It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
This session is based on my research and experiments in Prompt Engineering and is 100% relevant for cloud developers who investigate adding some LLM-powered features to their solutions. It's a guide to building proper prompts for AI to get desired results fast and cost-efficient.
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Episode 2: The LLM / GPT / AI Prompt / Data Engineer RoadmapAnant Corporation
In this episode we'll discuss the different flavors of prompt engineering in the LLM/GPT space. According to your skill level you should be able to pick up at any of the following:
Leveling up with GPT
1: Use ChatGPT / GPT Powered Apps
2: Become a Prompt Engineer on ChatGPT/GPT
3: Use GPT API with NoCode Automation, App Builders
4: Create Workflows to Automate Tasks with NoCode
5: Use GPT API with Code, make your own APIs
6: Create Workflows to Automate Tasks with Code
7: Use GPT API with your Data / a Framework
8: Use GPT API with your Data / a Framework to Make your own APIs
9: Create Workflows to Automate Tasks with your Data /a Framework
10: Use Another LLM API other than GPT (Cohere, HuggingFace)
11: Use open source LLM models on your computer
12: Finetune / Build your own models
Series: Using AI / ChatGPT at Work - GPT Automation
Are you a small business owner or web developer interested in leveraging the power of GPT (Generative Pretrained Transformer) technology to enhance your business processes?
If so, Join us for a series of events focused on using GPT in business. Whether you're a small business owner or a web developer, you'll learn how to leverage GPT to improve your workflow and provide better services to your customers.
Dive into the world of GPT-4, the state-of-the-art AI language model by OpenAI. Learn how to craft effective prompts and unlock the full potential of GPT-4 for a wide range of applications, including content generation.
Keywords:
GPT-4, OpenAI, artificial intelligence, language model, prompting, content generation, machine learning, natural language processing, NLP, deep learning, tokenization, context window, prompt engineering, reinforcement learning, fine-tuning, response quality, API, zero-shot learning, few-shot learning, AI ethics, use cases, best practices, performance optimization, transformer architecture, AI-powered solutions.
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Episode 2: The LLM / GPT / AI Prompt / Data Engineer RoadmapAnant Corporation
In this episode we'll discuss the different flavors of prompt engineering in the LLM/GPT space. According to your skill level you should be able to pick up at any of the following:
Leveling up with GPT
1: Use ChatGPT / GPT Powered Apps
2: Become a Prompt Engineer on ChatGPT/GPT
3: Use GPT API with NoCode Automation, App Builders
4: Create Workflows to Automate Tasks with NoCode
5: Use GPT API with Code, make your own APIs
6: Create Workflows to Automate Tasks with Code
7: Use GPT API with your Data / a Framework
8: Use GPT API with your Data / a Framework to Make your own APIs
9: Create Workflows to Automate Tasks with your Data /a Framework
10: Use Another LLM API other than GPT (Cohere, HuggingFace)
11: Use open source LLM models on your computer
12: Finetune / Build your own models
Series: Using AI / ChatGPT at Work - GPT Automation
Are you a small business owner or web developer interested in leveraging the power of GPT (Generative Pretrained Transformer) technology to enhance your business processes?
If so, Join us for a series of events focused on using GPT in business. Whether you're a small business owner or a web developer, you'll learn how to leverage GPT to improve your workflow and provide better services to your customers.
Dive into the world of GPT-4, the state-of-the-art AI language model by OpenAI. Learn how to craft effective prompts and unlock the full potential of GPT-4 for a wide range of applications, including content generation.
Keywords:
GPT-4, OpenAI, artificial intelligence, language model, prompting, content generation, machine learning, natural language processing, NLP, deep learning, tokenization, context window, prompt engineering, reinforcement learning, fine-tuning, response quality, API, zero-shot learning, few-shot learning, AI ethics, use cases, best practices, performance optimization, transformer architecture, AI-powered solutions.
Seminar on ChatGPT Large Language Model by Abhilash Majumder(Intel)
This presentation is solely for reading purposes and contains technical details about ChatGPT fundamentals
If you are considering using either language model, but aren’t quite sure which one’s the best fit for your intended purpose, read on for a ChatGPT vs. GPT-3 head-to-head comparison where we evaluate every aspect of the language models, right from their emergence, how they work, and their suitability in different applications.
