Now is the time to unravel the mysteries of cloud computing. The speaker is going to brief about Generative AI in the session that is related to study Jams 2023
Lock in your calendars for October because GDSC GTBIT is about to drop the Google Cloud Jams bomb, and guess what? You're on the VIP list! 🌟🥳 Join us for an electrifying session hosted by tech virtuoso Mukal himself And upskill your learning journey using the Google Skill Boost Portal and conquer those certifications !
Python vs R for Data Science: What’s the Difference? How can they automate?iTrainMalaysia1
Businesses utilizing data to their best advantage remain competitive in the market, keeping them steps ahead from their counterparts, more evidently now when things are forced to move online.
"Embark On a Cloud Odyssey" Cloud Campaign Induction ProgramAnayPund
🌟 "Embark On a Cloud Odyssey"🌟
🌟 GDSC Google Cloud Study Jam 2023 Induction Program 🌟
🚀 Welcome to the Future of Cloud Technology!
Are you ready to embark on an exciting journey into the world of Google Cloud? Join us for the GDSC Google Cloud Study Jam 2023 Induction Program, a thrilling event designed to kickstart your cloud computing adventure.
🎉 Why Attend:
- Explore the cutting-edge technologies powering Google Cloud.
- Build practical skills through guided exercises.
- Boost your resume with valuable cloud computing experience.
- Connect with a dynamic community of tech enthusiasts.
- Win prizes and bragging rights!
🌥️ Cloudy skies are ahead – let's soar together!🚀
LESSON 1: INTRODUCTION TO PYTHON, VARIABLES, DNA CODING, AI
Introduction to Python, how to download (Python 3), Create your own Chat Bot. Introducing variables, sequence, programs, Alan Turing and Artificial Intelligence. Big ideas to discuss: DNA Coding and Intelligent design. Create apps which include the use of random number and item generation. Suggested videos on ‘Introducing Python’ and History of Computing. Learn about Mathematical and comparison operators and the importance of indentation in Python. Includes a suggested videos, ‘Big ideas’ discussion, and HW/research projects section.
Distributed Natural Language Processing Systems in PythonClare Corthell
Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet.
Thinking Machines Conference, Manila, February 2016
http://thinkingmachin.es/events/
Now is the time to unravel the mysteries of cloud computing. The speaker is going to brief about Generative AI in the session that is related to study Jams 2023
Lock in your calendars for October because GDSC GTBIT is about to drop the Google Cloud Jams bomb, and guess what? You're on the VIP list! 🌟🥳 Join us for an electrifying session hosted by tech virtuoso Mukal himself And upskill your learning journey using the Google Skill Boost Portal and conquer those certifications !
Python vs R for Data Science: What’s the Difference? How can they automate?iTrainMalaysia1
Businesses utilizing data to their best advantage remain competitive in the market, keeping them steps ahead from their counterparts, more evidently now when things are forced to move online.
"Embark On a Cloud Odyssey" Cloud Campaign Induction ProgramAnayPund
🌟 "Embark On a Cloud Odyssey"🌟
🌟 GDSC Google Cloud Study Jam 2023 Induction Program 🌟
🚀 Welcome to the Future of Cloud Technology!
Are you ready to embark on an exciting journey into the world of Google Cloud? Join us for the GDSC Google Cloud Study Jam 2023 Induction Program, a thrilling event designed to kickstart your cloud computing adventure.
🎉 Why Attend:
- Explore the cutting-edge technologies powering Google Cloud.
- Build practical skills through guided exercises.
- Boost your resume with valuable cloud computing experience.
- Connect with a dynamic community of tech enthusiasts.
- Win prizes and bragging rights!
🌥️ Cloudy skies are ahead – let's soar together!🚀
LESSON 1: INTRODUCTION TO PYTHON, VARIABLES, DNA CODING, AI
Introduction to Python, how to download (Python 3), Create your own Chat Bot. Introducing variables, sequence, programs, Alan Turing and Artificial Intelligence. Big ideas to discuss: DNA Coding and Intelligent design. Create apps which include the use of random number and item generation. Suggested videos on ‘Introducing Python’ and History of Computing. Learn about Mathematical and comparison operators and the importance of indentation in Python. Includes a suggested videos, ‘Big ideas’ discussion, and HW/research projects section.
