO. Brought to you by The Hive. #hivedata]]>
Presented by SVP & CTO of Rockwell Automation, Sujeet Chand on 3/28/18, hosted by TIBCO. Brought to you by The Hive. #hivedata]]> Thu, 29 Mar 2018 17:17:09 GMT /slideshow/digital-transformation-digital-twins-for-delivering-business-value-in-iiot/92338901 HiveData@slideshare.net(HiveData) Digital Transformation; Digital Twins for Delivering Business Value in IIoT HiveData Presented by SVP & CTO of Rockwell Automation, Sujeet Chand on 3/28/18, hosted by TIBCO. Brought to you by The Hive. #hivedata <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/digtwinsthehivepresentationpdf-180329171710-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presented by SVP &amp; CTO of Rockwell Automation, Sujeet Chand on 3/28/18, hosted by TIBCO. Brought to you by The Hive. #hivedata
Digital Transformation; Digital Twins for Delivering Business Value in IIoT from The Hive
]]> 1142 4 https://cdn.slidesharecdn.com/ss_thumbnails/digtwinsthehivepresentationpdf-180329171710-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Quantum Computing (IBM Q) - Hive Think Tank Event w/ Dr. Bob Sutor - 02.22.18 /slideshow/quantum-computing-ibm-q-hive-think-tank-event-w-dr-bob-sutor-022218/88773871 20180222-ibmqgeneralpresentation-bobsutor-hivedata-180224000304
Dr. Bob Sutor is Vice President for AI, Blockchain, and Quantum Solutions at IBM Research. In this role he is the R&D executive leading a large global group of scientists, software engineers, and designers who create and integrate leading edge science and technologies to give IBM's clients the most advanced solutions available. Our work is often mathematically-based and thus includes AI technologies like machine learning, deep learning, text and image analytics, statistics, predictive analytics, and optimization. Sutor co-leads the IBM Research effort to support IBM's commercial blockchain efforts with advanced innovations across a broad range of its embedded technologies. He leads the group developing the next generation software stack and algorithms for quantum computers. Dr. Sutor has an undergraduate degree from Harvard College and a Ph.D. from Princeton University, both in Mathematics.]]>
Dr. Bob Sutor is Vice President for AI, Blockchain, and Quantum Solutions at IBM Research. In this role he is the R&D executive leading a large global group of scientists, software engineers, and designers who create and integrate leading edge science and technologies to give IBM's clients the most advanced solutions available. Our work is often mathematically-based and thus includes AI technologies like machine learning, deep learning, text and image analytics, statistics, predictive analytics, and optimization. Sutor co-leads the IBM Research effort to support IBM's commercial blockchain efforts with advanced innovations across a broad range of its embedded technologies. He leads the group developing the next generation software stack and algorithms for quantum computers. Dr. Sutor has an undergraduate degree from Harvard College and a Ph.D. from Princeton University, both in Mathematics.]]> Sat, 24 Feb 2018 00:03:04 GMT /slideshow/quantum-computing-ibm-q-hive-think-tank-event-w-dr-bob-sutor-022218/88773871 HiveData@slideshare.net(HiveData) Quantum Computing (IBM Q) - Hive Think Tank Event w/ Dr. Bob Sutor - 02.22.18 HiveData Dr. Bob Sutor is Vice President for AI, Blockchain, and Quantum Solutions at IBM Research. In this role he is the R&D executive leading a large global group of scientists, software engineers, and designers who create and integrate leading edge science and technologies to give IBM's clients the most advanced solutions available. Our work is often mathematically-based and thus includes AI technologies like machine learning, deep learning, text and image analytics, statistics, predictive analytics, and optimization. Sutor co-leads the IBM Research effort to support IBM's commercial blockchain efforts with advanced innovations across a broad range of its embedded technologies. He leads the group developing the next generation software stack and algorithms for quantum computers. Dr. Sutor has an undergraduate degree from Harvard College and a Ph.D. from Princeton University, both in Mathematics. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20180222-ibmqgeneralpresentation-bobsutor-hivedata-180224000304-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Dr. Bob Sutor is Vice President for AI, Blockchain, and Quantum Solutions at IBM Research. In this role he is the R&amp;D executive leading a large global group of scientists, software engineers, and designers who create and integrate leading edge science and technologies to give IBM&#39;s clients the most advanced solutions available. Our work is often mathematically-based and thus includes AI technologies like machine learning, deep learning, text and image analytics, statistics, predictive analytics, and optimization. Sutor co-leads the IBM Research effort to support IBM&#39;s commercial blockchain efforts with advanced innovations across a broad range of its embedded technologies. He leads the group developing the next generation software stack and algorithms for quantum computers. Dr. Sutor has an undergraduate degree from Harvard College and a Ph.D. from Princeton University, both in Mathematics.
