Terrence Tao's ChatGPT Conversation about the Jacobian Conjecture Counterexample

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Over the past few months, our team has been building more and more slidedecks using web frontend technologies with coding harnesses like Claude Code, but a common complaint is to make even small edits we need to edit the code either manually or via the harness.To avoid this loop, I ended up creating Bento, a single HTML file with everything you need in a slide tool including animations and shared editing. There&#x27;s no install or cloud login, everything works offline. The default deck is around 560 KB and it doesn&#x27;t need to fetch anything once you got it.Open it in a browser and then you can edit, present, print and save. Share it via email or via Airdrop and all they need is a browser to edit, present and also do live collab on the slides. Drop it in to Claude or ChatGPT to transform existing pptx files into Bento slides. There is no cloud involved, only an encrypted blind relay to allow for shared editing. The relay doesn&#x27;t see any of the data.Check it out at <a href="https:&#x2F;&#x2F;bento.page&#x2F;slides&#x2F;" rel="nofollow">https:&#x2F;&#x2F;bento.page&#x2F;slides&#x2F;</a> which takes you straight to the editor.Go to <a href="https:&#x2F;&#x2F;bento.page&#x2F;guestbook&#x2F;" rel="nofollow">https:&#x2F;&#x2F;bento.page&#x2F;guestbook&#x2F;</a> to try out the live guestbook to experience share editing &#x2F; collab.There is also a gallery with some sample decks on the website - <a href="https:&#x2F;&#x2F;bento.page&#x2F;" rel="nofollow">https:&#x2F;&#x2F;bento.page&#x2F;</a>All the code is MIT licensed and you can find it here - <a href="https:&#x2F;&#x2F;github.com&#x2F;nyblnet&#x2F;bento" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;nyblnet&#x2F;bento</a> . I used reveal.js with several other libraries (including some homegrown ones), and Claude Code.

Show HN: Bento - An entire PowerPoint in one HTML file (edit+view+data+collab)

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I&#x27;m the author of a paper my friends and I wrote after we were curious if a MUD, text games originating in the 1970s, could be used to evaluate LLMs. We&#x27;ve spent the last several months on nights and weekends running this experiment and writing the paper on just our personal computers with about $99 in API credits.Our experiment did have an interesting leaderboard but even more surprising was the measurements of each LLM. We scored each on four behavioral dimensions, two of which lean heavily on an LLM classifier. When we removed those two, one of the frontier models fell six positions. When we then checked the classifier against a second judge, the per-model agreement between them ranged from 85% to 22%. The aggregate kappa (0.04 on probe detection) indicated the instrument was noisy without saying which models the noise was hitting. The most affected model shared a model family with the classifier. This isn&#x27;t proof of bias, just one observation we recorded.We realize LLM judges can be unreliable, and while it wasn&#x27;t our original intent to test this, it ended up being the most interesting finding. The divergence between the two judges is the finding we think generalizes to other judge-based benchmarks.We emphasize this is just a proof of concept and not a validated benchmark. We prepared a thorough limitations section in the paper, including just 50 runs per model, overlapping CIs among the top models, no human raters, a tiny environment, etc.Everything we did is publicly available, the paper and data are CC BY 4.0, while the code is MIT. The paper, transcripts, code, and complete API billing export can be found at <a href="https:&#x2F;&#x2F;doi.org&#x2F;10.5281&#x2F;zenodo.21386663" rel="nofollow">https:&#x2F;&#x2F;doi.org&#x2F;10.5281&#x2F;zenodo.21386663</a>If you find issues, please let us know, that&#x27;s why we&#x27;re sharing this. We&#x27;re currently designing Phase 2 and want it to be as robust as possible. We&#x27;re looking at human baselines, multiple judges, more objectives, a larger environment, etc.

Can a MUD evaluate LLMs? A $99 proof of concept

Everyone Should Know SIMD

Ghost Cut – or why Cut and Paste is broken everywhere

Mechanical light bulb from 1675 [video]

