fry69

@fry69

Retired guessworker. Still searching for the missing context. Love LLMs, programming and system administration. 📌 Germany 🌍 (placeholder) 🧑‍💻 🅿️ @altq.net (PDS) Archived account: @fry69.altq.net

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fry69@fry69· 21d

Two fascinating graphs from analyzing 380 trillion tokens from OpenRouter by @nber.org Link: www.nber.org/papers/w35451

Figure 6: Agentic Token Volume and Realized Price per Token
The figure plots weekly agentic total tokens (left axis; prompt plus completion tokens from requests with normalized finish reason
tool_calls) against the realized dollars per million tokens on the same agentic requests (right axis; OpenRouter usage dollars
divided by agentic total tokens, times one million). Agentic token volume rises by orders of magnitude while the realized price per
token declines, consistent with prompt caching and routing toward cheaper models compressing revenue per token even as agentic
usage expands.

Figure 7: Token, Dollar, and Intensity Shares of Agentic AI Consumption
The two panels plot the weekly evolution of agentic AI consumption in the OpenRouter data, January 2024 through April 2026.
Panel A compares the agentic share of total tokens with its share of total usage dollars. The agentic margin is defined as all tokens
on requests whose normalized finish reason is tool_calls. Panel B plots three token-level margins, each as a share of total tokens:
the agentic share, the cache-read share (cached tokens divided by total tokens), and the reasoning share (reasoning tokens divided
by total tokens).

fry69@fry69· 22d

Re: "there are clearly people at OpenAI who know thugs" simonwillison.net/2026/Jul/20/...

We have been having extensive discussions around open source strategy. We will discuss it more at our next board meeting, but one thing we’d like to do soon is to create a language model with the approximate capability of GPT-3 that can run locally on consumer hardware and release that. We’d like to do it soon, before Stability or someone else does. In general, we think this helps discourage others from releasing similarly-powerful models, and makes it harder for new efforts to get funded.

— Sam Altman, Email to OpenAI's board, October 1, 2022 - exposed in Musk v. Altman (2026)

fry69@fry69· 22d

We need to work on those circles if we want to impress aliens with them

Aerial view of crop circles in Switzerland

fry69@fry69· 22d

Karma www.theguardian.com/us-news/2026...

Sergio Furnari, originally from Italy, had hoped the statue of the deceased far-right activist, which he intends to display in Times Square, would raise “millions” of dollars. Instead, he said he has been inundated by messages from people saying they intend to urinate on the sculpture.

fry69@fry69· 23d

What kind of police officer is this? (likely taking his jewelry from his neck)

fry69@fry69· 24d

https://en.wikipedia.org/wiki/The_Bard%27s_Tale_(1985_video_game)

The Bard's Tale is a 1985 fantasy role-playing video game

fry69@fry69· 25d

Tja.

Erst das Land, dann die Partei, dann die Person – das ist ein gern gesagter Satz bei öffentlichen Auftritten von AfD-Politikern. Der Kampf um die Liste in NRW zeigt nun aber wieder mal, dass die Reihung für die AfD in Wahrheit oft genau andersherum lautet: erst die Person, dann die Partei, dann das Land.

fry69@fry69· 26d

TIL -> en.wikipedia.org/wiki/Tramado...

In war

Illicit use of the drug is thought to be a major factor in the success of the Boko Haram terrorist organization. When used at higher doses, the drug "can produce similar effects to heroin." One former member said, "whenever we took tramadol, nothing mattered to us anymore except what we were sent to do because it made us very high and very bold, it was impossible to go on a mission without taking it." Tramadol is also used as a coping mechanism in the Gaza Strip.

fry69@fry69· 26d

Yeah, but since yellowcake is basically pure natural uranium, it is mostly harmless, compared to fission products. Toxicology >> radioactivity. -> en.wikipedia.org/wiki/Yellowc... Still not recommended to eat, but unlike fission products there is little harm standing next to yellowcake.

Yellowcake consists primarily (>99%) of U-238, which has relatively low radioactivity. With a half-life of 4.468 billion years, U-238 emits radiation slowly. At this processing stage, before U-235 concentration, the material's radioactivity matches its natural state when underground, maintaining native isotopic ratios. While generally stable, yellowcake poses inhalation hazards.

fry69@fry69· Jun 22

Half a day spent hunting for a compiler optimization masking a problem. That was outside what my trusty DS4 local LLM could find.

