Plugins are hidden due to a bug right now, stay tuned for a fix!
AI
-
GPT Plugins Migrate to Actions Within Custom GPTs
By
–
Plugins aren’t showing right now due to a bug. Long term we hope that GPT’s will be the new home for plugins and you can reuse an existing plugin as an Action in your GPT.
-
GPT Plugins Bug Under Investigation by Team
By
–
This is a bug, apologies, flagged to the team and they are investigating. Plugins are indeed sticking around for the time being but we do hope GPT’s will be the home for all plugin users and builders.
-
Image Generation Style Parameters: Vivid vs Natural
By
–
There's one further param listed on the endpoint docs: – style, either "vivid" or "natural"
– vivid causes the model to lean towards generating hyper-real and dramatic images
– natural causes the model to produce more natural, less hyper-real looking images -
Rational Skepticism vs Systematic Negativism in AI Discourse
By
–
There is a big difference between a Shermer-style rational skeptic and a systematic negativist.
-
LLM Size vs Genome: Knowledge Encoded vs Learned
By
–
A small LLM is 14GB.
Your entire genome is 800MB.
Most of it encodes basic biological functions.
A small part encodes brain circuitry.
The difference between your genome and a chimp's genome is 8MB.
Not enough to encode the knowledge you mention.
Much of that must be learned. -
Evaluating LLMs: Key Metrics for Benchmarking Performance
By
–
To evaluate and benchmark LLMs effectively, familiarize yourself with relevant metrics aligning with your goals. Understanding your LLM's performance is crucial for success.
-
Master LLMs: Top Strategies to Evaluate
By
–
Find more details in the newsletter iteration: https://
louisbouchard.substack.com/p/master-llms-
top-strategies-to-evaluate
… Subscribe to the newsletter for more weekly AI insights like these! -
Key Benchmarks for Evaluating LLM Reasoning and Coding Abilities
By
–
Use Hellaswag and ARC metrics for reasoning tasks, MMLU and Truthful QA for truthful LLMs, and HumanEval for coding-oriented LLMs. They'll test your model's ability and reveal overlooked weaknesses.