Distributed Natural Language Processing Systems in PythonClare Corthell
Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet.
Thinking Machines Conference, Manila, February 2016
http://thinkingmachin.es/events/
Grammarly AI-NLP Club #2 - Recent advances in applied chatbot technology - Jo...Grammarly
Speaker: Jordi Carrera Ventura, Artificial Intelligence technologist at Telefónica R&D
Summary: Chatbots (aka conversational agents, spoken dialogue systems) allow users to interface with computers using natural language by simply asking questions or issuing commands.
Given a query, the chatbot builds a semantic representation of the input, transforms it into a logical statement, and performs all the necessary actions to fulfill the user's intent. Sometimes this simply means calculating an exact answer or retrieving a fact from a database, whereas other times it means building a contextual model and running a full-fledged conversation flow while keeping track of anaphoras and cross-references.
Besides the direct applications of chatbots in IoT (Amazon’s Alexa, Apple's Siri) and IT (the historical field of Information Retrieval as a whole can be seen as a sub-problem of spoken dialogue systems), chatbots' main appeal for technologists is their location at the intersection of all major Natural Language Processing technologies and many of the deepest questions in Cognitive Science today: semantic parsing, entity recognition, knowledge representation, and coreference resolution.
In this talk, I will explore those questions in the context of an applied industry setting, and I will introduce a framework suitable for addressing them, together with an overview of the state-of-the-art in chatbot technology and some original techniques.
Gain a practical understanding of how to integrate AI capabilities into your PHP projects with examples from the leading sources of hosted AI: OpenAI and Hugging Face. Armed with this knowledge, you can unlock new possibilities for intelligent, dynamic, and user-centric PHP applications that leverage the power of Artificial Intelligence.
So, join us for this transformative journey as we bridge the gap between PHP and AI, opening the door to a world of smarter and more innovative web applications.
A lightning talk presentation from Jisc's Focus on the future: new developments in accessible and assistive technologies event held on 16 March 2022 as part of Digifest community fringe.
Speech Recognition: Art of the possible - DigiFest 2022Dominik Lukes
Presentation introducing a panel discussion on the present and future of speech recognition for lecture capture at Digifest 2022 online fringe on Assistive Technologies: https://www.jisc.ac.uk/events/focus-on-the-future-new-developments-in-accessible-and-assistive-technologies-16-mar-2022
Speech Recognition: Art of the possible - DigiFest 2022Dominik Lukes
Presentation introducing a panel discussion on the present and future of speech recognition for lecture capture at Digifest 2022 online fringe on Assistive Technologies: https://www.jisc.ac.uk/events/focus-on-the-future-new-developments-in-accessible-and-assistive-technologies-16-mar-2022
Introduction to Prompt Engineering (Focusing on ChatGPT)Chameera Dedduwage
This is an introductory session on how to engineer prompts for commercially available Large Language Models (LLMs) such as ChatGPT and Gemini. This session uses ChatGPT as the example, but the strategies can be equally applied to Gemini and other LLMs.
Fusing Modeling and Programming into Language-Oriented ProgrammingMarkus Voelter
Modeling in general is of course different from programming (think: climate models). However, when we consider the role of models in the context of “model-driven”, i.e., when they are used to automati- cally construct software, it is much less clear that modeling is different from programming. In this paper, I argue that the two are conceptually indistinguishable, even though in practice they traditionally emphasize different aspects of the (conceptually indistinguishable) common approach. The paper discusses and illustrates language-oriented programming, the approach to {modeling| programming} we have successfully used over the last 7 years to build a range of innovative systems in domains such as insurance, healthcare, tax, engineering and consumer electronics. It relies on domain-specific languages, modular language extension, mixed notations, and in particular, the Jetbrains MPS language workbench.
Building intelligent applications with Large Language ModelsSpeck&Tech
ABSTRACT: Large Language Models (LLMs) have proved extraordinary capabilities in language understanding and generation, but their most promising feature is probably their reasoning capability. The fact that LLMs can understand complex problems, plan step-by-step solutions, and even work by intuition, make them powerful reasoning engine to be placed at the core of AI-powered application. In this session, we are going to explore how LLMs are revolutionizing the world of software development and paving the way for a new landscape for LLM-powered applications.
