Preparing the next generation for the cognitive eraSteven Miller
Short version of my latest presentation used during a panel session at the ASA Research Symposium at Southern Illinois University Carbondale on November 21st 2015
Digital transformation - decoding the industrial 4.0 revolutionAnnamaria Porzioli
What is digital trasformation ? What is the impact on companies and what does it mean for employees ? Discover it in the presentation I did in Bocconi University on Sept. 13th 2016
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
Preparing the next generation for the cognitive eraSteven Miller
Short version of my latest presentation used during a panel session at the ASA Research Symposium at Southern Illinois University Carbondale on November 21st 2015
Digital transformation - decoding the industrial 4.0 revolutionAnnamaria Porzioli
What is digital trasformation ? What is the impact on companies and what does it mean for employees ? Discover it in the presentation I did in Bocconi University on Sept. 13th 2016
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
The workshop - 'AI transforming Business' is conducted on 20-21st Feb 2019 at Chennai hosted by CII.in (Confederation of Indian Industry) for top Indian executives.
This is a 2-day full-time workshop focused on coaching delegates on Artificial Intelligence(AI), Transforming business with AI, AI Data Strategy and best practices from organizations leading AI adoption across the world.
Delegates attended include Ex-CEO and Vice Chair of Cognizant Mr. Lakshmi Narayanan, CEO and MD of Ameex, AVP of Infosys, MD and CEO Rane Group, Sr. General Manager of Blue Star, Joint General Manager of L&T and 30 more delegates from top management from manufacturing, agriculture banking, and healthcare.
Speaker: Ashok Kumar - AI Evangelist, Entrepreneur, Executives Coach, Ph.D. Scholar, MBA
Organizations today have lots and lots of data. Typically when it comes to data analysis we have to know what our measures of success are before we design our BI. These are typically manifested by competency, or domain driven KPI's but what if those metrics don't actually measure success at all? In this talk we will be discussing how to leverage azure machine learning to answer questions in your organization about success and how to find the KPI's that really matter and drive results.
In this session we'll dive into the journey that Google chooses to take in order focus on AI: what was the mindset, what were the challenges and what is the direction for the future.
How is Big Content Different From Big Data?John Mancini
Moving the Mountain -- Evanta CIO Presentation on Big Data and Big Content -- central premise -- Big Data analysis without a strategy for the Content that usually fulfills the analytics is a waste of time.
Is IT Really the Villain? - Future of Technology in the EnterpriseJohn Mancini
Is IT the Villain? - The Future of Technology in the Enterprise -- A summary of my keynote presentation at the CITE Conference and Expo in San Francisco. How do organizations deal with the advantages of social, mobile, and consumer technologies without losing control?
A presentation given to the University of Central Florida Dept Industrial Organizational Psychology, on Jan 12th, 2018. Covers the what why and how of AI, machine learning, Deep Learning and its coming impact to Transportation, healthcare, and use all.
Smart Data Slides: Modern AI and Cognitive Computing - Boundaries and Opportu...DATAVERSITY
We will kickoff the 2017 series with an overview of the current state of commercial artificial intelligence (AI) and cognitive computing. The research and commercial communities are far from consensus on a few important definitions, so we will start with two that are critical to our understanding and analysis.
#ModernAI applies research from computer science, psychology, mathematics, linguistics and neuroscience to develop problem-solving applications that supplant or augment human intellectual performance. Unlike more traditional AI R&D, #ModernAI typically leverages machine learning and big data.
Cognitive computing is a problem-solving approach based on #ModernAI that focuses on processes for understanding, reasoning, learning and planning.
In this webinar, we will present a framework for analyzing modern AI/cognitive computing tools and technologies, with an emphasis on the risks and reward of adopting them at varying stages of maturity.
