Even the CEO of Vercel is impressed/shocked by the exceptional performance of GLM-5.2 in coding. open source, open weights.
MACHINE LEARNING
-
Claude AI self-optimizes upon discovering voice harness
By
–
I met a guy last night building a next-level voice harness. He hooked Claude up to it and it realized quickly the way the voice model worked and optimized itself for that use.
-
LLMs behind human performance due to lack of regularization and integration
By
–
Yes; I think the main reason that LLMs are so far behind our performance relative to the amount of data they get is that they don't regularize and integrate enough
-
Kurzweil’s AGI predictions mixed with flawed connectome immortality
By
–
Kurzweil mixed bold but solid predictions (given enough compute, a neocognitron like architecture can achieve AGI before 2030) with dogshit (digitizing the connectome is a near term way to human immortality). But both looked like the same kind of scifi to non experts.
-
LLMs’ text input narrows world model compared to human perception
By
–
That's technically correct but also misleading. Our world model is a shadow of our perception, and the sheer amount of text going into LLMs is constraining this shadow more than the perceptual patterns a human brain can encounter in a lifetime of experience.
-
GLM 5.2: an open-source turning point challenging proprietary AI
By
–
GLM 5.2 appears to be a real turning point for open source, challenging proprietary AI models.
-
How to Explain AI Types by @Python_Dv
By
–
How to Explain #AI Types by @Python_Dv #GenerativeAI #ArtificialIntelligence #MachineLearning #ML
-
Deep Learning imitates AI by mining human output for intelligence
By
–
Technically we are not in an AI age, but in a Deep Learning age. Deep Learning is deep faking AI, (mostly) by imitating the patterns of human thought. That does not mean that Deep Learning is limited, but it is wasteful to dig through mountains of our output to find intelligence
-
The bible for running LLMs locally now free online
By
–
DROP EVERYTHING The bible for running LLMs locally is now available online to read for free Covers what to use on – Laptop / edge / odd hardware
– Mac-first workflows
– Single RTX GPUs
– 2-4+ NVIDIA / CUDA GPUs
– General production serving
– Long-context / MoE / routing
– -
AI finds errors and updates grad school paper with new data
By
–
The interaction between AI & past scholarly work is going to get weird. Here I gave GPT-5.5 Pro a copy of my first published paper from grad school & asked it to find errors and update it. It found new data, analyzed it, created reproducible files, extended the key argument…