
180: Reinforcement Learning
Failed to add items
Sorry, we are unable to add the item because your shopping cart is already at capacity.
Add to basket failed.
Please try again later
Add to Wish List failed.
Please try again later
Remove from Wish List failed.
Please try again later
Follow podcast failed
Unfollow podcast failed
-
Narrated by:
-
By:
About this listen
Intro topic: Grills
News/Links:
- You can’t call yourself a senior until you’ve worked on a legacy project
- https://www.infobip.com/developers/blog/seniors-working-on-a-legacy-project
- Recraft might be the most powerful AI image platform I’ve ever used — here’s why
- https://www.tomsguide.com/ai/ai-image-video/recraft-might-be-the-most-powerful-ai-image-platform-ive-ever-used-heres-why
- NASA has a list of 10 rules for software development
- https://www.cs.otago.ac.nz/cosc345/resources/nasa-10-rules.htm
- AMD Radeon RX 9070 XT performance estimates leaked: 42% to 66% faster than Radeon RX 7900 GRE
- https://www.tomshardware.com/tech-industry/amd-estimates-of-radeon-rx-9070-xt-performance-leaked-42-percent-66-percent-faster-than-radeon-rx-7900-gre
Book of the Show
- Patrick:
- The Player of Games (Ian M Banks)
- https://a.co/d/1ZpUhGl (non-affiliate)
- The Player of Games (Ian M Banks)
- Jason:
- Basic Roleplaying Universal Game Engine
- https://amzn.to/3ES4p5i
- https://amzn.to/3ES4p5i
- Basic Roleplaying Universal Game Engine
Patreon Plug https://www.patreon.com/programmingthrowdown?ty=h
Tool of the Show
- Patrick:
- Pokemon Sword and Shield
- Jason:
- Features and Labels ( https://fal.ai )
Topic: Reinforcement Learning
- Three types of AI
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Online vs Offline RL
- Optimization algorithms
- Value optimization
- SARSA
- Q-Learning
- Policy optimization
- Policy Gradients
- Actor-Critic
- Proximal Policy Optimization
- Value optimization
- Value vs Policy Optimization
- Value optimization is more intuitive (Value loss)
- Policy optimization is less intuitive at first (policy gradients)
- Converting values to policies in deep learning is difficult
- Imitation Learning
- Supervised policy learning
- Often used to bootstrap reinforcement learning
- Policy Evaluation
- Propensity scoring versus model-based
- Challenges to training RL model
- Two optimization loops
- Collecting feedback vs updating the model
- Difficult optimization target
- Policy evaluation
- Two optimization loops
- RLHF & GRPO
No reviews yet
In the spirit of reconciliation, Audible acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.