Can we just maybe get "line go up now but might not forever?"
Who's Who of AI
Isaiah Bishop
Why they matter
Tracked through public AI activity and peer connections inside the directory.
- AI signals
- 7 past 30d
- Sources
- 6 distinct domains
- Discussions
- 106 past 30d
- Latest signal
- 12h ago
ML Eng. and econometrics. Honorary Commodities Trader**. more left-posting than normal.
**Regrettably degen trading on here, im sorry
Views dont reflect my employer
What they're sharing
When AI builds itself anthropic.com
openai.com
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Qwen/Qwen3.8-27B · Hugging Face huggingface.co
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Claude Fable 5 and Claude Mythos 5 anthropic.com
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Generative artificial intelligence creates delicious, sustainable, and nutritious burgers | npj Science of Food nature.com
How LLMs Distort Our Written Language arxiv.org
nytimes.com
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openai.com
Emergent Capabilities Arise Randomly from Learning Sparse Attention Patterns arxiv.org
wsj.com
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What Investment Data Implies about the AI Transition nber.org
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z.ai
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Articles & links
Isaiah Bishop reposted
Astra, the next version of GPT, solves 10 unsolved problems in math Each of these problems has had little to no progress in ten years or more openai.com/index/ten-ad...
Isaiah Bishop reposted
Qwen3.8-27B is out! On the benchmarks they included, is close to or exceeds Opus 4.6 huggingface.co/Qwen/Qwen3.8...
Isaiah Bishop reposted
www.anthropic.com/news/claude-...
Isaiah Bishop reposted
Finally, AI finds its ultimate use case. A diffusion model trained on burger recipes "discovers the classic Big Mac without explicit supervision and generates novel burgers optimized for deliciousness, sustainability, or nutrition." ASI= automated slider intelligence www.natur…
AI Weekly's analysis
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Isaiah Bishop reposted
Fantastic paper demonstrating how LLM editing is gradually distorting our writing and the way we think to write: arxiv.org/abs/2603.18161
AI Weekly's analysis
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- Heavy LLM users produced nearly 70% more essays that stayed neutral on the topic question, and reported the writing felt less creative and not their own.
- Even when asked only to fix grammar in 2021 human-written essays, LLMs significantly altered the semantic meaning of the text.
- About 21% of peer reviews at a recent top AI conference were AI-generated, and those reviews scored papers a full point higher on average.
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Isaiah Bishop reposted
It's interesting. Don't have an entirely clear picture from just this, but I would have questions about the counterfactuals here that I doubt could be answered (would these groups' tactics be substantively different without this access? etc.). www.nytimes.com/2026/07/10/u...
Man look at the change in the sales pitch openai.com/index/gpt-5-6/
Isaiah Bishop reposted
I'm so happy when other people write papers on nondeterministic factors in training. embrace the chaos
AI Weekly's analysis
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- Emergent capabilities arise stochastically: the same model can gain or fail to gain a capability depending on its random initialization.
- Researchers used Pythia models from 14M to 410M parameters to show attention pattern learning is the key bottleneck to capability emergence.
- More attention heads improved learning efficiency; MLP-Mixer outperformed standard transformers on tasks with complex attention patterns.
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Isaiah Bishop reposted
“.. what does it say when even Masa thinks it’s too far out there?” @wsj.com $SPCX www.wsj.com/tech/why-one...
Isaiah Bishop reposted
According to a new NBER paper, to justify the AI investment surge we're seeing, the implied productivity gains need to be enormous. The authors calibrate a model where AI-sector productivity rises by roughly 2.7x. Link: www.nber.org/papers/w35290
Isaiah Bishop reposted
GLM-5.2 weights are now out! 1M context, and beats or matches GPT-5.5 and Opus 4.7 on many tasks... I hope to see a comparison between this model and Kimi-k2.7 soon z.ai/blog/glm-5.2 It also contains agentic slime (?)
Their own posts
Recent commentary
If both anthropic, and OpenAI gor from 10 bil ARR in Q1, to 100-200 bil ARR in Q4. surely we are having a hole somewhere thats being created
A guy made a homeautomation-based weather station and it looks really good, and all the reddit comments are like "actually you shouldve tagged this AI??? disgusting"
Contrary to what a lot of people think about LLM code quality, what its really enabled us to do is parallelize tech maintenance. And as a result our repos are so much cleaner
Have openAI and Anthropic cracked continual learning? Well its simple, if its what you expect they wouldn't need to keep raising money
Was listening to Dwarkesh but im always struck by this kind of belief that AI will be able to, in his words, start a business and be great at it or "be as good at texas politics as LBJ" and like it just seems to me we are asking too much of generalization
it does kind of feel like a lot of things have become correlated in ways that are undesirable. Idk how to say this but like it was useful when bonds and stocks werent correlated. Useful when US and ex-US werent just different flavours of the AI trade. And like same politically.
I had posts earlier in 2025 saying "AI build out isnt like sub prime" and that was true then. We are definitely looking a little more subprime for sure
Probably worth thinking about why AI isnt like serving cloud. And i think a key difference is that the migration to cloud providers like AWS, Azure, GCS was taking already established revenue, and then streamlining and consolidating. AI services remain high CAPEX/highly uncertain projection based
I do wish we could have competent govt because like LLMs and Robotics being govt owned does legit feel like in the limit we could achieve socialist paradise and oceans of lemonade or whatever
Thinking about, mathematics and programming are maybe the most natural places for an LLM to succeed because they are literally studies of abstraction. Like math doesn't get harder it just goes into a new universe of abstraction.
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In Isaiah Bishop's orbit
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