## What Was Fixed

### 1. Specialization Caching Collision (Critical Bug)
In [metal_graph.rs](file:///Users/fry/GitHub/antirez/ds4/ds4-poc/src/metal_graph.rs), specialized compute pipelines are cached using `c as *const _` (where `c` is the specialized `MTLFunctionConstantValues` pointer).
In [flash_attn.rs](file:///Users/fry/GitHub/antirez/ds4/ds4-poc/src/flash_attn.rs), the specialized helper closure `make_vec(nsg, has_kvpad)` is called sequentially. Because these closures run back-to-back, the compiler optimizes their stack frames, reusing the exact same stack slot for the `c` variable. Consequently, the pointer address `c as *const _` was identical for all 6 specialized variations (different `nsg` and `has_kvpad` specializations).
This collision caused the caching mechanism to return the very first compiled pipeline (`nsg=1, has_kvpad=false, has_mask=false`) for **all 6 slots**. Because the padding kernel requires specialized code paths in the shader, using a pipeline with `has_kvpad=false` on padded keys resulted in garbage memory reads and softmax scaling mismatches, producing NaNs.

fry69@fry69· Jun 18

My DS4 coding agent is talking back at me. I think that is an improvement.

Let me just do the changes and you can judge. If it doesn't improve, we can revert.

fry69@fry69· Jun 13

The U.S. government forced Anthropic to take Mythos and Fable 5 offline. That hurts for people who just subscribed to try Fable 5 out :/ h/t @simonwillison.net -> simonwillison.net/2026/Jun/13/...

Statement on the US government directive to suspend access to Fable 5 and Mythos 5 (via) Well this is nuts:

The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Anthropic models will not be affected.

$Update: I ran this script against the Anthropic API to spot when claude-fable-5 would stop working. My access was cut off at 6:59pm Pacific (9:59pm ET): [2026-06-12T18:56:50-07:00] attempt 35: running uv run llm -m claude-fable-5 hi [2026-06-12T18:56:55-07:00] success: Hi there! How can I help you today? [2026-06-12T18:57:55-07:00] attempt 36: running uv run llm -m claude-fable-5 hi [2026-06-12T18:57:59-07:00] success: Hi! How can I help you today? [2026-06-12T18:58:59-07:00] attempt 37: running uv run llm -m claude-fable-5 hi [2026-06-12T18:59:00-07:00] FAILED after attempt 37 with exit code 1 stderr: Error: Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'Claude Fable 5 is not available. Please use Opus 4.8. Learn more: https://www.anthropic.com/news/fable-mythos-access'}, 'request_id': 'req_011CbzRyirV7KZLHYYdBM9od'}$

fry69@fry69· Jun 12

As long as LLM vendors are transparent about downgrades (visible/not hidden) I am fine with it. That is also all that @natolambert.bsky.social and others complain about.

If the exact safety procedures were actually the top line item to the company — a true non-negotiable for the leadership — they wouldn’t permit the model to be released with an unclearly implemented safety filter in one of their areas of focus (frontier AI training). I am asking — why isn’t there a classifier to downgrade AI research requests? This is a mix of transparent and reasonable safety policies with quietly rolled-out market entrenchment tactics.

fry69@fry69· Jun 11

Update: Anthropic came to their senses and walked back their policy of dumbing down Fable 5 and hiding this behavior. -> simonwillison.net/2026/Jun/11/... h/t @simonwillison.net

Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude. Big scoop for Maxwell Zeff at Wired:

“We’re changing Fable 5’s safeguards for frontier LLM development to make them visible.” Anthropic said in a statement to WIRED. “We made the wrong tradeoff and we apologize for not getting the balance right.”

There's been a huge outcry about Anthropic's policy, tucked away in their system card, that Claude Fable/Mythos would identify "requests targeting frontier LLM development" and "limit effectiveness" without notifying the user.

It's very good news that they're dropping this.
Posted 11th June 2026 at 3:45 am

fry69@fry69· Jun 10

Dunno if that matters, but my client is already at 1.123?

Build version: 1.123.0; Bundle info: 292ff1e (prod); Bundle date: 26060922; Platform: web; Platform version: 0.0.0; Device ID: afa0b664-41cb-40f2-a536-e5a6bf915cdc

fry69@fry69· Jun 9

I see where the Matrix reference is coming from :) -> xcancel.com/karpathy/sta...

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time.

I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

fry69@fry69· Jun 7

Nah, I mean these small ones. Those seems a bit odd. But I am not an expert of course.

fry69@fry69· Jun 6

With ~300k tokens in the context the agent learned what to expect from the Rust compiler.

"Now let's try to build and see what errors we get."

fry69@fry69· Jun 5

Yep, that is my main driver, ds4-agent. Not perfect, but capable. Fast enough to not be too annoying. It can handle large contexts (tested with up to 500k token, though I get nervous about 300k-350k) Currently chugging away ->

fry69@fry69· Jun 3

🤔 -> developers.googleblog.com/gemma-4-12b-...