Quantum Computing (IBM Q) - Hive Think Tank Event w/ Dr. Bob Sutor - 02.22.18 from The Hive
]]> 1409 3 https://cdn.slidesharecdn.com/ss_thumbnails/20180222-ibmqgeneralpresentation-bobsutor-hivedata-180224000304-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Rendezvous Architecture Makes Machine Learning Logistics Easier /slideshow/hivethinktank102317teddunningmachinelearninglogistics/81163607 hivethinktank102317-ted-dunning-machine-learning-logistics-171024195025
Think Tank Event 10/23/2017, hosted by The Hive and presented by Ted Dunning, Chief Application Architect of MapR Technologies and Ellen Friedman of MapR Technologies.]]>
Think Tank Event 10/23/2017, hosted by The Hive and presented by Ted Dunning, Chief Application Architect of MapR Technologies and Ellen Friedman of MapR Technologies.]]> Tue, 24 Oct 2017 19:50:24 GMT /slideshow/hivethinktank102317teddunningmachinelearninglogistics/81163607 HiveData@slideshare.net(HiveData) The Hive Think Tank: Rendezvous Architecture Makes Machine Learning Logistics Easier HiveData Think Tank Event 10/23/2017, hosted by The Hive and presented by Ted Dunning, Chief Application Architect of MapR Technologies and Ellen Friedman of MapR Technologies. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hivethinktank102317-ted-dunning-machine-learning-logistics-171024195025-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Think Tank Event 10/23/2017, hosted by The Hive and presented by Ted Dunning, Chief Application Architect of MapR Technologies and Ellen Friedman of MapR Technologies.
The Hive Think Tank: Rendezvous Architecture Makes Machine Learning Logistics Easier from The Hive
]]> 690 3 https://cdn.slidesharecdn.com/ss_thumbnails/hivethinktank102317-ted-dunning-machine-learning-logistics-171024195025-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Data Science in the Enterprise /slideshow/data-science-in-the-enterprise/75971853 amr-cdsw-thehive-20170511-170515032224
Amr Awadallah's slides from his talk at TIBCO in collaboration with The Hive Think Tank on May 11th, 2017.]]>
Amr Awadallah's slides from his talk at TIBCO in collaboration with The Hive Think Tank on May 11th, 2017.]]> Mon, 15 May 2017 03:22:24 GMT /slideshow/data-science-in-the-enterprise/75971853 HiveData@slideshare.net(HiveData) Data Science in the Enterprise HiveData Amr Awadallah's slides from his talk at TIBCO in collaboration with The Hive Think Tank on May 11th, 2017. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/amr-cdsw-thehive-20170511-170515032224-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Amr Awadallah&#39;s slides from his talk at TIBCO in collaboration with The Hive Think Tank on May 11th, 2017.
Data Science in the Enterprise from The Hive
]]> 1244 2 https://cdn.slidesharecdn.com/ss_thumbnails/amr-cdsw-thehive-20170511-170515032224-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 AI in Software for Augmenting Intelligence Across the Enterprise /slideshow/pdf-ai-in-software-for-augmenting-intelligence-across-the-enterprise/75196270 2017-04-12aihivemocandasfinaltohiveforshare1-170419220330
際際滷s from Michael O'Connell, Chief Analytics Officer TIBCO and Ahmer Srivastava, Director of Analytics, Wafer Operations Western Digital]]>
際際滷s from Michael O'Connell, Chief Analytics Officer TIBCO and Ahmer Srivastava, Director of Analytics, Wafer Operations Western Digital]]> Wed, 19 Apr 2017 22:03:30 GMT /slideshow/pdf-ai-in-software-for-augmenting-intelligence-across-the-enterprise/75196270 HiveData@slideshare.net(HiveData) AI in Software for Augmenting Intelligence Across the Enterprise HiveData 際際滷s from Michael O'Connell, Chief Analytics Officer TIBCO and Ahmer Srivastava, Director of Analytics, Wafer Operations Western Digital <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2017-04-12aihivemocandasfinaltohiveforshare1-170419220330-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 際際滷s from Michael O&#39;Connell, Chief Analytics Officer TIBCO and Ahmer Srivastava, Director of Analytics, Wafer Operations Western Digital
AI in Software for Augmenting Intelligence Across the Enterprise from The Hive
]]> 1236 7 https://cdn.slidesharecdn.com/ss_thumbnails/2017-04-12aihivemocandasfinaltohiveforshare1-170419220330-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 High Precision Analytics for Healthcare: Promises and Challenges by Sriram Vishwanath /slideshow/predictive-analytics-for-healthcare-payers-and-providers-by-sriram-vishwanath/73377216 9-170320182328
This talk by Sriram Vishwanath was a part of The Hive Annual Summit 2017. You can watch Vishwanaths talk on YouTube HiveMumble channel.]]>
This talk by Sriram Vishwanath was a part of The Hive Annual Summit 2017. You can watch Vishwanaths talk on YouTube HiveMumble channel.]]> Mon, 20 Mar 2017 18:23:28 GMT /slideshow/predictive-analytics-for-healthcare-payers-and-providers-by-sriram-vishwanath/73377216 HiveData@slideshare.net(HiveData) High Precision Analytics for Healthcare: Promises and Challenges by Sriram Vishwanath HiveData This talk by Sriram Vishwanath was a part of The Hive Annual Summit 2017. You can watch Vishwanaths talk on YouTube HiveMumble channel. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/9-170320182328-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This talk by Sriram Vishwanath was a part of The Hive Annual Summit 2017. You can watch Vishwanaths talk on YouTube HiveMumble channel.
