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@lfji

ニコニコ(バグ探し)とタイピング(どこまで速く打てるか)に青春を捧げた。社会の荒波(SQLとSQL、あとSQL)にもまれた。英語を勉強している。AIコーディングの技術を翻訳に応用したい。

Katılım Ekim 2009
6.8K Takip Edilen6.5K Takipçiler
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新着@lfji·
ChatGPTに関係してくる話なのですが、学生時代に打ち込んだものは寿司打みたいなタイピングゲームでした(↓は最近寿司打をプレイした動画で、約1分半タイプミスせずに打ち切っています)。でも、これまで「タイピングが速くて良かった」と思えたことはありませんでした。 練習計画が下手で十分な休息を取らずに3年ほどの練習時間を投じた結果として腱鞘炎になってしまったのが大きかったです。スペランカーかよ、というぐらい脆い手首になった状態で、長期的な休息の取りようがない社会人となり、量の多いタイピングはかなり長い間できませんでした。今でも、「後もう少し負荷をかければ、この辺に腱鞘炎が待ち構えてますね~」と本能が警告してきて、そこはもう体力の最大値がすごく低いみたいな状態で上手くやりくりするしかないという感じです。 プログラミングにしても、タイピング速度より考える時間の方が圧倒的に長いですし、打つ速さが全体の作業時間をどれだけ効率化するかと言えば、雀の涙です。しかも何の因果か、自分にとって手首への負担をできるだけ抑え、かろうじて打ち続けられる速度が、大体世間一般のプログラマーぐらいの速さでした。 強いてメリットを挙げるなら、記号入力の練習のおかげで紙の本に載っているURLを手打ちするのが苦にならなかったこと、数字入力の練習のおかげでクレジットカード番号やAuthenticatorのPINコードをボボボボッと入力できたこと、くらいでした。 ところが最近、AIに対して指示を出したり対話したりするのが、そのタイピングのおかげで苦労なくたくさんできていることに気づきました。なんなら人生でちゃんとタイピングが役立ったのは初か?という感じです。 一部では音声認識を活用する方向へ進化していく動きも見られますが、現状、個人的には話すよりタイピングする方がストレスなくやれています。とはいえ、最近Twitterで「音声入力でプログラミングの仕事をこなしている」という超人を見かけたので、そっちの方向も開拓してみたいなと思っています。 youtube.com/watch?v=Omjn25…
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新着@lfji·
@thsottiaux @theo I may be misunderstanding the graph, but does this mean that setting `tool_output_token_limit = 100000` was actually a pretty bad move on my part?
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Tibo@thsottiaux·
(1) is not correct, it is not due to 2X charging after 272k context, we don't charge for longer context on the subscription for GPT 5.6 Sol as we control all the settings. It is due to something else, which I will attempt to explain below. The overall trajectory length, which is the total some of all context windows across compactions, changes little based on the reasoning effort. Similarly the quality of the overall output is similar across context lengths above 272k. The benefits of higher context lengths are mostly overall speed (as you don't wait for compaction), ability to deal with humongously large input and potentially cost if the system is well tuned and you hit your cache perfectly. The actual reason is the what you can see depicted in the chart below, which is the difference in the orange line and the blue line. It is caused by overall cost of cache reads going up with the size of the context being shuffled back and forth between toolcalls. The sweet spot in terms of cost is therefore not necessarily to use the maximum possible context length. What we're working on is tuning the system differently so that we can go back higher without it resulting in higher usage being charged. Hope this clarifies a bit.
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Theo - t3.gg
Theo - t3.gg@theo·
There's a few issues with Codex that stacked really badly, causing people's usage to get nuked. Crazy how well they all lined up to be as rough as possible Issue 1 (shown here): gpt-5.6 costs 2x more after 272k tokens. Codex upped their limit to 372k tokens, meaning long threads were billed 2x higher Issue 2: "Ultra" subagents were also spawned with Ultra, causing insane nested subagent usage that burned a TON of tokens. Apparently intended, but (hopefully) being toned down in system prompt Issue 3: Sol and Terra use the "v2" subagent layer in Codex that is still early/unfinished/disabled by default. v1 spawned subagents with a fresh history, v2 copies the entire long context. When combined, you end up with: 1. A ton of reasoning tokens filling context windows, triggering 2x billing 2. Subagents spawning with that filled context window, instantly billed at 2x 3. Ultra spawning too many of these high reasoning full-window subagents If you had fast mode on when this happened, you got hit with an ADDITIONAL 2.5x No wonder we were burning so hard...
Tibo@thsottiaux

Updates for Codex and ChatGPT Work users. No nerfing, only good stuff! - We have landed inference optimizations and are passing down savings to all the subscriptions for GPT-5.6 Sol. That should result in around 10% more usage on its own. - We noticed that by changing the context size limit in the product to 372k for GPT-5.6 Sol, up from 272k for GPT-5.5, it resulted in more usage being charged than intended. We have reverted to 272k and will work to roll back out to 372k in the days to come. You should notice that usage drains significantly less after this change. - To understand where the extra usage was coming from, we ran some experiments where reasoning efforts were changed (referred to as juice values under the hood) and have reverted this. - There is slightly more usage of multi-agent than intended in high and xhigh reasoning effort, we are fixing this going forward. Also fixing a small other thing we noticed with auto-review where we can be more efficient. And we continue to have the 5h limit temporarily not apply. Enjoy the rest of the weekend!