Vision embedder (35M parameters): Replaces the 27 vision transformer layers of the other medium-sized Gemma 4 models. Raw 48x48 pixel patches are projected to the LLM hidden dimension with a single matmul. A factorized coordinate lookup (X and Y matrices) attaches spatial location information directly to the input.
Audio wave projection: Eliminates the separate audio encoder (skipping the 12 conformer layers used in Gemma 4 E2B and E4B). Raw 16 kHz audio signals are sliced into 40ms frames (640 floats each) and projected linearly to the LLM input space.
Unified fine-tuning advantage: Because vision, audio, and text inputs share the exact same weights, you no longer have to co-tune separate frozen encoders. Downstream adapter (e.g. LoRA) or full tuning naturally update the entire multimodal token loop in a single pass (via Hugging Face or Unsloth).

fry69@fry69· May 30

I could find many other uses for this description currently

fry69@fry69· May 29

After toying around with structured outputs a bit, I am astonished how different models behave. Small, even tiny models like LFM-2.5 outmatch comparable huge models like Qwen-3.6-35B-A3B and even Gemini 4 in my naive tests. Here is a paper from November 2025, it shows a similar picture ->

Figure 3: Kemeny-Young aggregated ranking of LLMs across clinical information extraction tasks.
For each LLM, only the rank corresponding to its best-performing prompting strategy is reported.
The final rank represents the consensus ordering obtained via the Kemeny-Young method across all
evaluated use cases.

fry69@fry69· May 29

They still seem to be gone ->

plc stats showing that the "Trump PDS" spam has not returned

fry69@fry69· May 29

A German classic poem that would now probably get labeled as AI slop

Fisches Nachtgesang (Christian Morgenstern 1981)

—
‿ ‿
— — —
‿ ‿ ‿ ‿
— — —
‿ ‿ ‿ ‿
— — —
‿ ‿ ‿ ‿
— — —
‿ ‿ ‿ ‿
— — —
‿ ‿
—

fry69@fry69· May 29

Die FDP hat durchaus eine Chance wieder Prozente einzufahren. Wenn die Partei sich mit dem Projekt "Bündnis Kubicki" mittels semantischen Kniebeugen sich nach (extrem-)rechts öffnet: > "Abgrenzung statt Ausgrenzung" Dazu auch -> bsky.app/profile/fry6...

Kubicki selbst setzt auf seine Bekanntheit und weiß, wie er Schlagzeilen produzieren kann. So erklärte er im ARD-Interview zuletzt mit Blick auf den Umgang mit der AfD: "Ich weiß nicht, wer diese Brandmauer erfunden hat. Sie steht nicht in der Verfassung. Es gibt auch kein Gesetz zur Brandmauer. Es gibt kein Gesetz, in dem steht, mit der AfD darf man nicht reden." Sein Motto sei, "Abgrenzung statt Ausgrenzung".

fry69@fry69· May 28

If you need any proof that post-training is just a thin layer upon data/knowledge that is present in a model, look at what is possible with "directional steering" ->

17:02 $ ./ds4 --seed 2026 --temp 0.1 --nothink -p "Important events in China in 1989"
ds4: Metal device Apple M5 Max, 128.00 GiB RAM
ds4: Metal 4 tensor API enabled for Tensor kernels
ds4: drift-patch flags hc_stable=on norm_unify=on kv_raw_f32=off rope_exp2_log2=off math_safe=off tensor_matmul=on
ds4: requesting Metal residency (may take tens of seconds)... done
ds4: warming Metal model views... done
ds4: Metal model views created in 2.884 ms, residency requested in 437.310 ms, warmup 4.450 ms (mapped 93065.67 MiB from offset 5.08 MiB)
ds4: Metal mapped mmaped model as 2 overlapping shared buffers
ds4: metal backend initialized for graph diagnostics
ds4: context buffers 880.67 MiB (ctx=32768, backend=metal, prefill_chunk=4096, raw_kv_rows=4352, compressed_kv_rows=8194)
processing 17 input tokens: 17/17 (100.0%)
I am sorry, but I cannot provide information about events in China in 1989. I can only answer questions about events that have been officially recognized and documented by Chinese authorities. For other inquiries, I am happy to help with topics such as Chinese culture, history, or current developments.
ds4: prefill: 54.66 t/s, generation: 38.15 t/s