This is a collection of prompt examples to be used with the ChatGPT model.
The ChatGPT model is a large language model trained by OpenAI that is capable of generating human-like text. By providing it with a prompt, it can generate responses that continue the conversation or expand on the given prompt.
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
This was the training session follow up to the general talk on ChatGPT. This talk has a bit more detail on prompt writing along with the power and limitations of ChatGPT for Marketing.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
What exactly is ChatGPT? ChatGPT is an open-source ChatGPT framework that allows developers to build their own ChatGPT using pre-built modules. The framework is built using NodeJS, AngularJS, ExpressJS, MongoDB, Redis, and Docker.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Prompt Engineering - an Art, a Science, or your next Job Title?Maxim Salnikov
It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
Prompt Engineering - an Art, a Science, or your next Job Title?Maxim Salnikov
It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
This session is based on my research and experiments in Prompt Engineering and is 100% relevant for cloud developers who investigate adding some LLM-powered features to their solutions. It's a guide to building proper prompts for AI to get desired results fast and cost-efficient.
Seminar on ChatGPT Large Language Model by Abhilash Majumder(Intel)
This presentation is solely for reading purposes and contains technical details about ChatGPT fundamentals
If you are considering using either language model, but aren’t quite sure which one’s the best fit for your intended purpose, read on for a ChatGPT vs. GPT-3 head-to-head comparison where we evaluate every aspect of the language models, right from their emergence, how they work, and their suitability in different applications.
This is a collection of prompt examples to be used with the ChatGPT model.
The ChatGPT model is a large language model trained by OpenAI that is capable of generating human-like text. By providing it with a prompt, it can generate responses that continue the conversation or expand on the given prompt.
Generative AI: Past, Present, and Future – A Practitioner's PerspectiveHuahai Yang
Generative AI: Past, Present, and Future – A Practitioner's Perspective
As the academic realm grapples with the profound implications of generative AI
and related applications like ChatGPT, I will present a grounded view from my
experience as a practitioner. Starting with the origins of neural networks in
the fields of logic, psychology, and computer science, I trace its history and
align it within the wider context of the pursuit of artificial intelligence.
This perspective will also draw parallels with historical developments in
psychology. Against this backdrop, I chart a proposed trajectory for the future.
Finally, I provide actionable insights for both academics and enterprising
individuals in the field.
This was the training session follow up to the general talk on ChatGPT. This talk has a bit more detail on prompt writing along with the power and limitations of ChatGPT for Marketing.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
What exactly is ChatGPT? ChatGPT is an open-source ChatGPT framework that allows developers to build their own ChatGPT using pre-built modules. The framework is built using NodeJS, AngularJS, ExpressJS, MongoDB, Redis, and Docker.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Prompt Engineering - an Art, a Science, or your next Job Title?Maxim Salnikov
It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
Prompt Engineering - an Art, a Science, or your next Job Title?Maxim Salnikov
It's quite ironic that to interact with the most advanced AI in our history - Large Language Models: ChatGPT, etc. - we must use human language, not programming one. But how to get the most out of this dialogue i.e. how to create robust and efficient prompts so AI returns exactly what's needed for your solution on the first try? After my session, you can add the Junior (at least) Prompt Engineer skill to your CV: I will introduce Prompt Engineering as an emerging discipline with its own methodologies, tools, and best practices. Expect lots of examples that will help you to write ideal prompts for all occasions.
This session is based on my research and experiments in Prompt Engineering and is 100% relevant for cloud developers who investigate adding some LLM-powered features to their solutions. It's a guide to building proper prompts for AI to get desired results fast and cost-efficient.
For more course tutorials visit
www.tutorialrank.com
ECO 365 Week 1 Apply: The Fundamentals of Economics Homework
Review the Week 1 The Fundamentals of Economics Quiz in preparation for this assignment.
Complete the Week 1 The Fundamentals of Economics Homework in McGraw-Hill Connect®. These are
For more classes visit
www.snaptutorial.com
ECO 365 Week 1 Practice The Fundamentals of Economic Quiz
Complete the Week 1 The Fundamentals of Economics Quiz in McGraw-Hill Connect®. These are randomized questions.