BIO: I'm Valentina Alto, a Data Science MSc graduate and Cloud Specialist at Microsoft, focusing on Analytics and AI workloads within the manufacturing and pharmaceutical industry since 2022. I've been working on customers' digital transformations, designing cloud architecture and modern data platforms, including IoT, real-time analytics, Machine Learning, and Generative AI. I'm also a tech author, contributing articles on machine learning, AI, and statistics, and I recently published a book on Generative AI and Large Language Models. In my free time, I love hiking and climbing around the beautiful Italian mountains, running, and enjoying a good book with a cup of coffee.
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборотОмские ИТ-субботники
Николай Линкер, Backend-developer, ISS Art
С детства любил математику, это и определило мою профессию. Закончил матфак ОмГУ, уже 16 лет разрабатываю ПО, постоянно ищу новые решения. Довелось поработать с широким диапазоном языков и предметных областей. Детально разбирался с графическими библиотеками, компиляторами и сетевыми протоколами. В докладе расскажу, что заслуживает распространения из Haskell в традиционные языки, вроде Java, и что в Java удалось лучше, чем в Haskell.
[Session #2] Leadership - Team & Event Management (1).pptxAshishChanchal1
The road to establishing and leading a successful Google Developer Student Club (GDSC) involves several key steps focusing on leadership, team management, and event management.
Grammarly AI-NLP Club #2 - Recent advances in applied chatbot technology - Jo...Grammarly
Speaker: Jordi Carrera Ventura, Artificial Intelligence technologist at Telefónica R&D
Summary: Chatbots (aka conversational agents, spoken dialogue systems) allow users to interface with computers using natural language by simply asking questions or issuing commands.
Given a query, the chatbot builds a semantic representation of the input, transforms it into a logical statement, and performs all the necessary actions to fulfill the user's intent. Sometimes this simply means calculating an exact answer or retrieving a fact from a database, whereas other times it means building a contextual model and running a full-fledged conversation flow while keeping track of anaphoras and cross-references.
Besides the direct applications of chatbots in IoT (Amazon’s Alexa, Apple's Siri) and IT (the historical field of Information Retrieval as a whole can be seen as a sub-problem of spoken dialogue systems), chatbots' main appeal for technologists is their location at the intersection of all major Natural Language Processing technologies and many of the deepest questions in Cognitive Science today: semantic parsing, entity recognition, knowledge representation, and coreference resolution.
In this talk, I will explore those questions in the context of an applied industry setting, and I will introduce a framework suitable for addressing them, together with an overview of the state-of-the-art in chatbot technology and some original techniques.
Gain a practical understanding of how to integrate AI capabilities into your PHP projects with examples from the leading sources of hosted AI: OpenAI and Hugging Face. Armed with this knowledge, you can unlock new possibilities for intelligent, dynamic, and user-centric PHP applications that leverage the power of Artificial Intelligence.
So, join us for this transformative journey as we bridge the gap between PHP and AI, opening the door to a world of smarter and more innovative web applications.
A lightning talk presentation from Jisc's Focus on the future: new developments in accessible and assistive technologies event held on 16 March 2022 as part of Digifest community fringe.
Speech Recognition: Art of the possible - DigiFest 2022Dominik Lukes
Presentation introducing a panel discussion on the present and future of speech recognition for lecture capture at Digifest 2022 online fringe on Assistive Technologies: https://www.jisc.ac.uk/events/focus-on-the-future-new-developments-in-accessible-and-assistive-technologies-16-mar-2022
Speech Recognition: Art of the possible - DigiFest 2022Dominik Lukes
Presentation introducing a panel discussion on the present and future of speech recognition for lecture capture at Digifest 2022 online fringe on Assistive Technologies: https://www.jisc.ac.uk/events/focus-on-the-future-new-developments-in-accessible-and-assistive-technologies-16-mar-2022
Introduction to Prompt Engineering (Focusing on ChatGPT)Chameera Dedduwage
This is an introductory session on how to engineer prompts for commercially available Large Language Models (LLMs) such as ChatGPT and Gemini. This session uses ChatGPT as the example, but the strategies can be equally applied to Gemini and other LLMs.