Explore our analysis of technology trends for 2019 and beyond: AI, IoT, Security, Big Data / Data Science, Mobile Apps Development, AR/VR, RPA (Robot Process Automation), Blockchain, Automotive Solutions, Business Intelligence, Cloud Computing, Service Desk, Autonomous Things, Augmented Analytics, AI-Driven Development, Digital Twins, Empowered Edge, Immersive Experience, Smart Spaces, Quantum Computing, and more.
Check our recommendations for businesses to stay current with the latest IT tendencies.
Includes a video by Gartner.
The Rise of the Machines: Understanding How Data Accelerates AIVolker Hirsch
These are my slides to a keynote I gave at the annual conference of the Association of Learned and Professional Society Publishers (ALPSP) in Noordwijk, Netherlands on 15 September 2017. They look at how data (and the increase of data sources we create) helps accelerate the power of AI.
They didn't shoot video but the audio is here: https://www.alpsp.org/write/MediaUploads/Conference/1709AIC/Audio/Plenary_5_-_Volker_Hirsch.mp3
Paperspace is the cloud AI-platform built for the future. Tens of thousands of individuals, startups and enterprises use Paperspace to power a range of next-generation applications. Gradient° by Paperspace is a deep learning platform built for developers. From exploration to production deployment, Gradient° enables individuals and teams to quickly develop and collaborate on deep learning models. Join over a hundred thousand developers on the platform and enjoy 1-click
Jupyter notebooks, prebuilt templates, a python library, and powerful low-cost GPUs.
Big Data Expo 2015 - IBM Outside the comfort zoneBigDataExpo
When it comes to high tech, we tend to wear blinders. We only want to see what's right in front of us. At times, we look forward but we rarely look around us to see how other industries are succeeding. This is especially true with organizations who want to look beyond business intelligence and reveal answers you never thought to ask. For example, what would demand forecasting for a Chief Marketing Officer in Media & Entertainment mean to a Chief Data Officer in banking? Or what would Customer Operations Transformation in Energy & Utilities mean to a Chief Customer Officer at a major retail operation? In this interactive and energetic session, we'll explore valuable cross-industry use cases to help get you "outside your comfort zone" and take a completely different look at how applications of advanced and predictive analytics on big data - or any data - can help you to act on real-time insights to fundamentally transform your business.
The workshop - 'AI transforming Business' is conducted on 20-21st Feb 2019 at Chennai hosted by CII.in (Confederation of Indian Industry) for top Indian executives.
This is a 2-day full-time workshop focused on coaching delegates on Artificial Intelligence(AI), Transforming business with AI, AI Data Strategy and best practices from organizations leading AI adoption across the world.
Delegates attended include Ex-CEO and Vice Chair of Cognizant Mr. Lakshmi Narayanan, CEO and MD of Ameex, AVP of Infosys, MD and CEO Rane Group, Sr. General Manager of Blue Star, Joint General Manager of L&T and 30 more delegates from top management from manufacturing, agriculture banking, and healthcare.
Speaker: Ashok Kumar - AI Evangelist, Entrepreneur, Executives Coach, Ph.D. Scholar, MBA
Organizations today have lots and lots of data. Typically when it comes to data analysis we have to know what our measures of success are before we design our BI. These are typically manifested by competency, or domain driven KPI's but what if those metrics don't actually measure success at all? In this talk we will be discussing how to leverage azure machine learning to answer questions in your organization about success and how to find the KPI's that really matter and drive results.
In this session we'll dive into the journey that Google chooses to take in order focus on AI: what was the mindset, what were the challenges and what is the direction for the future.
How is Big Content Different From Big Data?John Mancini
Moving the Mountain -- Evanta CIO Presentation on Big Data and Big Content -- central premise -- Big Data analysis without a strategy for the Content that usually fulfills the analytics is a waste of time.
Is IT Really the Villain? - Future of Technology in the EnterpriseJohn Mancini
Is IT the Villain? - The Future of Technology in the Enterprise -- A summary of my keynote presentation at the CITE Conference and Expo in San Francisco. How do organizations deal with the advantages of social, mobile, and consumer technologies without losing control?