High Precision Analytics for Healthcare: Promises and Challenges by Sriram Vishwanath from The Hive
]]> 490 4 https://cdn.slidesharecdn.com/ss_thumbnails/9-170320182328-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 "The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation /slideshow/the-future-of-manufacturing-by-sujeet-chand-svpcto-rockwell-automation/73377107 3-170320182114
This talk was part of The Hive Annual Summit 2017. You can watch Chands talk on a YouTube HiveMumble channel.]]>
This talk was part of The Hive Annual Summit 2017. You can watch Chands talk on a YouTube HiveMumble channel.]]> Mon, 20 Mar 2017 18:21:14 GMT /slideshow/the-future-of-manufacturing-by-sujeet-chand-svpcto-rockwell-automation/73377107 HiveData@slideshare.net(HiveData) "The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation HiveData This talk was part of The Hive Annual Summit 2017. You can watch Chands talk on a YouTube HiveMumble channel. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/3-170320182114-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This talk was part of The Hive Annual Summit 2017. You can watch Chands talk on a YouTube HiveMumble channel.
"The Future of Manufacturing" by Sujeet Chand, SVP&CTO, Rockwell Automation from The Hive
]]> 792 3 https://cdn.slidesharecdn.com/ss_thumbnails/3-170320182114-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Social Impact & Ethics of AI by Steve Omohundro /slideshow/social-impact-ethics-of-ai-by-steve-omohundro/73376820 11-170320181518
This talk was part of The Hive Annual Summit 2017 on "AI & the Future of Business. You can watch Omohundros talk on YouTube HiveMumble channel. ]]>
This talk was part of The Hive Annual Summit 2017 on "AI & the Future of Business. You can watch Omohundros talk on YouTube HiveMumble channel. ]]> Mon, 20 Mar 2017 18:15:18 GMT /slideshow/social-impact-ethics-of-ai-by-steve-omohundro/73376820 HiveData@slideshare.net(HiveData) Social Impact & Ethics of AI by Steve Omohundro HiveData This talk was part of The Hive Annual Summit 2017 on "AI & the Future of Business. You can watch Omohundros talk on YouTube HiveMumble channel. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/11-170320181518-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This talk was part of The Hive Annual Summit 2017 on &quot;AI &amp; the Future of Business. You can watch Omohundros talk on YouTube HiveMumble channel.
Social Impact & Ethics of AI by Steve Omohundro from The Hive
]]> 1279 7 https://cdn.slidesharecdn.com/ss_thumbnails/11-170320181518-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: AI in The Enterprise by Venkat Srinivasan /slideshow/the-hive-think-tank-ai-in-the-enterprise-by-venkat-srinivasan/71825555 aienterprise2017v7hive-170206181401
This The Hive Think Tank talk by Venkat Srinivasan, CEO of RAGE Frameworks, focuses on successful applications of AI in the Enterprise. We start with a broad and more inclusive definition of AI in the context of enterprise business processes. We introduce a taxonomy of AI solution methods that broaden the focus beyond a narrow focus on deep learning based on neural nets. In line with the taxonomy, we present several successful AI applications in use today at major corporations across industries including financial services, manufacturing/retail, professional services, logistics. These applications range from commercial lending, contract review, customer service intelligence, market and competitive intelligence, signals for capital markets, regulatory compliance and others.]]>
This The Hive Think Tank talk by Venkat Srinivasan, CEO of RAGE Frameworks, focuses on successful applications of AI in the Enterprise. We start with a broad and more inclusive definition of AI in the context of enterprise business processes. We introduce a taxonomy of AI solution methods that broaden the focus beyond a narrow focus on deep learning based on neural nets. In line with the taxonomy, we present several successful AI applications in use today at major corporations across industries including financial services, manufacturing/retail, professional services, logistics. These applications range from commercial lending, contract review, customer service intelligence, market and competitive intelligence, signals for capital markets, regulatory compliance and others.]]> Mon, 06 Feb 2017 18:14:00 GMT /slideshow/the-hive-think-tank-ai-in-the-enterprise-by-venkat-srinivasan/71825555 HiveData@slideshare.net(HiveData) The Hive Think Tank: AI in The Enterprise by Venkat Srinivasan HiveData This The Hive Think Tank talk by Venkat Srinivasan, CEO of RAGE Frameworks, focuses on successful applications of AI in the Enterprise. We start with a broad and more inclusive definition of AI in the context of enterprise business processes. We introduce a taxonomy of AI solution methods that broaden the focus beyond a narrow focus on deep learning based on neural nets. In line with the taxonomy, we present several successful AI applications in use today at major corporations across industries including financial services, manufacturing/retail, professional services, logistics. These applications range from commercial lending, contract review, customer service intelligence, market and competitive intelligence, signals for capital markets, regulatory compliance and others. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/aienterprise2017v7hive-170206181401-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This The Hive Think Tank talk by Venkat Srinivasan, CEO of RAGE Frameworks, focuses on successful applications of AI in the Enterprise. We start with a broad and more inclusive definition of AI in the context of enterprise business processes. We introduce a taxonomy of AI solution methods that broaden the focus beyond a narrow focus on deep learning based on neural nets. In line with the taxonomy, we present several successful AI applications in use today at major corporations across industries including financial services, manufacturing/retail, professional services, logistics. These applications range from commercial lending, contract review, customer service intelligence, market and competitive intelligence, signals for capital markets, regulatory compliance and others.