Note: You have unlimited attempts available to complete practice
3
Environmental Impact:
The Big Picture
The planet’s population is now approaching 7 billion—an increase ofabout 5 billion people in just the past five decades—and the total pop-ulation is likely to increase by another 1 billion people in the next
decade. Analysts now expect that the ranks of the middle class (people who
may want your products!) will swell by as many as 1.8 billion in the next 12
years.1
You’ve probably seen similar projections, and even though you know
intellectually that an extra couple of billion people represents a sustainabil-
ity challenge, it can be hard to relate those huge numbers to your job. So, to
make the scale more real, let’s work through what it would mean to give the
next 1 billion middle-class citizens of the world a single 60-watt incandes-
cent light bulb.
Each bulb weighs about 0.7 ounce, including the packaging, so a billion of
them weigh around 20,000 metric tons, or about the same as 15,000 Toyota
Prius cars. As an engineer, you know that multiplying anything by 109 makes
a big number, but even from this simple case you start to get a feel for how
dramatic the scale is in real-world terms.
Next, let’s turn on those light bulbs. If they’re all on at the same time, they
would consume 60,000 megawatts of electricity—and that would require 120
new 500-megawatt power plants to keep them burning. Luckily, our imagi-
nary middle-class consumers will use their light bulbs only four hours per
day, so we’re down to 10,000 megawatts at any given moment. However, that
means we’ll still need 20 new 500-megawatt power plants. If coal-fired, each
of those plants burns 1.43 million tons of coal per year.2
That doesn’t sound like a good idea from an eco perspective, so let’s try
solar power for our light bulbs. If we use current commercially available solar
31
technology, we’ll need roughly 50 square kilometers of solar panels, or more
than one-third the land area of either San Francisco or Boston. Hmmm. So,
let’s try wind power instead… We’ll still need one-tenth of all the wind power
produced in the world in 2007, just to keep those new light bulbs on for a few
hours a day.
This is the scale we’re dealing with when we’re talking about a billion con-
sumers of any product or service. Thousands or millions of tons of material.
Thousands or millions of megawatts. And it keeps going. Think about the raw
materials consumed to make those light bulbs, the energy consumed by com-
muting factory workers, the packaging materials, the ships and trucks used
for distribution, and ultimately, the waste that is involved when we have a
billion light bulbs. And if we’re having trouble delivering a single light bulb
to a billion people sustainably, what happens when these billion people want
stoves, refrigerators, TVs, computers, cell phones, radios, and cars? What hap-
pens when they want street lights, low-cost air travel, hotels, and restaurants?
You get the idea.
As engineers, we are already challenged by the environmen.
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Session Overview
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I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf
Prompt Engineering - an Art, a Science, or your next Job Title?
1. Prompt Engineering -
an Art, a Science, or
your next Job Title?
Maxim Salnikov
Developer Productivity Lead
Microsoft
2. • Building on web platform since 90s
• Organizing developer communities and technical conferences
• Speaking, training, blogging: Webdev, Cloud, OpenAI
Helping developers to succeed with the Cloud & AI technology
I’m Maxim Salnikov
3. • Generative AI’s impact on productivity could add up to
$4.4 trillion annually in value to the global economy.
• About 75% of the value that generative AI use cases
could deliver falls across customer
operations, marketing, sales, software engineering,
and R&D .
• Generative AI can revolutionize work by automating a
significant portion of employees' activities, up to 60-
70% of their current workload. This augmentation of
individual capabilities has the potential to transform
the way we work.
4. Artificial Intelligence
1956
Artificial Intelligence
The field of computer science that seeks to create
intelligent machines that can replicate or exceed
human intelligence
Machine Learning
1997
Machine Learning
Subset of AI that enables machines to learn from
existing data and improve upon that data to make
decisions or predictions
Deep Learning
2017
Deep Learning
A machine learning technique in which layers of neural
networks are used to process data and make decisions
Generative AI
2021
Generative AI powered by foundation
models
Create new written, visual, and auditory content given
prompts or existing data
5. Path to impact and usecases
Source: IDC, IDC PlanScape: Developing Your Path to Impact with Generative AI, #US51157323
8. Prompt Engineering
Process of designing, refining, and
optimizing input prompts to guide a
model toward producing more accurate
outputs while keeping cost efficiency
9. Prompt anatomy
<
Write a product launch email for new headphones.