A presentation given to the University of Central Florida Dept Industrial Organizational Psychology, on Jan 12th, 2018. Covers the what why and how of AI, machine learning, Deep Learning and its coming impact to Transportation, healthcare, and use all.
Smart Data Slides: Modern AI and Cognitive Computing - Boundaries and Opportu...DATAVERSITY
We will kickoff the 2017 series with an overview of the current state of commercial artificial intelligence (AI) and cognitive computing. The research and commercial communities are far from consensus on a few important definitions, so we will start with two that are critical to our understanding and analysis.
#ModernAI applies research from computer science, psychology, mathematics, linguistics and neuroscience to develop problem-solving applications that supplant or augment human intellectual performance. Unlike more traditional AI R&D, #ModernAI typically leverages machine learning and big data.
Cognitive computing is a problem-solving approach based on #ModernAI that focuses on processes for understanding, reasoning, learning and planning.
In this webinar, we will present a framework for analyzing modern AI/cognitive computing tools and technologies, with an emphasis on the risks and reward of adopting them at varying stages of maturity.
Explore our analysis of technology trends for 2019 and beyond: AI, IoT, Security, Big Data / Data Science, Mobile Apps Development, AR/VR, RPA (Robot Process Automation), Blockchain, Automotive Solutions, Business Intelligence, Cloud Computing, Service Desk, Autonomous Things, Augmented Analytics, AI-Driven Development, Digital Twins, Empowered Edge, Immersive Experience, Smart Spaces, Quantum Computing, and more.
Check our recommendations for businesses to stay current with the latest IT tendencies.
Includes a video by Gartner.
The Rise of the Machines: Understanding How Data Accelerates AIVolker Hirsch
These are my slides to a keynote I gave at the annual conference of the Association of Learned and Professional Society Publishers (ALPSP) in Noordwijk, Netherlands on 15 September 2017. They look at how data (and the increase of data sources we create) helps accelerate the power of AI.
They didn't shoot video but the audio is here: https://www.alpsp.org/write/MediaUploads/Conference/1709AIC/Audio/Plenary_5_-_Volker_Hirsch.mp3
Paperspace is the cloud AI-platform built for the future. Tens of thousands of individuals, startups and enterprises use Paperspace to power a range of next-generation applications. Gradient° by Paperspace is a deep learning platform built for developers. From exploration to production deployment, Gradient° enables individuals and teams to quickly develop and collaborate on deep learning models. Join over a hundred thousand developers on the platform and enjoy 1-click
Jupyter notebooks, prebuilt templates, a python library, and powerful low-cost GPUs.
Big Data Expo 2015 - IBM Outside the comfort zoneBigDataExpo
When it comes to high tech, we tend to wear blinders. We only want to see what's right in front of us. At times, we look forward but we rarely look around us to see how other industries are succeeding. This is especially true with organizations who want to look beyond business intelligence and reveal answers you never thought to ask. For example, what would demand forecasting for a Chief Marketing Officer in Media & Entertainment mean to a Chief Data Officer in banking? Or what would Customer Operations Transformation in Energy & Utilities mean to a Chief Customer Officer at a major retail operation? In this interactive and energetic session, we'll explore valuable cross-industry use cases to help get you "outside your comfort zone" and take a completely different look at how applications of advanced and predictive analytics on big data - or any data - can help you to act on real-time insights to fundamentally transform your business.
To gain a current global snapshot of how organizations are using big data and analytics, cloud, mobile, and social technologies, the IBM Center for Applied Insights conducted a survey of 1,447 IT and business decision makers. The research shows that big data and analytics, cloud, mobile, and social are now mainstream, driving strategic opportunities for the enterprise. How are leading companies staying out ahead when everybody is jumping into the fray? Learn about three key characteristics that give them an edge.