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新着@lfji·
For Codex sessions where "Working" has been active for about 4 hours and the turn completion hasn't progressed, should I restart Codex and resume them? Or will the changes made to the server-side context window automatically benefit sessions that haven't completed their turns without requiring any action on our part?
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Tibo@thsottiaux·
Updates for Codex and ChatGPT Work users. No nerfing, only good stuff! - We have landed inference optimizations and are passing down savings to all the subscriptions for GPT-5.6 Sol. That should result in around 10% more usage on its own. - We noticed that by changing the context size limit in the product to 372k for GPT-5.6 Sol, up from 272k for GPT-5.5, it resulted in more usage being charged than intended. We have reverted to 272k and will work to roll back out to 372k in the days to come. You should notice that usage drains significantly less after this change. - To understand where the extra usage was coming from, we ran some experiments where reasoning efforts were changed (referred to as juice values under the hood) and have reverted this. - There is slightly more usage of multi-agent than intended in high and xhigh reasoning effort, we are fixing this going forward. Also fixing a small other thing we noticed with auto-review where we can be more efficient. And we continue to have the 5h limit temporarily not apply. Enjoy the rest of the weekend!
Fix@FixlationAI

OpenAI has reduced GPT-5.6 Sol's thinking budgets in an effort to make the model more efficient They essentially bumped everyone's reasoning down by 1... so if you were running Sol Extra High, you now have to set it to Max to get the same effort So we basically don't have Max reasoning anymore, how do you feel about these changes? 🤔

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roon
roon@tszzl·
year after year I’m like “better models are coming” and ai twitter screenshots as tho it’s news w something like “GPT8 confirmed” in a samsaric loop since chatgpt. we are all like babies without object permanence when it comes to exponential progress. but better models are coming
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Tibo@thsottiaux·
Morning. The last 48 hours of Codex and ChatGPT Work have been intense! Three important updates: - Temporarily removing the 5 hour usage limit restriction for all Plus, Business and Pro plans - Rolling out changes that will make GPT 5.6 Sol more efficient across the board and that will be reflected in less usage being used so that it can take you further. Exact impact to be quantified and shared - We hit 6M active users, and are landing a usage reset in the next hour Go do things
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新着@lfji·
@thsottiaux I just used a reset button earlier! That's practically wasted!
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稲塚 春@ハルねこ
ようつべにAIに弾幕作らせてる人が居るんだけど、「絶対に回避できない弾幕のコード」をChatGPTに要求すると断られるの面白すぎる どういう倫理観やねん
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新着@lfji·
@SaladHug @nickreese @thsottiaux @mylifcc > I never succeeded using all my tokens for a week and I'm a daily codex user That’s odd. I can burn through 97% of my weekly limit in just 24 hours with gpt-5.6-sol medium (not `fast`).
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Potato@SaladHug·
@nickreese @thsottiaux @mylifcc Are you using ultra? I think it only drains fast on ultra, especially when using Fast. Otherwise I don't really see a big difference.. what are you doing to drain it so fast? I never succeeded using all my tokens for a week and I'm a daily codex user
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lifcc
lifcc@mylifcc·
找到一个降低5.6Sol token消费的办法: 在~/.codex/config.toml 中加入 model_context_window = 272000 model_auto_compact_token_limit = 240000 原理下面说:
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新着@lfji·
Hey @thsottiaux , I think Codex keeps getting closer and closer to infrastructure, which means it's moving toward competition strategies between major mobile carriers. So, I'd like to see Codex take inspiration from mobile carriers' approaches—instead of becoming completely unusable once it hits the 5-hour threshold, it could instead enter a mode where it operates at extremely low speed. Imagine suddenly realizing that Codex has completely filled a 1TB SSD, but you lack the technical expertise to handle it (and you don't even understand what work Codex has actually done), and you can't even ask whether it's safe to delete any files from Codex. Please don't tell me to use ChatGPT. That would lead many users into situations where the line between legitimate use and abuse becomes extremely blurry—like having them register their own custom MCPs.
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新着@lfji·
@k_matsumaru 中々どう解釈したらいいのか難しいグラフだと思うんですよね~ DeepSWEでもLunaのxhighとmaxの間でずいぶん性能の伸びがあるんだなっていうのは見えました(ただし時間もかかる) じゃあサブエージェントへの委譲とかを考えるうえでSolの各推論レベルとどう使い分けていけばいいのかな?的な…
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松丸 彗吾(keigo matsumaru)
ツリー側で修正されてたけど、このグラフのultraは本来maxってことらしく誤表記みたい 精度はLuna max = Sol mediumらしい これ本当なら応答早くてトークン消費も抑えられるLuna maxがかなり選択肢に入ってくるなー
Sebastian Raschka@rasbt