Fusing Modeling and Programming into Language-Oriented ProgrammingMarkus Voelter
Modeling in general is of course different from programming (think: climate models). However, when we consider the role of models in the context of “model-driven”, i.e., when they are used to automati- cally construct software, it is much less clear that modeling is different from programming. In this paper, I argue that the two are conceptually indistinguishable, even though in practice they traditionally emphasize different aspects of the (conceptually indistinguishable) common approach. The paper discusses and illustrates language-oriented programming, the approach to {modeling| programming} we have successfully used over the last 7 years to build a range of innovative systems in domains such as insurance, healthcare, tax, engineering and consumer electronics. It relies on domain-specific languages, modular language extension, mixed notations, and in particular, the Jetbrains MPS language workbench.
Building intelligent applications with Large Language ModelsSpeck&Tech
ABSTRACT: Large Language Models (LLMs) have proved extraordinary capabilities in language understanding and generation, but their most promising feature is probably their reasoning capability. The fact that LLMs can understand complex problems, plan step-by-step solutions, and even work by intuition, make them powerful reasoning engine to be placed at the core of AI-powered application. In this session, we are going to explore how LLMs are revolutionizing the world of software development and paving the way for a new landscape for LLM-powered applications.
BIO: I'm Valentina Alto, a Data Science MSc graduate and Cloud Specialist at Microsoft, focusing on Analytics and AI workloads within the manufacturing and pharmaceutical industry since 2022. I've been working on customers' digital transformations, designing cloud architecture and modern data platforms, including IoT, real-time analytics, Machine Learning, and Generative AI. I'm also a tech author, contributing articles on machine learning, AI, and statistics, and I recently published a book on Generative AI and Large Language Models. In my free time, I love hiking and climbing around the beautiful Italian mountains, running, and enjoying a good book with a cup of coffee.
2016-11-12 02 Николай Линкер. Чему Java может поучиться у Haskell и наоборотОмские ИТ-субботники
Николай Линкер, Backend-developer, ISS Art
С детства любил математику, это и определило мою профессию. Закончил матфак ОмГУ, уже 16 лет разрабатываю ПО, постоянно ищу новые решения. Довелось поработать с широким диапазоном языков и предметных областей. Детально разбирался с графическими библиотеками, компиляторами и сетевыми протоколами. В докладе расскажу, что заслуживает распространения из Haskell в традиционные языки, вроде Java, и что в Java удалось лучше, чем в Haskell.
[Session #2] Leadership - Team & Event Management (1).pptxAshishChanchal1
The road to establishing and leading a successful Google Developer Student Club (GDSC) involves several key steps focusing on leadership, team management, and event management.
Android is a mobile operating system developed by Google, known for its open-...AshishChanchal1
Android is a mobile operating system developed by Google, known for its open-source nature, customizable user interface, vast app ecosystem, tight integration with Google services, robust security features, broad device compatibility, and regular updates.
Introduction to Machine Learning (ML) fundamentals.
Overview of Google Cloud's Vertex AI platform.
Hands-on demonstrations of ML model deployment and management.
Q&A sessions to address specific queries and challenges.
Resources for further learning and exploration in ML and Vertex AI.
_Solution Challenge_ Introduction for Angular.pptxAshishChanchal1
Unlock the potential of web development with Angular! From the basics to hands-on coding, this workshop has it all. Get ready to dive into the world of dynamic web applications. 🌐💻
Agenda:
🌱 Basics of Angular
⚙️ Installation Guide
📂 File Structure of Angular
👩💻 Hands-on: Build a Simple Angular App
_Solution Challenge_ Info Session Presentation december 6 (1).pptxAshishChanchal1
e Google Developer Student Clubs 2023 Solution Challenge mission is to solve for one of the United Nations’ 17 Sustainable Development Goals using Google technology.
Created by the United Nations in 2015 to be achieved by 2030, the 17 Sustainable Development Goals (SDGs) agreed upon by all 193 United Nations Member States aim to end poverty, ensure prosperity, and protect the planet.
We invite to join the competition
📚 Learn Google Cloud: Participants are provided with access to Google Cloud resources and guided through various topics and hands-on exercises related to Google Cloud services such as Compute Engine, BigQuery, Kubernetes, Cloud Storage, and more.
