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2. What is Google Cloud Study Jam?
• Google Cloud Study Jams will provide students an opportunity to kickstart
their learning on Cloud technology.
• The goal is to teach developers cloud skills using Google Cloud Platform
through hands-on technical labs and tutorials.
• Participants get free access to Qwiklabs for one month to complete hands-
on labs. Those who complete designated labs receive Google Cloud badges
and rewards.
• Expand your learnings and be industry-ready!
5. What is cloud?
â—Ź Cloud technology essentially refers to the delivery of computing services -
servers, storage, databases, networking, software, analytics and more - over the
Internet ("the cloud") to offer faster innovation, flexible resources and economies
of scale
â—Ź Take the analogy of a small office having very cramped office space
â—Ź Similarly cloud also rents us some storage and computing resources by giving a
price. As the usage increases more resources will be utilised and more price will
be paid
6.
7.
8. Google Cloud Storage
â—Ź Google Cloud Storage is an object storage service that allows users to store
and retrieve data in the form of objects
â—Ź It provides highly scalable, durable, and secure storage for various types of
data, including documents, images, and multimedia content.
Google Cloud Datastore & SQL Datastore
â—Ź This services provide NoSQL document/collection model and SQL tables for
building highly scalable and consistent applications
â—Ź It automatically handles sharding and replication, providing a robust and
flexible storage solution for structured data
9.
10. Google Compute Engine
â—Ź Google Compute Engine is an Infrastructure as a Service (IaaS) that allows
users to run virtual machines (VMs) on Google's infrastructure.
â—Ź It provides scalable and flexible computing resources for running various
workloads
Google App Engine
â—Ź Google App Engine is a Platform as a Service (PaaS) that enables developers
to build and deploy applications without managing the underlying infrastructure
â—Ź It supports multiple programming languages and automatically scales based on
demand.
11. Google BigQuery
â—Ź Google BigQuery is a serverless, highly scalable, and cost-effective data
warehouse and analytics service.
â—Ź It allows users to run fast SQL queries on large datasets and analyze data in
real-time, making it ideal for business intelligence and data analysis
Google AI/ML Services
â—Ź Vertex AI is Google's flagship AI/ML platform. It allows you to train ML
models, host trained models, and make predictions using those models
â—Ź You can train models using TensorFlow, scikit-learn, XGBoost, and custom
containers. Vertex AI also offers AutoML capabilities to automate the model
training process
13. We’re in an AI-driven
revolution
Source: AI: Recent Trends and Applications, Emerging Communication and Computing
Steam
Power
1784
Electricity
1870
Information
Technology
1969
Artificial Intelligence
Today
A
I
14. This revolution started at Google and we continue to
innovate
Responsible AI at 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.
16. 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.
17. Proprietary + Confidential
First, some vocabulary
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.
18. 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.
19. 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
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
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:
Few-
shot EXAMPLE
23. 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
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.
25. 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.
26. Proprietary + Confidential
Temperature
Temperature is a number used to tune the degree of randomness.
Lower temperature →less randomness
â—Ź Temperature of 0 is deterministic (greed decoding)
â—Ź Generally better for tasks like q&a and summarization where you expect a
more “correct” answer
â—Ź If you notice the model repeating itself, the temp is probably too low
High temperature → more randomness
â—Ź Can result in more unusual (you might even say creative) response
â—Ź If you notice the model going off topic or being nonsensical, the temp is
likely too high
27. 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)
28. Proprietary + Confidential
LLM applications in
industry
Customer Support
â—Ź Interactive Humanlike Chatbots
â—Ź Conversation summarization for agents
â—Ź Sentiment Analysis and Entity extraction
Technology
â—Ź Generating Code Snippets from description
â—Ź Code Translation between languages
â—Ź Auto Generated Documentation from Code
Financial Services
â—Ź Auto-generated summary of documents
â—Ź Entity Extraction from KYC documents
HealthCare
â—Ź Domain specific entity extraction
â—Ź Case documentation summary
Retail
â—Ź Generating product descriptions
Media and Gaming
â—Ź Designing game storylines, scripts
â—Ź Auto Generated blogs, articles, and tweets
â—Ź Grammar Correction and text-formatting
29. Proprietary + Confidential
Traditional ML
Dev
â—Ź Needs 1000+ training examples
to get started
â—Ź Needs ML expertise (probably)
â—Ź Needs compute time + hardware
â—Ź Thinks about minimizing a loss
function
â—Ź Needs 0 training examples*
â—Ź Does not need ML expertise*
â—Ź Does not need to train a model*
â—Ź Thinks about prompt design
LLM
Dev
*To get
started
31. 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?
I want to
write a
novel. How
do I get
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 &
explainabl
e
How do we integrate our
existing data &
applications
How will we
control
costs?
Bard +
MakerSuite
Vertex AI + Duet
AI
Consumer
s
Enterprise
s
32. Foundation
Models
Vertex AI
End-to-End ML Platform
Generative Al
App Builder
Tex
t
Chat Code Imag
e
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
Developer
s
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
33. Duet AI for 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
39. IMPORTANT POINTERS TO REMEMBER
● Don’t engage in making notes
â—Ź Cover the topics which are easy to understand and intuitive first
â—Ź Use google chrome at its latest version for attending labs
â—Ź Videos link for labs will be shared with you so that you can watch them
whenever you are stuck
● Don’t try to become an expert, Be a learner!