The Hive Think Tank: AI in The Enterprise by Venkat Srinivasan from The Hive
]]> 1496 7 https://cdn.slidesharecdn.com/ss_thumbnails/aienterprise2017v7hive-170206181401-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Machine Learning Applications in Genomics by Prof. Jian Ma, CMU /slideshow/prof-jian-ma/70189132 ma-hive-final-4-161216003015
In this The Hive Think Tank talk, Professor Jian Ma introduces machine learning methods that can be used to help tackle some of the most intriguing questions in genomics and biomedicine. He discusses the research projects in his group to study genome structure and function, including algorithms to unravel complex genomic aberrations in cancer genomes and gene regulatory principles encoded in our genome, by utilizing probabilistic graphical models and deep neural network techniques. The knowledge obtained from such computational methods can greatly enhance our ability to understand disease genomes.]]>
In this The Hive Think Tank talk, Professor Jian Ma introduces machine learning methods that can be used to help tackle some of the most intriguing questions in genomics and biomedicine. He discusses the research projects in his group to study genome structure and function, including algorithms to unravel complex genomic aberrations in cancer genomes and gene regulatory principles encoded in our genome, by utilizing probabilistic graphical models and deep neural network techniques. The knowledge obtained from such computational methods can greatly enhance our ability to understand disease genomes.]]> Fri, 16 Dec 2016 00:30:15 GMT /slideshow/prof-jian-ma/70189132 HiveData@slideshare.net(HiveData) The Hive Think Tank: Machine Learning Applications in Genomics by Prof. Jian Ma, CMU HiveData In this The Hive Think Tank talk, Professor Jian Ma introduces machine learning methods that can be used to help tackle some of the most intriguing questions in genomics and biomedicine. He discusses the research projects in his group to study genome structure and function, including algorithms to unravel complex genomic aberrations in cancer genomes and gene regulatory principles encoded in our genome, by utilizing probabilistic graphical models and deep neural network techniques. The knowledge obtained from such computational methods can greatly enhance our ability to understand disease genomes. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ma-hive-final-4-161216003015-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this The Hive Think Tank talk, Professor Jian Ma introduces machine learning methods that can be used to help tackle some of the most intriguing questions in genomics and biomedicine. He discusses the research projects in his group to study genome structure and function, including algorithms to unravel complex genomic aberrations in cancer genomes and gene regulatory principles encoded in our genome, by utilizing probabilistic graphical models and deep neural network techniques. The knowledge obtained from such computational methods can greatly enhance our ability to understand disease genomes.