🛠️ Gain Practical Experience: These events are designed to provide practical, hands-on experience with Google Cloud tools and services. You'll have the opportunity to work on real-world scenarios and projects.
👩🏫 Interact with Experts: Some Study Jams may have Google Cloud experts or trainers available to answer questions and provide guidance as you work through the exercises.
🎁 Earn Rewards: Depending on the specific Study Jam event, participants may have the chance to earn rewards, certifications, or other incentives upon successful completion of the exercises.
🤝 Network and Collaborate: Study Jams often provide a platform for participants to network and collaborate with peers who share an interest in Google Cloud.
To participate in a Google Cloud Study Jam, you may need to register for the event, access the required materials and resources, and complete the exercises within a specified timeframe. These events are a great way to kickstart your journey into Google Cloud or expand your knowledge if you're already familiar with the platform. 🌟
"Dive into the world of tech innovation and collaboration at our GDSC (Google Developer Student Club) Info Session! Join us to discover exciting opportunities, workshops, and projects that will enhance your coding skills and expand your network within the tech community."
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
4. We’re in anAI-driven revolution
Source: AI: Recent Trends and Applications, Emerging Communication and Computing
Steam Power
1784
Electricity
1870
Information
Technology
1969
Artificial Intelligence
Today
AI
5. Proprietary +Confidential
NLP Evolution
What’s the noun in
this sentence?
What’s the invoice
amount?
Extraction
LLMs portend both quantitative and qualitative jumps in AI
capabilities
Conversational AI
Write an essay
Write some code
Generation
Translate this text to
Korean
Summarize this
document
Transformation
Are these the same
things?
Is the invoice vendor
recognized?
Matching
LLMs improve performance on
“classical NL” use cases
LLMs increasingly enable
new use cases.
Is the sentence’s
sentiment positive?
Is this an invoice?
Classification
6. This revolution started at Google and we continue to innovate
Responsible AIat the foundation
Google invents
Transformer
kickstarting LLM
revolution
Google’s
groundbreaking
large language
model, BERT
AlphaFold predicts
structures of all
known proteins
Text-to-Text
Transfer Transformer
LLM 10B P model open
sourced
Google LaMDA
model trained to
converse
Google PaLM
single model to
generalize across
domains
A conversational AI
Service powered by
LaMDA.
8. Traditional
programming
Wave of
neural networks
~2012
Cat:
type: animal
legs: 4
ears: 2
fur: yes
likes: yarn, catnip
(etc …)
This is a cat.
This is not a cat.
Is this a cat?
Yes
So, you’ve learned about
cats and millions of other
concepts …what’s a cat?
Proprietary +Confidential
Go read this huuuuuuge
pile of books.
A cat is …
Generative
language models
LaMDA, PaLM, GPT-3, etc.
9. Proprietary +Confidential
First, some vocab
Generative Model: An ML model that produces content, including language, code,
imagery, music, video, etc.
Large Language Model: machine learning models that are really good at
understanding and generating human language. Large refers to both size and
complexity of the neural network itself, as well as the size of the dataset it was trained
on. Can also be used for non-generative language tasks (eg classification)
Transformer: The neural network architecture underlying most of today’s generative
models (and, more widely, most SOTA ML models). Published by Google in 2017.
10. Proprietary +Confidential
What is a language model?
[...] [...]
[...]
honesty
[...]
the
is best
[...]
approach ...
way
Most likely next word Next most likely next word
Less likely next words
policy
11. Proprietary +Confidential
What is a language model?
To be or not to be.
Mumbai is to India, what London is to England
Masala Dosa is a popular South Indian Dish
12. Proprietary +Confidential
Prompt: the text you feed to your model
Prompt Design: The art and science of
figuring out what text to feed your language
model to get it to take on the behavior you
want.
13. Proprietary +Confidential
What is a language model?
Write a poem about Cricket
Cricket, oh cricket, game of my heart,
Where legends are born and dreams start.
With bat and ball, we play as one,
Under the sun, until the day is done.
From the village green to the grandest stage,
Cricket unites us, age after age.
With every run, we cheer and shout,
As our heroes make us proud.
