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← Avoiding sending prompts and code to external services is the…
17 connected korrents · 16 moments from 28 Feb 2024 to 21 Sept 2026.
Everything filed under LLMs
LLMs
Everything filed under privacy
privacy
Everything filed under OpenAI
OpenAI
Everything filed under scaling laws
scaling laws
Everything filed under the cloud
the cloud
Everything filed under documentation
documentation
Everything filed under AI alignment
AI alignment Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: Avoiding sending prompts and code to external services is the strongest reason to use local AI models instead of cloud ones. Avoiding sending prompts and code to external services is the strongest reason to use local AI models instead of cloud ones. Last stated 6 months ago
9 Apr 2026
EB
Emanuele Bartolesi — holds since 2026-04-09 — tap for who they are
Same subject: Cloud AI models are still better than local models for tasks that need high accuracy, large context handling, or production-grade reliability. — tap to centre the map on it Cloud AI models are still better than local models for tasks that need high accuracy, large context handling, or production-grade reliability. Last stated 6 months ago
9 Apr 2026
EB
Emanuele Bartolesi — holds since 2026-04-09 — tap for who they are
Same subject: Users should never have to think about whether an AI agent's work runs locally or in the cloud. — tap to centre the map on it Users should never have to think about whether an AI agent's work runs locally or in the cloud. Last stated 3 weeks ago
8 Sept 2026
RU
Roman Ugarte — holds since 2026-09-08 — tap for who they are
Same subject: Running AI models locally on a Mac Studio offers performance and cost advantages over cloud-based solutions. — tap to centre the map on it Running AI models locally on a Mac Studio offers performance and cost advantages over cloud-based solutions. Last stated 2 weeks ago
21 Sept 2026
FV
Federico Viticci — holds since 2026-09-21 — tap for who they are
Same subject: Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject. — tap to centre the map on it Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject. Last stated 8 months ago
12 Feb 2026
PS
Peter Steinberger — holds since 2026-02-12 — tap for who they are
Same subject: Weaker AI models match stronger ones on simple prompts, but strong models are increasingly preferred as prompts get more challenging. — tap to centre the map on it Weaker AI models match stronger ones on simple prompts, but strong models are increasingly preferred as prompts get more challenging. Last stated 3 years ago
28 Feb 2024
CH
Chip Huyen — holds since 2024-02-28 — tap for who they are
Same subject: Models are far more differentiated from one another than clouds are, so AI will not commoditise the way cloud did. — tap to centre the map on it Models are far more differentiated from one another than clouds are, so AI will not commoditise the way cloud did. Last stated 8 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — tap for who they are
Same subject: The strongest reason to keep training much smarter models quickly is to build defences against other AI. — tap to centre the map on it The strongest reason to keep training much smarter models quickly is to build defences against other AI. Last stated 4 weeks ago
6 Sept 2026
JP
Jakub Pachocki — holds since 2026-09-06 — tap for who they are
Same subject: There is unmet demand for a single, well-integrated local AI model experience, rather than a patchwork of local AI components. — tap to centre the map on it There is unmet demand for a single, well-integrated local AI model experience, rather than a patchwork of local AI components. Last stated 5 months ago
14 May 2026
SS
Salvatore Sanfilippo — holds since 2026-05-14 — tap for who they are
Same subject: A company can lead its industry on values like privacy and user respect without actually excelling at them — tap to centre the map on it A company can lead its industry on values like privacy and user respect without actually excelling at them Last stated 6 months ago
1 Apr 2026
MA
Marco Arment — holds since 2026-04-01 — tap for who they are
Same subject: A company's terms of service cannot enlarge or shrink your constitutional privacy rights in either direction. — tap to centre the map on it A company's terms of service cannot enlarge or shrink your constitutional privacy rights in either direction. Last stated 10 months ago
16 Dec 2025
OK
Orin Kerr — holds since 2025-12-16 — tap for who they are
Same subject: A home assistant is only as good as its context, and context comes from sensors placed around the house rather than from a better model. — tap to centre the map on it A home assistant is only as good as its context, and context comes from sensors placed around the house rather than from a better model. Last stated 4 months ago
7 Jun 2026
TF
Tony Fadell — holds since 2026-06-07 — tap for who they are
Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. Last stated 10 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. Last stated 3 months ago
26 Jun 2026
NB
Noam Brown — holds since 2026-06-26 — tap for who they are
Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. Last stated 7 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. — tap to centre the map on it A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. — tap to centre the map on it A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it. Last stated 4 weeks ago
3 Sept 2026
ZM
Zvi Mowshowitz — holds since 2026-09-03 — tap for who they are
Same subject: Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. — tap to centre the map on it Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
At the centre
Avoiding sending prompts and code to external services is the strongest reason to use local AI models instead of cloud ones.
Holds Read this korrent →
Cloud AI models are still better than local models for tasks that need high accuracy, large context handling, or production-grade reliability.
Holds
Users should never have to think about whether an AI agent's work runs locally or in the cloud.
Holds
Running AI models locally on a Mac Studio offers performance and cost advantages over cloud-based solutions.
Holds
Do not run a personal agent on a cheap or local model: weak models are gullible and easy to prompt-inject.
Holds
Weaker AI models match stronger ones on simple prompts, but strong models are increasingly preferred as prompts get more challenging.
Holds
Models are far more differentiated from one another than clouds are, so AI will not commoditise the way cloud did.
Holds
The strongest reason to keep training much smarter models quickly is to build defences against other AI.
Holds
There is unmet demand for a single, well-integrated local AI model experience, rather than a patchwork of local AI components.
Holds
A company can lead its industry on values like privacy and user respect without actually excelling at them
Holds
A company's terms of service cannot enlarge or shrink your constitutional privacy rights in either direction.
Holds
A home assistant is only as good as its context, and context comes from sensors placed around the house rather than from a better model.
Holds
"Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next.
Holds
A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number.
Holds
A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from.
Holds
A startup should not begin life as a nonprofit and bolt a for-profit arm on later, whatever OpenAI's own history suggests.
Holds
A technique that lets an AI model's reasoning shift outside its visible Chain of Thought is dangerous, both because it works and because a leading lab is willing to deploy it.
Holds
Advertising was a necessary phase for the internet but a momentary industry, and an AI people pay for is better because they know the answers are not influenced by advertisers.
Holds