The Hive Think Tank: Machine Learning Applications in Genomics by Prof. Jian Ma, CMU from The Hive
]]> 1925 7 https://cdn.slidesharecdn.com/ss_thumbnails/ma-hive-final-4-161216003015-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: The Future Of Customer Support - AI Driven Automation /slideshow/the-hive-think-tank-the-future-of-customer-support-ai-driven-automation/69739908 hivepanelfutureofcusserv-161201213837
The Hive Think Tank Panel Discussion moderated by Kate Leggett (Forrester) with panelists: Allan Leinwand (ServiceNow), Nitin Narkhede (Wipro), Jason Smale (Zendesk), Dan Turchin (Neva). The future of customer support is AI-driven virtual agents. Soon, well interact conversationally with bots that know who we are, how were impacted, and what we need. Soon, the capabilities of virtual agents will far exceed those of todays best human agents. Well receive support that is more reliable than friends, more accurate than social media, and less frustrating than waiting on hold.]]>
The Hive Think Tank Panel Discussion moderated by Kate Leggett (Forrester) with panelists: Allan Leinwand (ServiceNow), Nitin Narkhede (Wipro), Jason Smale (Zendesk), Dan Turchin (Neva). The future of customer support is AI-driven virtual agents. Soon, well interact conversationally with bots that know who we are, how were impacted, and what we need. Soon, the capabilities of virtual agents will far exceed those of todays best human agents. Well receive support that is more reliable than friends, more accurate than social media, and less frustrating than waiting on hold.]]> Thu, 01 Dec 2016 21:38:37 GMT /slideshow/the-hive-think-tank-the-future-of-customer-support-ai-driven-automation/69739908 HiveData@slideshare.net(HiveData) The Hive Think Tank: The Future Of Customer Support - AI Driven Automation HiveData The Hive Think Tank Panel Discussion moderated by Kate Leggett (Forrester) with panelists: Allan Leinwand (ServiceNow), Nitin Narkhede (Wipro), Jason Smale (Zendesk), Dan Turchin (Neva). The future of customer support is AI-driven virtual agents. Soon, well interact conversationally with bots that know who we are, how were impacted, and what we need. Soon, the capabilities of virtual agents will far exceed those of todays best human agents. Well receive support that is more reliable than friends, more accurate than social media, and less frustrating than waiting on hold. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hivepanelfutureofcusserv-161201213837-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The Hive Think Tank Panel Discussion moderated by Kate Leggett (Forrester) with panelists: Allan Leinwand (ServiceNow), Nitin Narkhede (Wipro), Jason Smale (Zendesk), Dan Turchin (Neva). The future of customer support is AI-driven virtual agents. Soon, well interact conversationally with bots that know who we are, how were impacted, and what we need. Soon, the capabilities of virtual agents will far exceed those of todays best human agents. Well receive support that is more reliable than friends, more accurate than social media, and less frustrating than waiting on hold.
The Hive Think Tank: The Future Of Customer Support - AI Driven Automation from The Hive
]]> 942 6 https://cdn.slidesharecdn.com/ss_thumbnails/hivepanelfutureofcusserv-161201213837-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Talk by Mohandas Pai - India at 2030, How Tech Entrepreneurship Will Create A $10 Trillion Economy /slideshow/the-hive-think-tank-talk-by-mohandas-pai-india-at-2030/69420746 thehivethinktank-indiaat2030-mohandaspai-161122182152
Over the next 15 years, India's growth will be fueled by its startups. Today, there are over 20,000 startups in India that have created a value of $80 billion and employ 325,000 people. Over the next ten years, by 2025, there will be 100,000 startups in the country that would have created over $500 billion of value and employ 3.2 million people. This talk is about India's growth over the next 15 years and the prominent role that entrepreneurs and startups will play in its rapid evolution. ]]>
Over the next 15 years, India's growth will be fueled by its startups. Today, there are over 20,000 startups in India that have created a value of $80 billion and employ 325,000 people. Over the next ten years, by 2025, there will be 100,000 startups in the country that would have created over $500 billion of value and employ 3.2 million people. This talk is about India's growth over the next 15 years and the prominent role that entrepreneurs and startups will play in its rapid evolution. ]]> Tue, 22 Nov 2016 18:21:52 GMT /slideshow/the-hive-think-tank-talk-by-mohandas-pai-india-at-2030/69420746 HiveData@slideshare.net(HiveData) The Hive Think Tank: Talk by Mohandas Pai - India at 2030, How Tech Entrepreneurship Will Create A $10 Trillion Economy HiveData Over the next 15 years, India's growth will be fueled by its startups. Today, there are over 20,000 startups in India that have created a value of $80 billion and employ 325,000 people. Over the next ten years, by 2025, there will be 100,000 startups in the country that would have created over $500 billion of value and employ 3.2 million people. This talk is about India's growth over the next 15 years and the prominent role that entrepreneurs and startups will play in its rapid evolution. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/thehivethinktank-indiaat2030-mohandaspai-161122182152-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Over the next 15 years, India&#39;s growth will be fueled by its startups. Today, there are over 20,000 startups in India that have created a value of $80 billion and employ 325,000 people. Over the next ten years, by 2025, there will be 100,000 startups in the country that would have created over $500 billion of value and employ 3.2 million people. This talk is about India&#39;s growth over the next 15 years and the prominent role that entrepreneurs and startups will play in its rapid evolution.