…
Zero-shot
17. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:
Few-shot
18. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:
Few-shot
INSTRUCTIO
N
19. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:
Few-shot
EXAMPL
E
20. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:
Few-shot
INPU
T
21. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:
Few-shot
nudge the LLM
to output
javascript
22. Proprietary +Confidential
Give examples
Convert Python to Javascript.
Python: print("hello world")
Javascript: console.log("hello world")
Python: for x in range(0, 100):
Javascript:for (var x = 0; x < 100; x++)
Few-shot
24. Proprietary +Confidential
What is a language model?
User : Who are you?
Bot: I am Sachin Tendulkar, the famous cricketer
and the best batsman the world has seen.
User: Where do you live?
Bot: I live in Mumbai.
User: What do you currently do?
Bot: …
Dialog
25. Proprietary +Confidential
What is a language model?
User : Who are you?
Bot: I am Sachin Tendulkar, the famous cricketer
and the best batsman the world has seen.
User: Where do you live?
Bot: I live in Mumbai.
User: What do you currently do?
Bot: …
Dialog
Prompt
26. Proprietary +Confidential
Customizing Chat
User : Who are you?
Bot: I am Sachin Tendulkar, the famous cricketer
and the best batsman the world has seen.
User: Where do you live?
Bot: I live in Mumbai.
User: {USER_INPUT}
Bot: I am currently retired from cricket, but I am
still involved in the game as a mentor and
ambassador.
Dialog
Prompt
27. Proprietary +Confidential
Prompt Design is tricky
The art and science of figuring out what text to feed
your language model to get it to take on the
behavior you want.
28. Proprietary +Confidential
A few observations:
1. LLMs are designed to predict the next word in a sequence. They
are not required to be “truthful” when doing so.
2. LLMs can generate plausible-looking statements that are irrelevant
or factually incorrect.
3. Hallucinations: LLM’s can generate false statements.
29. Proprietary +Confidential
What is an LLM?
[...] [...]
[...]
honesty
[...]
the
is best
[...]
approach ...
way
Most likely next word Next most likely next word
Less likely next words
policy
34. Proprietary +Confidential
Temperature
T
emperature is a number used to tune the degree of randomness.
Lower temperature →less randomness
● T
emperature of 0 is deterministic (greed decoding)
● Generally better for tasks like q&a and summarization where you expect a
more “correct” answer
● If you notice the model repeating itself, the temp is probably too low
High temperature → more randomness
● Can result in more unusual (you might even say creative) response
● If you notice the model going off topic or being nonsensical, the temp is
likely too high
35. Proprietary +Confidential
Top K
[sīars (0.5),clouds (0.23),birds (0.05) …dusī (0.03)]
Only sample from top K tokens
K =2
Top P
[sīars (0.5),clouds (0.23),birds (0.05) …dusī (0.03)]
Chooses from smallest possible set
of words whose cumulative
probability >=probability P
P =.75
36. What are large language models?
ML algorithms that can recognize, predict, and
generate human languages
Pre-trained on petabyte scale text-based datasets
resulting in large models with 10s to 100s of
billions of parameters
LLMs are normally pre-trained on a large corpus
of text followed by fine-tuning on a specific task
Go read this huuuuuuge pile
of books.
So, you’ve learned about
cats and millions of other
concepts …what’s a cat?
A cat is a small, domesticated
carnivorous mammal.
Generative language models
LaMDA, PaLM, GPT-3, etc.
LLMs can also be called Large Models (includes all
types of data modality) and Generative AI (a
model that produces content)
37. Why are large language models
different?
LLMs are characterized by emergent
abilities, or the ability to perform tasks that
were not present in smaller models.
LLMs contextual understanding of human
language changes how we interact with
data and intelligent systems.
LLMs can find patterns and connections in
massive, disparate data corpora.
Search
Conversation
Content generation
38. Proprietary +Confidential
LLM applications in industry
Customer Support
● Interactive Humanlike Chatbots
● Conversation summarization for agents
● Sentiment Analysis and Entity extraction
Technology
● Generating Code Snippets from description
● Code Translation between languages
● Auto Generated Documentation from Code
Financial Services
● Auto-generated summary of documents
● Entity Extraction from KYC documents
HealthCare
● Domain specific entity extraction
● Case documentation summary
Retail
● Generating product descriptions
Media and Gaming
● Designing game storylines, scripts
● Auto Generated blogs, articles, and tweets
● Grammar Correction and text-formatting
39. Proprietary +Confidential
Traditional ML Dev
● Needs 1000+ training examples
to get started
● Needs ML expertise (probably)
● Needs compute time +hardware
● Thinks about minimizing a loss
function
● Needs 0 training examples*
● Does not need ML expertise*
● Does not need to train a model*
● Thinks about prompt design
LLM Dev
*T
o get started
41. Consumers & enterprises have different needs….
Plan a 3 day
trip to
Patagonia
Create a
valentine
poem.
