Who are we?
Our Goal
Value
Investment
For the value to be greater than the investment.
Understanding
AI technology.
AI knowledge opens doors!
Once a week
for 1 hr.
Involvement In HUMIC
Involvement In HUMIC
FIF (optional meetings)
Who are YOU?
Computer Science
17
Math/Statistics/Applied Math
21
Physics/Astrophysics
3
Economics
20
Government
7
EU Laws will be implemented rolling in 2026.
Environmental Science
3
Social Studies, Sociology, English, History of Science, Philosophy
8
At Harvard’s halls, bright minds begin to weave,�A fellowship where future thought takes flight.�Through learning’s spark, new visions they conceive,�Machine and human joined to seek the light.
Neuroscience, Psychology, MBB
7
Bio (Bioengineering, HDRB, Chemical and Physical Biology, Integrative Biology, etc.)
https://www.youtube.com/watch?v=7q8Uw3rmXyE
https://ideausher.com/blog/ai-powered-medical-imaging/
sciencedirect.com/book/9780443184987/artificial-intelligence-in-tissue-and-organ-regeneration
17
AFVS, Music, Theater
3
ChatGPT generated: Mona Lisa
Harvard club!
In Harvard square!
You will be introduced to each of these technologies!!
Now LOCK IN for our first bit of learning… :)
Agenda
Agenda
AI > ML > DL
Deep Learning
Machine Learning
AI
“Computer systems able to perform tasks that normally require human intelligence”
“Using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy”
“teaches computers to process data in a way that is inspired by the human brain”
Logical Reasoning
Spatial Reasoning
Language understanding
Creativity
x + 3 =y,
y + 1 = z
=> x +4 = z
Agenda
Machine Learning
Supervised learning
Reinforcement Learning
Unsupervised Learning
Supervised Learning
Supervised Learning
ML model
?=
x_i
g_i
y_i
Gradient Descent
Unsupervised Learning
Clustering data points with similar properties
CS
Chemistry
Econ
Chem/bio/physics
CS & Phil
Finance
K-Means Algorithm for Clustering
Reinforcement Learning
Reinforcement Learning
Model
y=h(x)
Input x
Output y
Supervised Learning Setting
Reinforcement Learning Setting
Model
a=h(s)
State s
Action a
New state s’
Reinforcement learning
Atlas from Boston Dynamics
Agenda
What’s coming :)
Who are YOU?
Attendance and Feedback
©2022 HUMIC. All rights reserved.
The Godfathers of AI
Geoffrey Hinton
“Now that neural nets work, industry and government have started calling neural nets AI. And the people in AI who spent all their life mocking neural nets and saying they'd never do anything are now happy to call them AI and try and get some of the money. “
Yoshua Bengio
Yann LeCun