This document provides an introduction to macroeconomics and defines key macroeconomic concepts. It begins by explaining that economics means "home management" and deals with how societies tackle unlimited wants with limited resources. It then outlines the three main economic questions of what, how, and for whom to produce. The document defines macroeconomics as studying whole economies and their aggregates, while microeconomics focuses on individual agents. It also distinguishes between positive and normative economics. Finally, it thoroughly explains gross domestic product (GDP) as a measure of total output and income, breaking down GDP into consumption, investment, government purchases, and net exports.
Measuring a nations Income
GDP
Real GDP
Nominal GDP
Circular Flow Diagram
Components of GDP
The GDP Deflator
Why Do We Care About GDP?
GDP Does Not Value:
Measuring a nations Income
GDP
Real GDP
Nominal GDP
Circular Flow Diagram
Components of GDP
The GDP Deflator
Why Do We Care About GDP?
GDP Does Not Value:
This is intended to develop uses understanding of the family as an economic unit. It will examine the family’s goal of improving its standard of living and the economic decisions the family makes to improve its well-being.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
29. ACTIVE LEARNING 1
GDP and its components
In each of the following cases, determine how much
GDP and each of its components is affected (if at all).
A. Debbie spends $200 to buy her husband a dinner
at the finest restaurant in New York.
B. Sarah spends $1800 on a new laptop to use in her
publishing business. The laptop was built in China.
C. Jane spends $1200 on a computer to use in her
editing business. She got last year’s model on sale
for a great price from a local manufacturer.
D. General Motors builds $500 million worth of cars,
30. ACTIVE LEARNING 1
Answers
A. Debbie spends $200 to buy her husband a dinner
at the finest restaurant in New York.
Consumption and GDP rise by $200.
B. Sarah spends $1800 on a new laptop to use in
her publishing business. The laptop was built in
China.
Investment rises by $1800, net exports fall
by $1800, GDP is unchanged.
30
31. ACTIVE LEARNING 1
Answers
C. Jane spends $1200 on a computer to use in her
editing business. She got last year’s model on
sale for a great price from a local manufacturer.
Current GDP and investment do not change,
because the computer was built last year.
D. General Motors builds $500 million worth of cars,
but consumers only buy $470 million of them.
Consumption rises by $470 million,
inventory investment rises by $30 million,
and GDP rises by $500 million.
31
46. ACTIVE LEARNING 2
Computing GDP
2007 (base yr)
P
Good A
Good B
$30
$100
Q
2008
P
2009
Q
900
$31 1,000
192 $102
200
P
Q
$36
$100
1050
205
Use the above data to solve these problems:
A. Compute nominal GDP in 2007.
B. Compute real GDP in 2008.
C. Compute the GDP deflator in 2009.
46
47. ACTIVE LEARNING 2
Answers
2007 (base yr)
P
Good A
Good B
$30
$100
Q
2008
P
2009
Q
900
$31 1,000
192 $102
200
P
Q
$36
$100
1050
205
A. Compute nominal GDP in 2007.
$30 x 900 + $100 x 192 = $46,200
B. Compute real GDP in 2008.
$30 x 1000 + $100 x 200 = $50,000
47
48. ACTIVE LEARNING 2
Answers
2007 (base yr)
P
Good A
Good B
Q
$30
$100
2008
P
2009
Q
900
$31 1,000
192 $102
200
P
Q
$36
$100
1050
205
C. Compute the GDP deflator in 2009.
Nom GDP = $36 x 1050 + $100 x 205 = $58,300
Real GDP = $30 x 1050 + $100 x 205 = $52,000
GDP deflator = 100 x (Nom GDP)/(Real GDP)
= 100 x ($58,300)/($52,000) = 112.1
48
Why do economists disagree even over positive theories?
Economics is a social science, like psychology, anthropology, and political science. It is concerned with reaching generalizations about human behavior. Human behavior is more variable and often difficult to predict. But, probably more important, humans too often can’t explain their true motivations. Economics assumes people are rational self-interest maximizers. All that we can really claim is that people act as if they are rational.
Social scientists don’t have laboratories to conduct controlled repeatable experiments to test theories like physical scientists. We can’t manipulate the economy simply to test our theories
Suggestion: Show these questions, and give your students 1-3 minutes to formulate their answers. When you are ready to discuss the answers, go to the next slide….
Suggestion (continued from previous slide): Show part A (but not the answer) and ask for someone to volunteer his or her response. Then show the answer to part A. Repeat for parts B, C, and D. (The answers to parts C and D appear on the following slide.)
After showing the answer to part A, ask your students whether the answer would be different if Debbie were a government employee. The correct answer is NO. Government employees engage in consumption, just like everyone else.
Regarding part C:
Jane’s purchase causes investment (for her own business) to increase by $1200. However, the computer is sold out of inventory, so inventory investment falls by $1200. The two transactions cancel each other, leaving aggregate investment and GDP unchanged.
Regarding part D:
This problem illustrates why expenditure always equals output, even when firms don’t sell everything they produce due to lackluster demand. The point here is that unsold output is counted in inventory investment, even when that “investment” was unintentional.
This example is similar to that in the text, but using different goods and different numerical values.
Suggestion: Ask your students to compute nominal GDP in each year before revealing the answers. Ask them to compute the rate of increase before revealing the answers.
In this example, nominal GDP grows for two reasons: prices are rising, and the economy is producing a larger quantity of goods.
Thinking of nominal GDP as total income, the increases in income will overstate the increases in society’s well-being because part of these increases are due to inflation.
We need a way to take out the effects of inflation, to see how much people’s incomes are growing in purchasing power terms. That is the job of real GDP.
This example shows that real GDP in every year is constructed using the prices of the base year and that the base year doesn’t change.
The growth rate of real GDP from one year to the next is the answer to this question:
“How much would GDP (and hence everyone’s income) have grown if there had been zero inflation?”
Thus, real GDP is corrected for inflation.
The table in the top half of this slide merely summarizes the answers from the previous two slides. This table will be used shortly to compute the growth rates in nominal and real GDP and to compute the GDP deflator and inflation rates.
Again, the growth rate of real GDP from one year to the next is the answer to this question:
“How much would GDP (and hence everyone’s income) have grown if there had been zero inflation?”
This is why real GDP is corrected for inflation.
The data in the table are for a hypothetical economy that produces two final goods, A and B. For all parts of this problem, use 2007 as the base year.
If you’re running short on time, you can skip part A – it’s the least challenging. If you only have time for one of the three, you might skip A and B, as C by itself covers all of the material: it requires students to compute nominal and real GDP before they can compute the GDP deflator.