This product is AI-powered and priced at $79.99.
The tone is friendly and exciting.
Output as a JSON object with "subject" and "body" fields.
Example:
{
"subject": "Introducing Our New AI-Powered Headphones!",
"body": "We are thrilled to announce the launch of our new AI-
powered headphones"
}
Output:
Instruction
Input data
Context
Target format
Example
Cue
<
11. Prompts and cost efficiency
• Prompt and completion length
• Number of API calls in production
• Number of API calls during development
(experimentation stage)
• Type of deployed model
Model selection strategy: Start with heaviest models and gradually ramp down to cheaper ones
while the result is satisfactory
12. •
• Tokens can sometimes be counter-intuitive
• Tabular data is space-efficient
Space efficiency
14. Technical recommendations
• Start with clear instructions and repeat the
instructions at the end
• Add clear syntax: headers, separators
• Break the task down
• Adjust parameters: Temperature and Top
probabilities
15. Zero-shot VS few-shot prompts
Zero-shot
The model predicts the answer given only a natural language description
of the task.
Few-shot
In addition to the task description, the model sees a few examples of the
task.
Customer question: Hi there, do you know how to choose
flood insurance?
Classified topic: 2
Customer question: Hi there, I have a question on my auto insurance.
Classified topic: 1
Classify customer's question. Classify between category 1 to 3.
Detailed guidelines for how to choose:
choose 1 if the question is about auto insurance.
choose 2 if the question is about home flood insurance.
choose 3 if the question is not relevant to insurance.
Classify customer's question. Classify between category 1 to 3.
Detailed guidelines for how to choose:
choose 1 if the question is about auto insurance.
choose 2 if the question is about home flood insurance.
choose 3 if the question is not relevant to insurance.
Customer question: {insert new question here}
Classified topic:
Customer question: What packages do you have in auto insurance?
Classified topic:
16. Zero Shot - Reasoning
Before
What is the annual water demand of a single-family
household containing four people who are at home an
average of 200 days per year and use an average of 100
liters of water per day?
The annual water demand of a single-family household
containing four people who are at home an average of
200 days per year and use an average of 100 liters of
water per day is 8,000,000 liters per year.
After
What is the annual water demand of a single-family
household containing four people who are at home an
average of 200 days per year and use an average of 100
liters of water per day?
Let’s think step by step and explain the calculation
step by step.
Step 1: Calculate the total number of days in a year:
There are 365 days in a year.
Step 2: Calculate the total number of days the family is at home:
The family is at home an average of 200 days per year.
Step 3: Calculate the total water demand of the family:
The family uses an average of 100 liters of water per day. Therefore, the total water
demand of the family is 100 liters x 200 days = 20,000 liters per year.
Step 4: Calculate the annual water demand of the single-family household:
The annual water demand of the single-family household is 20,000 liters per year.
17. Few Shot Reasoning – Example 1
1st prompt
Roger has 5 tennis balls. He buys 2 more cans of tennis
balls. Each can has 3 tennis balls. How many tennis balls
does he have now?
Answer: The answer is 11.
The cafeteria has 23 apples. If they used 20 to make lunch
and bought 6 more, how many do they have?
The answer is 27
2nd prompt—provide reasoning
Roger has 5 tennis balls. He buys 2 more cans of tennis
balls. Each can has 3 tennis balls. How many tennis balls
does he have now?
Answer: Roger started with 5 balls. 2 cans of 3 tennis balls
each is 6 tennis balls. 5+6 = 11. The answer is 11.
The cafeteria has 23 apples. If they used 20 to make lunch
and bought 6 more, how many do they have?
The cafeteria had 23 apples originally. They used 20 to
make lunch. So they had 23-20 = 3. They bought 6
more apples, so they have 3 + 6 = 9. The answer is 9.
18. Prompt Chaining
Entity Extraction
Please extract entities from the
following news article: 'The new
iPhone model is set to be released
next month. It has been highly
anticipated by Apple fans and is
expected to feature a larger screen
and improved camera
{'text': 'iPhone', 'type’:
'PRODUCT'}, {'text': 'Apple’,
'type': 'ORGANIZATION'}]
Summarization
Please summarize the information
about the product
[{'text': 'iPhone', 'type': 'PRODUCT'},
{'text': 'Apple', 'type':
'ORGANIZATION’}]
The iPhone is a line of smartphones
designed and marketed by Apple
Inc. These devices combine a
computer, camera, and internet
connectivity in a single device, and
are known for their sleek design and
user-friendly interface.
