Accelerating Cognitive Business with Hybrid CloudDenny Muktar
IBM Indonesia BusinessConnect Events, March 22nd, 2016.
Disruptors are reinventing business processes and leading their industries with digital transformations. Cognitive Business extends digital business with cognitive computing - both of which exist in and are built using the cloud. This presentation covers an IBM approach of building and starting the Hybrid Cloud Journey.
Best practices in deploying IBM Operation Decision Manager Standard 8.8.0Pierre Feillet
This session was presented at Interconnect 2016 in session bdm-4361. It covers ODM 8.8.0 version. This deck explains the basics of ODM architecture and guides deployment for DevOps.
Accelerating Cognitive Business with Hybrid CloudDenny Muktar
IBM Indonesia BusinessConnect Events, March 22nd, 2016.
Disruptors are reinventing business processes and leading their industries with digital transformations. Cognitive Business extends digital business with cognitive computing - both of which exist in and are built using the cloud. This presentation covers an IBM approach of building and starting the Hybrid Cloud Journey.
Best practices in deploying IBM Operation Decision Manager Standard 8.8.0Pierre Feillet
This session was presented at Interconnect 2016 in session bdm-4361. It covers ODM 8.8.0 version. This deck explains the basics of ODM architecture and guides deployment for DevOps.
Intelligent enterprise: Cognitive Business Presentation from World of WatsonNancy Pearson
How Companies Are Using Cognitive Computing to Drive Tangible Results including information from the 2016 Cognitive Advantage Report: http://www.ibm.com/cognitive/advantage-reports/
The Intelligent Enterprise: How Companies are Using Cognitive Computing to Dr...Susanne Hupfer, Ph.D.
Presented by Susanne Hupfer and Nancy Pearson at IBM World of Watson Conference, Oct. 2016.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
Applying cognitive computing to business operations, transforming front to ba...HfS Research
Ambitious business leaders are reinventing their enterprises digitally with creative strategies, products and customer experiences. Emerging cognitive solutions have the ability to impact business processes in entirely new ways through autonomous decision making and insightful human engagement. However, many business leaders still view cognitive computing as tomorrow’s potential, not necessarily today’s.
In this webinar, experts from HfS Research, IBM, and Waterfund discuss how cognitive platform based solutions and a design-thinking led approach allow for delivering a personalized, end-to-end frictionless experience.
Watch and learn:
Getting real with Cognitive. Real enterprise case examples of cognitive solutions that transform the way Finance, HR and Procurement services operate
How cognitive capabilities and solutions are enhancing IBM clients' BPO services
The role of service delivery to achieve the Intelligent OneOffice
How the next generation of Service Delivery can bring about a frictionless front to back office transformation
Watch the webinar: http://www.hfsresearch.com/pov/hfs-webinar-august-4
Presentation on Bachat Gat (Self Help Groups), how to form a SHG, various avenues etc. This presented was presented before the MMS Students of BGIMS, Mumbai Central.
We interviewed thirty of today's top thinkers in artificial intelligence to get a glimpse of what's coming next - the direction technology and applications will take over the next ten years.
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.
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
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
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
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).
Intelligent enterprise: Cognitive Business Presentation from World of WatsonNancy Pearson
How Companies Are Using Cognitive Computing to Drive Tangible Results including information from the 2016 Cognitive Advantage Report: http://www.ibm.com/cognitive/advantage-reports/
The Intelligent Enterprise: How Companies are Using Cognitive Computing to Dr...Susanne Hupfer, Ph.D.
Presented by Susanne Hupfer and Nancy Pearson at IBM World of Watson Conference, Oct. 2016.
Wondering how and why forward-thinking businesses are already adopting cognitive computing and artificial intelligence technologies? Curious about the top business challenges organizations are tackling with cognitive computing? The "IBM Cognitive Study," which surveyed 600 leaders and decision-makers from around the world, provides answers to these questions and more. About 70% of decision-makers say that cognitive computing is extremely important to their business strategy and success. Learn how smart companies are becoming cognitive businesses, and how they're already driving tangible results and ROI.
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
Applying cognitive computing to business operations, transforming front to ba...HfS Research
Ambitious business leaders are reinventing their enterprises digitally with creative strategies, products and customer experiences. Emerging cognitive solutions have the ability to impact business processes in entirely new ways through autonomous decision making and insightful human engagement. However, many business leaders still view cognitive computing as tomorrow’s potential, not necessarily today’s.
In this webinar, experts from HfS Research, IBM, and Waterfund discuss how cognitive platform based solutions and a design-thinking led approach allow for delivering a personalized, end-to-end frictionless experience.
Watch and learn:
Getting real with Cognitive. Real enterprise case examples of cognitive solutions that transform the way Finance, HR and Procurement services operate
How cognitive capabilities and solutions are enhancing IBM clients' BPO services
The role of service delivery to achieve the Intelligent OneOffice
How the next generation of Service Delivery can bring about a frictionless front to back office transformation
Watch the webinar: http://www.hfsresearch.com/pov/hfs-webinar-august-4
Presentation on Bachat Gat (Self Help Groups), how to form a SHG, various avenues etc. This presented was presented before the MMS Students of BGIMS, Mumbai Central.
We interviewed thirty of today's top thinkers in artificial intelligence to get a glimpse of what's coming next - the direction technology and applications will take over the next ten years.
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.
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
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
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
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).
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
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.
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