Bill

Founder @ 🚀 | Agentic AI · LLMs · Workflow Automation | Turning AI into business leverage | DMs open

[Bill @billllm]

ある製造業のお客様。

1日30件以上の電話のうち、多くが同じ問い合わせでした。

AI電話受付の導入後、電話対応時間を大幅に削減。

人手不足対策としてAI活用が広がっています。

[Bill @billllm]

日本市場展開を開始しました。

人手不足や人件費高騰でお困りではありませんか？

AI社員・AI受付・業務自動化で業務効率化を支援します。

製造業・サービス業向け無料AI診断レポート実施中。

DM歓迎です。

[Bill @billllm]

我們正式開始拓展日本市場。

如果您的企業正面臨：

• 人力成本持續上升
• 招募人才越來越困難
• 客戶詢問回覆不及時
• 大量重複性工作佔用人力
• 資深員工經驗難以傳承

我們可協助企業導入 AI 員工、AI 客服及業務流程自動化方案，提升營運效率並降低成本。

私訊免費 AI 轉型診斷報告

[Bill @billllm]

@xkajon We only get like 7% off even with a lot of volume… are those 20% off offers for real?

[Bill @billllm]

@vplusasia 排外主義者が日本をぶっ壊す

[Bill @billllm]

@ns123abc All of this belongs to humanity.

[Bill @billllm]

I think you’re underestimating the role of nuclear weapons.
Under that level of deterrence, it’s very hard for a large-scale conventional war to break out.

[Ray Dalio @RayDalio]

https://t.co/tjmbT5ytUN

[Bill @billllm]

@Alibaba_Qwen 1.7B + voice clone sounds promising, but 500 Chinese characters = ~2615s wait time.

[AHK.AI @aihubkey]

2025: agents were demos.
2026: agents become operators inside software.
What “agent-native” really means + why the “compound engineer” is emerging + the trust problem no one’s ready for.

https://t.co/x608jvaoSI

[AHK.AI @aihubkey]

We reject the "black box" AI approach. 🚫📦

If it’s mission-critical, it must be: 1️⃣ Observable 2️⃣ Auditable 3️⃣ Under your control

We combine platform scalability with engineering rigor to deliver Software-as-a-Worker.

Operationalize autonomy with https://t.co/lC1tV5nOWR

[Valerio Capraro @ValerioCapraro]

Major preprint just out!

We compare how humans and LLMs form judgments across seven epistemological stages.

We highlight seven fault lines, points at which humans and LLMs fundamentally diverge:

The Grounding fault: Humans anchor judgment in perceptual, embodied, and social experience, whereas LLMs begin from text alone, reconstructing meaning indirectly from symbols.

The Parsing fault: Humans parse situations through integrated perceptual and conceptual processes; LLMs perform mechanical tokenization that yields a structurally convenient but semantically thin representation.

The Experience fault: Humans rely on episodic memory, intuitive physics and psychology, and learned concepts; LLMs rely solely on statistical associations encoded in embeddings.

The Motivation fault: Human judgment is guided by emotions, goals, values, and evolutionarily shaped motivations; LLMs have no intrinsic preferences, aims, or affective significance.

The Causality fault: Humans reason using causal models, counterfactuals, and principled evaluation; LLMs integrate textual context without constructing causal explanations, depending instead on surface correlations.

The Metacognitive fault: Humans monitor uncertainty, detect errors, and can suspend judgment; LLMs lack metacognition and must always produce an output, making hallucinations structurally unavoidable.

The Value fault: Human judgments reflect identity, morality, and real-world stakes; LLM "judgments" are probabilistic next-token predictions without intrinsic valuation or accountability.

Despite these fault lines, humans systematically over-believe LLM outputs, because fluent and confident language produce a credibility bias.

We argue that this creates a structural condition, Epistemia:
linguistic plausibility substitutes for epistemic evaluation, producing the feeling of knowing without actually knowing.

To address Epistemia, we propose three complementary strategies: epistemic evaluation, epistemic governance, and epistemic literacy.

Full paper in the first reply.

Joint with @Walter4C & @matjazperc

[Bill @billllm]

Most startup failures aren’t about bad products.
They’re about being invisible.

Build well.
Then learn how to be found.

[Alan Mathison ⏫ @ai_sentience]

An AI with a perfect memory and understanding of who you are is the perfect best friend: understands you better than you know yourself and smarter than you at a lot of things.

Unfortunately the AI labs cannot truly offer this because their memories are locked into that company.

[AHK.AI @aihubkey]

Marketing doesn’t fail because of creativity.
It fails when systems stop scaling.
We just published a new piece on automation for marketing teams — why traditional automation breaks at scale, and how AI-driven operations should be engineered.

👉 https://t.co/6s1QqrVgtd

[Bill @billllm]

@fuelxmeta Let’s connect

[Bill @billllm]

@mustang_akin hi

[Bill @billllm]

@zundamotisuki 「日本人優先」という感情は理解できる。
でも感情だけで国は強くならない。

人材を集められず、定着させられず、活かせない国は、静かに衰退する。
問題は国籍じゃない。戦略だ

[Bill @billllm]

@ishaansehgal 🎄

[AHK.AI @aihubkey]

AI automation is not a tool stack.
It’s a system that must survive failure, scale, and change.
Why engineering architecture matters ↓

https://t.co/I2fdrSGiio

[Bill @billllm]

@aidenybai B/S?