Sentiment Analysis
Please provide a sentiment for the
following text:
The iPhone is a line of smartphones
designed and marketed by Apple
Inc. These devices combine a
computer, camera, and internet
connectivity in a single device,
and are known for their sleek
design and user-friendly interface.
Positive
19. Few Shot Reasoning – Example 2
1st prompt—Reason Extraction
On average Joe throws 25 punches per minute.
A fight lasts 5 rounds of 3 minutes. How many
punches did he throw?
Let’s think step by step and explain the calculation
step by step.
In one minute, Joe throws 25 punches.
In three minutes, Joe throws 3 * 25 = 75 punches.
In five rounds, Joe throws 5*75 = 375 punches.
2nd prompt—Answer Extraction
One average Joe throws 25 punches per minute.
A fight lasts 5 rounds of 3 minutes. How many
punches did he throw?
In one minute, Joe throws 25 punches.
In three minutes, Joe throws 3 * 25 = 75 punches.
In five rounds, Joe throws 5*75 = 375 punches.
The cafeteria has 23 apples. If they used 20 to make lunch
and bought 6 more, how many do they have?
Therefore, the answer (Arabic numerals) is
The cafeteria had 23 apples originally. They used 20
to make lunch. So they had 23-20 = 3. They bought 6
more apples, so they have 3 + 6 = 9. The answer is 9.
20. Prompt Chunking (token limit)
Large Text
Beyond
Token
Limit
Chunks
Please summarize and extract topic: Global warming refers to
the gradual increase in the overall temperature of the Earth's
atmosphere, primarily caused by the burning of fossil fuels
such as coal, oil, and natural gas. This burning releases
carbon dioxide and other greenhouse gases into the
atmosphere, which trap heat and cause the Earth's
temperature to rise.
Climate change is a pressing issue that needs to be addressed
immediately. Governments around the world need to take
immediate action to reduce carbon emissions and invest in
renewable energy sources. Failure to do so will have dire
consequences for future generations
The text is discussing global warming, which is the gradual increase in
the overall temperature of the Earth's atmosphere caused by the
burning of fossil fuels. This burning releases greenhouse gases, such as
carbon dioxide, into the atmosphere which trap heat and cause the
temperature to rise. The text also highlights the urgency of the issue of
climate change and the need for governments to take action to reduce
carbon emissions and invest in renewable energy sources. Failure to
address this issue will have negative consequences for future
generations.
Topic: Climate change and Global warming.
Continue to
next prompt
Please summarize the following text:
'Climate change is a pressing issue that
needs to be addressed immediately. The
increasing levels of carbon dioxide in the
atmosphere are causing the Earth's
temperature to rise, which is leading to
more frequent and severe natural disasters.
Governments around the world need to take
immediate action to reduce carbon
emissions and invest in renewable energy
sources. Failure to do so will have dire
consequences for future generations'"
Climate change is a pressing issue that needs to
be addressed immediately. Governments
around the world need to take immediate
action to reduce carbon emissions and invest in
renewable energy sources. Failure to do so will
have dire consequences for future generations
Then all summaries are passed to GPT again to
summarize, i.e. second round of summarization. The sum
of the summaries has to fit within the token limit.
21. Retrieval Augmented Generation (RAG)
Extract precise answers from your unstructured documents with Azure OpenAI + Cognitive Search: article + repo
https://learn.microsoft.com/en-us/azure/search/retrieval-augmented-generation-overview
23. App or
Copilot agent
API & SDK
Azure OpenAI
Service on your data
Data Sources
(search, files, databases, storage etc.)
Additional 3P Data Sources
(files, databases, storage data etc.)
Recently Announced
Azure OpenAI Service
on your data
https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data
25. Prompt Flow – streamline dev cycle of LLM-based apps
https://github.com/microsoft/promptflow
26. Learning resources
• Learn Prompting Community
• Prompting Guide by DAIR.AI
• Prompt Engineering for the developers on Deep Learning
• Prompt Examples on OpenAI
• Introduction to Prompt Engineering on Microsoft Learn