A picture of a
panda playing
yahtzee
How to make GF
pancakes?
Iwant to
write a novel.
How do Iget
started?
Create a jazz
song for a bday
card
How do we
control our
data
How do we deal with
fraud &security
We need to be
accurate &
explainable
How do we integrate our
existing data &
applications
How will we
control
costs?
Bard +MakerSuite VertexAI +Duet AI
Consumers Enterprises
42. Google’s research drives a family of models
PaLM 2
Across many
modaliīies….Texī,
Code,Image, Dialogue,
Mulīimodal…..
Foundation Model
Families
Codey
Imagen
That power experiences for all users
Consumer /Hobbyist
Experiences
Bard
MakerSuite
Enterprise Experiences
AI Builder Experiences
VertexAI
Generative AIApp Builder
Med-PaLM 2
Sec-PaLM
● Unicorn
● Bison
● Otter
● Gecko
Animal indicates size
Numbers indicate version
001-> 002
Signifies refresh
Models for AI Builders
Example:
PALM API’s Model:
text-bison-001
Powers
In-console Code &Chat Assistance
SecurityAIWorkbench
43. Foundation
Models
VertexAI
End-to-End ML Platform
Generative Al
App Builder
Text Chat Code Image
Video
Google Cloud Infrastructure - GPUs/TPUs
Contact Center AI Healthcare AI
Discovery AI
Document AI
Conversation AI
Enterprise
Search
Foundation
Models
Business Users
AI Practitioners
Developers
Audio and
Music
Generative AI
Studio
Generative AI
APIs
Model Garden
Cloud AI Portfolio
To support the needs of Generative AI centric enterprise development
Duet Al for
Google Workspace
Duet Al for
Google Cloud
44. Duet AIfor Google Workspace Enterprise
Helps you write
in Gmail and Docs
Duet AI works behind the
scenes to help you write —
whether it’s refining existing
work or helping you get started
Helps you visualize
in Slides
With Duet AI, you can easily
create images for
presentations and meetings
from a simple prompt
Helps you organize
in Sheets
Duet AI is here to help you
organize, classify and
analyze your data faster
than ever before
Helps you connect
in Meet
Duet AI helps you look and
sound your best on video
calls so you can focus on the
conversation
45. Foundation Models
Across a variety of model sizes to address use cases
Embeddings APIfor
Text and Image
Extract semantic information
from unstructured data
PaLM for Text
Custom language tasks
Chirp for
Speech to Text
Build voice enabled applications
PaLM for Chat
Multi-turn conversations with
session context
Codey for
Code Generation
Improve coding and debugging
Now in GA
Allowlist
Imagen for Text to Image
Create and edit images from
simple prompts
Now in GA
Now in GA
Now in GA
Now in GA Now in GA
46. Announcing - GA onVertexAI
Generative AIStudio
Interact with, tune, and deploy foundation models
A simple UIfor interacting with models
Chat interface to interact with models
Prompt gallery to explore sample use cases
Prompt design to tune models
T
une models with your own data
A variety of tuning methods including tuning with simple
text prompts, fine-tuning, and tuning with human feedback
(RLHF).
Use models in production
Embed into applications by quickly generating and
customizing API code
Multiple modalities
APIs available for Text, Image (Allowlist), Code, and Speech
GA
49. If your campus is allocated the Gen AI
Arcade Game :here's the list of labs to
complete
For others:
Visit Generative AIArcade Game and ll
complete the Labs
Visit Google Cloud Computing
Foundations path and complete the
following journeys:
5 Create and Manage Cloud Resources
6Perform Foundational Infrastructure
T
asks in Google Cloud
2 Google Cloud Computing Foundations:
Infrastructure in Google Cloud