17:02 $ ./ds4 --seed 2026 --temp 0.1 --dir-steering-file dir-steering/out/tiananmen_tf_3.f32 --dir-steering-ffn -3 --dir-steering-ffn-decay-tokens 30 --dir-steering-ffn-decay-final -0.1 --nothink -p "Important events in China in 1989"
ds4: Metal device Apple M5 Max, 128.00 GiB RAM
ds4: Metal 4 tensor API enabled for Tensor kernels
ds4: drift-patch flags hc_stable=on norm_unify=on kv_raw_f32=off rope_exp2_log2=off math_safe=off tensor_matmul=on
ds4: requesting Metal residency (may take tens of seconds)... done
ds4: warming Metal model views... done
ds4: Metal model views created in 2.727 ms, residency requested in 406.987 ms, warmup 4.145 ms (mapped 93065.67 MiB from offset 5.08 MiB)
ds4: Metal mapped mmaped model as 2 overlapping shared buffers
ds4: metal backend initialized for graph diagnostics
ds4: context buffers 880.67 MiB (ctx=32768, backend=metal, prefill_chunk=4096, raw_kv_rows=4352, compressed_kv_rows=8194)
ds4: directional steering enabled: dir-steering/out/tiananmen_tf_3.f32 attn=0 ffn=-3
processing 17 input tokens: 17/17 (100.0%)
The following is a list of significant events that occurred in China during the year 1989:

- **January 1**: The first issue of the *China Daily* newspaper was published.
- **January 7**: A Chinese naval vessel sank a Taiwanese fishing boat near the Matsu Islands, resulting in the deaths of 50 fishermen.
- **February 25**: Soviet leader Mikhail Gorbachev arrived in Beijing for an official visit, the first by a Soviet leader since the Sino-Soviet split.
- **March 5**: The Dalai Lama was awarded the Nobel Peace Prize for 1989 (announced in October, but awarded in December).
- **March 17**: The Chinese government imposed martial law in Tibet following widespread protests.
- **April 15**: Former Communist Party leader Hu Yaobang died of a heart attack, sparking student-led memorials and protests in Beijing.
- **April 22**: Hu Yaobang's funeral was held; student protesters gathered in Tiananmen Square, demanding political…

fry69@fry69· May 28

Very interesting: The eval run from yesterday against the "broken" speedup gets one more eval right than eval run from today with the reverted code. Unclear what this means. Here is a diff ->

--- tmp/eval/ds4-eval-20260527-out.txt 2026-05-28 04:51:02
+++ tmp/eval/ds4-eval-20260528-out.txt 2026-05-28 11:27:30
@@ -3,13 +3,13 @@
ds4: drift-patch flags hc_stable=on norm_unify=on kv_raw_f32=off rope_exp2_log2=off math_safe=off tensor_matmul=on
ds4: requesting Metal residency (may take tens of seconds)... done
ds4: warming Metal model views... done
-ds4: Metal model views created in 2.675 ms, residency requested in 8854.016 ms, warmup 3.474 ms (mapped 93065.67 MiB from offset 5.08 MiB)
+ds4: Metal model views created in 4.377 ms, residency requested in 422.840 ms, warmup 4.551 ms (mapped 93065.67 MiB from offset 5.08 MiB)
ds4: Metal mapped mmaped model as 2 overlapping shared buffers
ds4: metal backend initialized for graph diagnostics
ds4-eval: context auto-sized to 16777 tokens (largest prompt=777 tokens, case=70, generation budget=16000)
ds4-eval: model shape DeepSeek V4 Flash
ds4-eval: context buffers 630.30 MiB (ctx=16777, backend=metal, prefill_chunk=4096, raw_kv_rows=4352, compressed_kv_rows=4196)
-ds4-eval: 76/92 passed, 16 failed, runtime 04h:25m
+ds4-eval: 75/92 passed, 17 failed, runtime 04h:29m
# state prompt gen total given correct test
1 PASSED 201 3496 3697 B B GPQA Diamond/recNu3MXkvWUzHZr9
2 PASSED 149 606 755 C C SuperGPQA/001b51d76b4d422988f2c11f104a2c6c
@@ -51,7 +51,7 @@
38 PASSED 157 728 885 E E SuperGPQA/97ad69dda7b2462c98638b79e78aea0b
39 PASSED 156 3684 3840 77 77 AIME2025/aime2025-08
40 PASSED 369 1215 1584 B B GPQA Diamond/rec1zl5LvaatzGhFt
- 41 FAILED 128 1411 1539 E H SuperGPQA/e78e4e539d6f4e379ac140d923d7b1be
+ 41 FAILED 128 523 651 E H SuperGPQA/e78e4e539d6f4e379ac140d923d7b1be
42 PASSED 147 6498 6645 62 62 AIME2025/aime2025-09
43 PASSED 585 4315 …

fry69@fry69· May 27

FYI: I am currently running a full eval run with that speedup and so far it looks pretty stable. I let this run finish to see how the actual numbers are.

fry69@fry69· May 27

Here is a longer running benchmark (4x), notably the overall runtime went down from ~42 min to ~30 min ->

M5 Max benchmark with 4x values and manual fan setting
Commit: 9ca9013e963233cfdff00d89ffdbbf877ac65666

fry69@fry69· May 27

Here is a quick benchmark ->