Desiring "Artificial" Intelligence
Two "Expert Systems"
Symptom Checker with Body from WebMD - Check Your Medical Symptoms
Uses: Sequential Decision Making
Encoding Human Intelligence at Scale
IBM's Deep Blue defeating Kasparov, 1997
Rule-based / Brute force
(an iPhone 16 is about 2TFlops or about 200,000 Deep Blues)
A phone recognizes your fingerprint (to unlock) because it has learned visual patterns.
Spotify or TikTok recommends content because it has learned patterns in behavior.
Netflix may know your movie preference better than you!!!
Waze knows
Examples → Training → Model → Prediction
Fairness
Random Bounce of a Roomba
Limitations of "Reinforcement Learning System?"
- Reward function: What behavior is the system being rewarded for?
What can Machine Learning really do (despite these limitations)?
The Black Box: Inputs & Outputs
Neural networks process various inputs to generate specific outputs. While the inputs and outputs are clear, the intricate connections and transformations within the hidden layers make the internal decision-making process incredibly complex and often inexplicable. This characteristic is often referred to as the "black box" problem, highlighting the challenge of understanding how the network arrives at its conclusions.
Suppose Waze wants to predict
"How many minutes will it take to drive this road?"
Inputs might include
- Time of day , Day of week. Weather. Current speed
- Historical traffic, Holidays, Nearby events
Output
- Expected travel time
More on AlphaGo:
Creativity: Is this still a skill only humans possess?
Lee goes on to lose game three, and AlphaGo secures victory in the best-of-five series. At the press conference afterward, with Hassabis sitting next to him, Lee apologizes for letting humanity down. “I should have shown a better result, a better outcome,” he says.
As Lee speaks, an unexpected feeling begins gnawing at Hassabis. As one of AlphaGo’s creators, he is proud, even elated, that the machine has achieved what so many thought it couldn’t. But even he feels his humanness rise. He starts to hope that Lee will win one.
New Knowledges
Targeted Oncology
AlphaFold AI Sets Stage for Future Approaches in Cancer
The 2024 Nobel Prize in Chemistry highlights AI-driven breakthroughs in computational protein design and structure prediction. Tools like AlphaFold promise faster development of targeted cancer drugs and transformative advances in oncology and medicine.
AI and innovation Frontiers
Explainability
shap.readthedocs.io
An introduction to explainable AI with Shapley values — SHAP latest documentation
This is an introduction to explaining machine learning models with Shapley values. Shapley values are a widely used approach from cooperative game theory that come with desirable properties. This tutorial is designed to help build a solid understanding of how to compute and interpet Shapley-based explanations of machine learning models. We will take a practical hands-on approach, using the shap Python package to explain progressively more complex models. This is a living document, and serves as
The ChatGPT Moment
This may not be a bug
No code Innovation?
Let's try it at
If you can "Generate" text, video, sound, concepts … what else can you do?
What AI cannot do (well)
So what are Leaders expecting from AI for their organizations?
Out of sample Data: One of the many ways AI fails
The training data does not include a situation that you want it to answer