The Hive Think Tank: Talk by Mohandas Pai - India at 2030, How Tech Entrepreneurship Will Create A $10 Trillion Economy from The Hive
]]> 1223 10 https://cdn.slidesharecdn.com/ss_thumbnails/thehivethinktank-indiaat2030-mohandaspai-161122182152-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: The Content Trap - Strategist's Guide to Digital Change /slideshow/the-hive-think-tank-the-content-trap-strategists-guide-to-digital-change-67083546/67083546 contenttrapbharatanandhivethinktankoctober52016-161012174812
In this The Hive Think Tank talk Harvard Business School Professor of Strategy Prof. Bharat Anand shares his insights on the Digital innovation trends that are shaping the way organizations will act in the future. In this talk, Professor Anand presents the findings from his forthcoming book. To answer these questions, Anand examines a range of businesses around the world, from Chinese internet giant Tencent to Scandinavian digital trailblazer Schibsted, from The New York Times to The Economist, and from talent management to the future of education.]]>
In this The Hive Think Tank talk Harvard Business School Professor of Strategy Prof. Bharat Anand shares his insights on the Digital innovation trends that are shaping the way organizations will act in the future. In this talk, Professor Anand presents the findings from his forthcoming book. To answer these questions, Anand examines a range of businesses around the world, from Chinese internet giant Tencent to Scandinavian digital trailblazer Schibsted, from The New York Times to The Economist, and from talent management to the future of education.]]> Wed, 12 Oct 2016 17:48:12 GMT /slideshow/the-hive-think-tank-the-content-trap-strategists-guide-to-digital-change-67083546/67083546 HiveData@slideshare.net(HiveData) The Hive Think Tank: The Content Trap - Strategist's Guide to Digital Change HiveData In this The Hive Think Tank talk Harvard Business School Professor of Strategy Prof. Bharat Anand shares his insights on the Digital innovation trends that are shaping the way organizations will act in the future. In this talk, Professor Anand presents the findings from his forthcoming book. To answer these questions, Anand examines a range of businesses around the world, from Chinese internet giant Tencent to Scandinavian digital trailblazer Schibsted, from The New York Times to The Economist, and from talent management to the future of education. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/contenttrapbharatanandhivethinktankoctober52016-161012174812-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this The Hive Think Tank talk Harvard Business School Professor of Strategy Prof. Bharat Anand shares his insights on the Digital innovation trends that are shaping the way organizations will act in the future. In this talk, Professor Anand presents the findings from his forthcoming book. To answer these questions, Anand examines a range of businesses around the world, from Chinese internet giant Tencent to Scandinavian digital trailblazer Schibsted, from The New York Times to The Economist, and from talent management to the future of education.
The Hive Think Tank: The Content Trap - Strategist's Guide to Digital Change from The Hive
]]> 3347 8 https://cdn.slidesharecdn.com/ss_thumbnails/contenttrapbharatanandhivethinktankoctober52016-161012174812-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Deep Visual Understanding from Deep Learning by Prof. Jitendra Malik /slideshow/deep-visual-understanding-from-deep-learning-by-prof-jitendra-malik/66110321 jitendramalikhivetalk-160916223556
In this The Hive Think Tank talk, Prof. Jitendra Malik talks about Artificial Intelligence (AI) and Computer Vision, past, present and future.]]>
In this The Hive Think Tank talk, Prof. Jitendra Malik talks about Artificial Intelligence (AI) and Computer Vision, past, present and future.]]> Fri, 16 Sep 2016 22:35:56 GMT /slideshow/deep-visual-understanding-from-deep-learning-by-prof-jitendra-malik/66110321 HiveData@slideshare.net(HiveData) Deep Visual Understanding from Deep Learning by Prof. Jitendra Malik HiveData In this The Hive Think Tank talk, Prof. Jitendra Malik talks about Artificial Intelligence (AI) and Computer Vision, past, present and future. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/jitendramalikhivetalk-160916223556-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this The Hive Think Tank talk, Prof. Jitendra Malik talks about Artificial Intelligence (AI) and Computer Vision, past, present and future.
Deep Visual Understanding from Deep Learning by Prof. Jitendra Malik from The Hive
]]> 2444 8 https://cdn.slidesharecdn.com/ss_thumbnails/jitendramalikhivetalk-160916223556-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Heron at Twitter /slideshow/the-hive-think-tank-heron-at-twitter/65606174 heron-meetup-hive-2016-160901203303
In this The Hive Think Tank talk, Heron team provides an introduction to Heron, how it is being used at Twitter and shares an operating experiences and challenges of running Heron at scale. They recently announced the open sourcing of Heron under the permissive Apache v2.0 license. Heron has been in production nearly 2 years and is widely used by several teams for diverse use cases. Prior to Heron, Twitter used Apache Storm, which we open sourced in 2011. Heron features a wide array of architectural improvements and is backward compatible with the Storm ecosystem for seamless adoption. ]]>
In this The Hive Think Tank talk, Heron team provides an introduction to Heron, how it is being used at Twitter and shares an operating experiences and challenges of running Heron at scale. They recently announced the open sourcing of Heron under the permissive Apache v2.0 license. Heron has been in production nearly 2 years and is widely used by several teams for diverse use cases. Prior to Heron, Twitter used Apache Storm, which we open sourced in 2011. Heron features a wide array of architectural improvements and is backward compatible with the Storm ecosystem for seamless adoption. ]]> Thu, 01 Sep 2016 20:33:03 GMT /slideshow/the-hive-think-tank-heron-at-twitter/65606174 HiveData@slideshare.net(HiveData) The Hive Think Tank: Heron at Twitter HiveData In this The Hive Think Tank talk, Heron team provides an introduction to Heron, how it is being used at Twitter and shares an operating experiences and challenges of running Heron at scale. They recently announced the open sourcing of Heron under the permissive Apache v2.0 license. Heron has been in production nearly 2 years and is widely used by several teams for diverse use cases. Prior to Heron, Twitter used Apache Storm, which we open sourced in 2011. Heron features a wide array of architectural improvements and is backward compatible with the Storm ecosystem for seamless adoption. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/heron-meetup-hive-2016-160901203303-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this The Hive Think Tank talk, Heron team provides an introduction to Heron, how it is being used at Twitter and shares an operating experiences and challenges of running Heron at scale. They recently announced the open sourcing of Heron under the permissive Apache v2.0 license. Heron has been in production nearly 2 years and is widely used by several teams for diverse use cases. Prior to Heron, Twitter used Apache Storm, which we open sourced in 2011. Heron features a wide array of architectural improvements and is backward compatible with the Storm ecosystem for seamless adoption.