To gain a current global snapshot of how organizations are using big data and analytics, cloud, mobile, and social technologies, the IBM Center for Applied Insights conducted a survey of 1,447 IT and business decision makers. The research shows that big data and analytics, cloud, mobile, and social are now mainstream, driving strategic opportunities for the enterprise. How are leading companies staying out ahead when everybody is jumping into the fray? Learn about three key Pacesetters characteristics that give them an edge.
Data and its Role in Your Digital TransformationVMware Tanzu
Data plays a big role in building the kinds of experiences demanded by the market today. In this session, we’ll unpack what goes into building a data-driven app, case studies of how organizations have successfully overcome siloed data and analytics to bring new predictive features into their applications, and what your next steps for data should be on your digital transformation journey.
Speaker: Les Klein, EMEA CTO Data, Pivotal
The Power of 3 - IBM PureApplications, SoftLayer and General Operational Eff...Prolifics
Speakers:
Mike Hastie, Prolifics
Bradley Hertenstein, Prolifics
Join Prolifics as we explore how combining PureApps (Infrastructure Automations), Softlayer (Cloud), and general operational effectiveness (DevOps) to reduce time to delivery, reduce complexity, and reduce cost. This is a birds of a feather interactive discussion but a recorded demo will be used to help level set and get the discussion started.
http://www.prolifics.com
FlockData Overview from Startup Pitch NightFlockData
Presentation from FlockData at DC Tech Startup Pitch Night in July 2015.
Learn how FlockData combines multiple open-source data tools, including graph data, search data and timeline, to help customers solve problems.
Presentation from FlockData at DC Tech Startup Pitch Night in July 2015.
Learn how FlockData combines multiple open-source data tools, including graph data, search data and timeline, to help customers solve problems.
Auto AI : AI used to create AI applicationsKaran Sachdeva
Building AI applications is a very complex process involving steps and workflows which are becoming more complex every other day. Its a circle since the AI application is nothing but a feedback loop between various steps involving data. Consider the below picture a data scientist or ML engineer has to work through. Now my mission as an evangelist of the AI technology who sees a lot of promise in this technology would like to make it simple so we can empower more professionals in the business to become what we call "citizen data scientists". A citizen data scientist is a business person empowered so well that he can combine his domain knowledge with tools an expert data scientist uses in a simplified way. We have seen this impacting customer experience in 5x and revenue increase in the range of 15-20%.
Is it harder to find a taxi when it is raining? Wilfried Hoge
Using open data to answer the question if it is harder to find a taxi, when it is raining. Live demo of analyzing taxi data with DashDB, R, and Bluemix.
Presented on data2day conference.
Role of Data in Digital TransformationVMware Tanzu
Data plays a big role in building the kinds of experiences demanded by the market today. In this session, we’ll unpack what goes into building a data-driven app, case studies of how organizations have successfully overcome siloed data and analytics to bring new predictive features into their applications, and what your next steps for data should be on your digital transformation journey.
Speaker: Les Klein, EMEA CTO Data, Pivotal
Systems of Engagement offer much value to industry & government alike but care needs to be taken in how they are protected against cyber attack. In this presentation I explain Systems of Engagement & illustrate the benefits using government case studies. I then discuss the security challenges Systems of Engagement pose and how to address them with commercial software technologies. Finally I look ahead to how to defend Systems of Insight hosted on future generations of cloud technology.
S ba0881 big-data-use-cases-pearson-edge2015-v7Tony Pearson
IBM is a market leader in big data and analytics solutions. This session explains the basics of Big Data, with actual use cases of clients who have benefited from IBM solutions in this space, followed by architectures with IBM BigInsights, BigSQL, Platform Symphony and Spectrum Scale.
An introduction to IBM Data Lake by Mandy Chessell CBE FREng CEng FBCS, Distinguished Engineer & Master Inventor.
Learn more about IBM Data Lake: https://ibm.biz/Bdswi9
Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."