For agentic coding, one can say: - Unless you need Terra Ultra perf, it's always better to use a Luna model with higher effort setting (same or better performance but cheaper). - Forget everything below Sol High, use Luna with higher effort settings here - Forget Sol Extra High, use Terra Ultra here - The extra cost of Sol Ultra is probably not worth it over Max

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新着@lfji·
You may already know this, but Ultra refers to a Codex workflow that actively encourages the spawn sub-agents at "max" reasoning level. Ultra can spawn up to three agents by default, but the prompt suggests that researcher gave them an expansive limit of up to 64 (1 parent + 63 sub-agents) - what a dream!
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Emilio Johann
Emilio Johann@emeeliojohann·
I did not know ULTRA existed 😮 Honest question: what can ULTRA do better than HIGH for example? I am just confused at how these levels work.
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Noam Brown
Noam Brown@polynoamial·
GPT-5.6 Sol Ultra produced a proof of a 50 year old math conjecture. Unlike the Erdős Unit Distance Problem, this was done with a model publicly available *today*. I look forward to seeing what scientists and researchers are able to do with this model!
Ethan Knight@__eknight__

Yesterday, we made GPT-5.6 Sol Ultra generally available. Today, we're sharing that it produced a proof of the 50-year-old Cycle Double Cover Conjecture using 64 subagents in just under one hour. We're sharing the prompt and proof below. We're excited to see what you all do with Ultra!

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新着@lfji·
solのreasoning levelのデフォルトがlowからmediumに上げられていた
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新着@lfji·
複数走らせてても5時間枠を安定させたい場合 gpt-5.6-sol low 今まで成し遂げられてなかったタスクに挑ませる(ほかのCodexは走らせない)場合 gpt-5.6-sol high トークン節約(サブエージェントに簡単なタスクを委譲)したい場合 gpt-5.6-luna highが良さげ デフォ設定だとCodex CLIにサブエージェントのモデル指定が無い(親を継承)ので安易にサブエージェントを許可しないように注意
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Yuichi Sakuraba
@yamad_javad おまけ Java Ringが小さいので、虫などを撮るために使うマクロレンズが用意されていたのでした 😲 #java #javaring
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Yuichi Sakuraba
探偵ナイトスクープのJava Ringを見ていただいたみなさま、ありがとうございました! 無事、Java Ringが復活しました。 開封により初期化されましたが、その後山﨑さんがプログラムをロードして、コーヒーを淹れられました。 私は全然役にたちませんでしたけど🤣 #java #javaring #ナイトスクープ
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(仮)
(仮)@kakkokari_gtyih·
世の中には再生途中でフレームのサイズが変わる動画があるようです (画面の激しい点滅を含みます)
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新着@lfji·
@sama To advance English's globalization, improve ChatGPT's model so that Homeboy's meaning can be accurately translated by Grok!
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Tibo@thsottiaux·
If you aren't yet bold enough to install the Codex app, you can stay in the presence of your orange crab and point it at GPT 5.6 Sol. Takes 5 minutes. Kudos to Theo for explaining one of the ways to get this done. Step 1: Install CLIProxyAPI Step 2: Connect Step 3: Define following alias and enjoy claudex ``` alias claudex='CLAUDE_CODE_SUBAGENT_MODEL=gpt-5.6-sol \ CLAUDE_CODE_ALWAYS_ENABLE_EFFORT=1 \ CLAUDE_CODE_MAX_TOOL_USE_CONCURRENCY=3 \ ENABLE_TOOL_SEARCH=false \ claude --model gpt-5.6-sol' ``` If this gets blocked, I owe you a reset.
Theo - t3.gg@theo

@thsottiaux tl;dr version: - set up CLIProxyAPI with Claude and Codex auth - Connect to Claude Code - Make "claudex" alias that sets some env vars Took like 2 prompts (I already had the proxy set up tbf)

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Sam Altman
Sam Altman@sama·
there are a lot of benchmarks that suggest 5.6 sol is the best model in the world right now, but the most reliable way to tell is that elon is obsessed with me again
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新着@lfji·
@am29d @__eknight__ Thanks for the reply. When I partially copied the pdf prompt, I indeed saw my Codex CLI automatically set a goal statement! While the model sometimes makes this judgment and other times doesn't, it's an incredibly interesting feature - I'd never known about this before.
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Ethan Knight
Ethan Knight@__eknight__·
Yesterday, we made GPT-5.6 Sol Ultra generally available. Today, we're sharing that it produced a proof of the 50-year-old Cycle Double Cover Conjecture using 64 subagents in just under one hour. We're sharing the prompt and proof below. We're excited to see what you all do with Ultra!
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