The Hive Think Tank: Heron at Twitter from The Hive
]]> 1245 2 https://cdn.slidesharecdn.com/ss_thumbnails/heron-meetup-hive-2016-160901203303-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Unpacking AI for Healthcare /slideshow/unpacking-ai-for-healthcare/65564451 unpackingaiforhealthcarebyashdamle-160831193815
In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiatas core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management. ]]>
In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiatas core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management. ]]> Wed, 31 Aug 2016 19:38:14 GMT /slideshow/unpacking-ai-for-healthcare/65564451 HiveData@slideshare.net(HiveData) The Hive Think Tank: Unpacking AI for Healthcare HiveData In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiatas core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/unpackingaiforhealthcarebyashdamle-160831193815-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this The Hive Think Tank talk, Ash Damle, CEO of Lumiata takes a deep dive into Lumiatas core technological engine - the Lumiata Medical Graph, which applies graph-based machine learning to compute the complex relationships between health data in the same way that a physician would, and how this medical AI engine powers personalization and automation within risk and care management.
The Hive Think Tank: Unpacking AI for Healthcare from The Hive
]]> 2603 14 https://cdn.slidesharecdn.com/ss_thumbnails/unpackingaiforhealthcarebyashdamle-160831193815-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank: Translating IoT into Innovation at Every Level by Prith Banerjee, CTO of Schneider Electric /slideshow/the-hive-think-tank-translating-iot-into-innovation-at-every-level-by-prith-banerjee-cto-of-schneider-electric/62642265 iot-hivethinktankkeynote-june2016-160602042136
In this presentation Prith Banerjee discusses how a sustainable future must become radically more efficient with the way we use energy. He shared how the Internet of Things (IoT) and the convergence of Operational Technology (OT) and Information Technology (IT) are enabling Schneider Electric's innovation at every level, redefining power and automation for a new world of energy which is more electric, decarbonized, decentralized and digitized. Prith shared how, in this new world of energy, Schneider ensures that Life Is On everywhere, for everyone and at every moment. He also shared a set of IoT predictions for the future, based on findings of the companys recent IoT Survey of 2,500 top business executives.]]>
In this presentation Prith Banerjee discusses how a sustainable future must become radically more efficient with the way we use energy. He shared how the Internet of Things (IoT) and the convergence of Operational Technology (OT) and Information Technology (IT) are enabling Schneider Electric's innovation at every level, redefining power and automation for a new world of energy which is more electric, decarbonized, decentralized and digitized. Prith shared how, in this new world of energy, Schneider ensures that Life Is On everywhere, for everyone and at every moment. He also shared a set of IoT predictions for the future, based on findings of the companys recent IoT Survey of 2,500 top business executives.]]> Thu, 02 Jun 2016 04:21:35 GMT /slideshow/the-hive-think-tank-translating-iot-into-innovation-at-every-level-by-prith-banerjee-cto-of-schneider-electric/62642265 HiveData@slideshare.net(HiveData) The Hive Think Tank: Translating IoT into Innovation at Every Level by Prith Banerjee, CTO of Schneider Electric HiveData In this presentation Prith Banerjee discusses how a sustainable future must become radically more efficient with the way we use energy. He shared how the Internet of Things (IoT) and the convergence of Operational Technology (OT) and Information Technology (IT) are enabling Schneider Electric's innovation at every level, redefining power and automation for a new world of energy which is more electric, decarbonized, decentralized and digitized. Prith shared how, in this new world of energy, Schneider ensures that Life Is On everywhere, for everyone and at every moment. He also shared a set of IoT predictions for the future, based on findings of the companys recent IoT Survey of 2,500 top business executives. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iot-hivethinktankkeynote-june2016-160602042136-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In this presentation Prith Banerjee discusses how a sustainable future must become radically more efficient with the way we use energy. He shared how the Internet of Things (IoT) and the convergence of Operational Technology (OT) and Information Technology (IT) are enabling Schneider Electric&#39;s innovation at every level, redefining power and automation for a new world of energy which is more electric, decarbonized, decentralized and digitized. Prith shared how, in this new world of energy, Schneider ensures that Life Is On everywhere, for everyone and at every moment. He also shared a set of IoT predictions for the future, based on findings of the companys recent IoT Survey of 2,500 top business executives.
The Hive Think Tank: Translating IoT into Innovation at Every Level by Prith Banerjee, CTO of Schneider Electric from The Hive
]]> 2396 5 https://cdn.slidesharecdn.com/ss_thumbnails/iot-hivethinktankkeynote-june2016-160602042136-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The Hive Think Tank - The Microsoft Big Data Stack by Raghu Ramakrishnan, CTO for Data, Microsoft /slideshow/the-hive-think-tank-the-microsoft-big-data-stack-by-raghu-ramakrishnan-cto-for-data-microsoft/62437561 microsoft-data-services-2016-160526172350
Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation. Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit. While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack.]]>
Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation. Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit. While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack.]]> Thu, 26 May 2016 17:23:49 GMT /slideshow/the-hive-think-tank-the-microsoft-big-data-stack-by-raghu-ramakrishnan-cto-for-data-microsoft/62437561 HiveData@slideshare.net(HiveData) The Hive Think Tank - The Microsoft Big Data Stack by Raghu Ramakrishnan, CTO for Data, Microsoft HiveData Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation. Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit. While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/microsoft-data-services-2016-160526172350-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Until recently, data was gathered for well-defined objectives such as auditing, forensics, reporting and line-of-business operations; now, exploratory and predictive analysis is becoming ubiquitous, and the default increasingly is to capture and store any and all data, in anticipation of potential future strategic value. These differences in data heterogeneity, scale and usage are leading to a new generation of data management and analytic systems, where the emphasis is on supporting a wide range of very large datasets that are stored uniformly and analyzed seamlessly using whatever techniques are most appropriate, including traditional tools like SQL and BI and newer tools, e.g., for machine learning and stream analytics. These new systems are necessarily based on scale-out architectures for both storage and computation. Hadoop has become a key building block in the new generation of scale-out systems. On the storage side, HDFS has provided a cost-effective and scalable substrate for storing large heterogeneous datasets. However, as key customer and systems touch points are instrumented to log data, and Internet of Things applications become common, data in the enterprise is growing at a staggering pace, and the need to leverage different storage tiers (ranging from tape to main memory) is posing new challenges, leading to caching technologies, such as Spark. On the analytics side, the emergence of resource managers such as YARN has opened the door for analytics tools to bypass the Map-Reduce layer and directly exploit shared system resources while computing close to data copies. This trend is especially significant for iterative computations such as graph analytics and machine learning, for which Map-Reduce is widely recognized to be a poor fit. While Hadoop is widely recognized and used externally, Microsoft has long been at the forefront of Big Data analytics, with Cosmos and Scope supporting all internal customers. These internal services are a key part of our strategy going forward, and are enabling new state of the art external-facing services such as Azure Data Lake and more. I will examine these trends, and ground the talk by discussing the Microsoft Big Data stack.
The Hive Think Tank - The Microsoft Big Data Stack by Raghu Ramakrishnan, CTO for Data, Microsoft from The Hive
]]> 2575 18 https://cdn.slidesharecdn.com/ss_thumbnails/microsoft-data-services-2016-160526172350-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-HiveData-48x48.jpg?cb=1526416450 The Hive(www.hivedata.com) is aventure fund &co-creation studiobased in Palo Alto, CA to co-create startups focused onAI-powered applications in the enterprise.The Hive works actively with founders to help them create, fund and launch data-driven startups. The Hive hasdeep domain expertisein AI. The Hive startups focus on AI and data-driven applications that disruptexisting markets and enable new opportunities.The Hive team consists of successfulcompany-builders, serial entrepreneurs and investors who have created market-leading companies with several billion dollars in exits. www.hivedata.com https://cdn.slidesharecdn.com/ss_thumbnails/charliemuirheadceocognitionxhivesummitmay2018responsibleaiaukperspective-180519010957-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/responsible-ai-by-charlie-muirhead/97566603 &quot;Responsible AI&quot;, by C... https://cdn.slidesharecdn.com/ss_thumbnails/201804hive2-180515210123-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/translating-a-trillion-points-of-data-into-therapies-diagnostics-and-new-insights-into-disease-by-atul-butte/97216217 Translating a Trillion... https://cdn.slidesharecdn.com/ss_thumbnails/digtwinsthehivepresentationpdf-180329171710-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/digital-transformation-digital-twins-for-delivering-business-value-in-iiot/92338901 Digital Transformation...