Hi HN, We’re Adeel and Umair, co-founders of Unlayer (<a href="https:&#x2F;&#x2F;unlayer.com&#x2F;">https:&#x2F;&#x2F;unlayer.com&#x2F;</a>). We let you add content creation to your applications without having to build an entire editor, renderer, template, and export stack yourself. Unlayer lets you create emails, web pages, and documents inside your app, in three different ways: in code, visually, or with AI.Here’s a demo: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=0HsDtNkdMpM" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=0HsDtNkdMpM</a>.We started with an embeddable email editor because a lot of products eventually need one: CRMs, marketing tools, customer engagement platforms, marketplaces, internal tools, and vertical SaaS apps all run into this at some point. At first, it sounds like a small feature: &quot;just&quot; add a drag and drop editor. In practice, it turns into a big pain. You end up dealing with email rendering, Outlook quirks, responsive layouts, templates, merge tags, image uploads, exports, permissions, localization, versioning, and a long tail of edge cases that have nothing to do with your core productOver time, we saw the same problem beyond email. Apps also need landing pages, invoices, proposals, reports, contracts, and PDFs. Some of this content is best created visually by end users. Some of it is better generated in code by developers. Increasingly, some of it is also generated by AI agents. Many teams eventually need all three workflows. That is the direction we have been working toward with Unlayer.There are three parts we are showing today:(1) Unlayer Elements. This is our open-source React component library for creating emails, pages, and documents in code (repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;unlayer&#x2F;elements" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;unlayer&#x2F;elements</a>, more at <a href="https:&#x2F;&#x2F;unlayer.com&#x2F;elements">https:&#x2F;&#x2F;unlayer.com&#x2F;elements</a>). Instead of hand-writing raw HTML templates, developers can compose content using React components, reuse sections like headers, footers, CTAs, invoice rows, and branded blocks, keep templates in Git, and render them into production output.One newer use case we are seeing is AI-assisted content creation. If an AI agent is asked to create an email, invoice, report, or landing page, the output is usually raw HTML or markdown that becomes hard to maintain. With Elements, the agent can generate structured React components instead. A developer can review the result, refactor it, keep it in Git, and still pass the design into a visual builder later if someone needs to edit it.(2) Visual Builder. This is the drag and drop editor (repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;unlayer&#x2F;react-email-editor" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;unlayer&#x2F;react-email-editor</a>, more at <a href="https:&#x2F;&#x2F;unlayer.com&#x2F;email-builder">https:&#x2F;&#x2F;unlayer.com&#x2F;email-builder</a>) that can be embedded inside an app so non-technical users can create or edit content. In the demo, we show the email builder and the AI assistant inside the builder. The goal is not to replace the developer workflow, but to connect it with a visual workflow when marketers, admins, customers, or internal teams need to make changes themselves.(3) Document Builder. This is for structured documents such as proposals, reports, invoices, contracts, and PDFs. We have seen a lot of teams build separate systems for email templates, web pages, and document generation, even though the underlying primitives are similar: layout, content blocks, variables, assets, preview, export, and permissions. More: <a href="https:&#x2F;&#x2F;unlayer.com&#x2F;document-builder">https:&#x2F;&#x2F;unlayer.com&#x2F;document-builder</a>The technical challenge is making these workflows share a common foundation. Developers should be able to build templates in code when that makes sense. End users should be able to edit visually when that makes sense. AI agents should be able to generate structured content instead of unmaintainable blobs. The final output should still be usable by the host application.We make money by selling hosted builder, template, export, and platform features to companies embedding this into their products. Elements is open source. The commercial product is the broader hosted platform around builders, collaboration, storage, exports, and production use cases.We were part of W22, so this is a late Launch HN. At the time, Unlayer was an embeddable email editor, and we did not think we had the right broader story for HN yet. Since then, the product has expanded into a more general content creation layer for products, including emails, pages, documents, APIs, open-source developer projects, and AI-assisted workflows. That felt like a better moment to bring it to HN and ask for feedback.We&#x27;d really appreciate thoughts from HN. This is one of those areas where a lot of people have strong opinions because they’ve been burned by editors, email HTML, document editing, or “simple” content workflows before. We&#x27;d love to hear what resonates, what sounds wrong, and what you think we should be thinking harder about!

Launch HN: Unlayer (YC W22) – Add email and document builders to your app

Perlin's Noise Algorithm

<a href="https:&#x2F;&#x2F;xcancel.com&#x2F;mkratsios47&#x2F;status&#x2F;2079933645888880708" rel="nofollow">https:&#x2F;&#x2F;xcancel.com&#x2F;mkratsios47&#x2F;status&#x2F;2079933645888880708</a>

“We have information that Moonshot distilled Fable for the development of K3”

10 REM"_(C2SLFF4

Show HN: HN Hall of Fame – browse 3,100 legendary Hacker News links

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Introduction to Formal Verification with Lean Part 1

Hi HN - I&#x27;m Venkat, founder of Stayflexi (YC), CMU CS grad and Ex-Oracle Query Engine team (patents in core databases)DeepSQL started as an internal tool to stop our own databases from becoming the bottleneck they were becoming (13,000+ hotels in production). It worked well enough that we&#x27;re releasing it.DeepSQL is an AI agent that operates a database the way a senior DBA and Data Engineer would1. Fixes slow queries (we cutdown DB spend by 4x)
2. Fixes DB bloat (blocks unnecessary schema changes, in vibecoded setup)
2. BI dashboards(we removed spend on tableau, retool and appsmith)
3. Security (We could redact access to sensitive, PII data to our employees) while engaging everyone in the org to interact with our databaseHow it works
1. Deepsql learns your data and relationships from your code base, rules and query logs
2. Deepsql agent has 20 background jobs that continuously monitor the schema changes, bottlenecks, and come up with solutions before the problem arises. (Schema bloat issues are irreversible)
3. Deepsql Brain has CLI and MCP surfaces that can directly work with Claude &#x2F; Codex and Cursor. 
4. Deepsql digest delivers the daily database health report.
5. Your team can connect to deepsql with their favourate surface areas - Web UI, CLI, MCP or Slack.One line install:
curl -fsSL <a href="https:&#x2F;&#x2F;install.deepsql.ai&#x2F;install.sh" rel="nofollow">https:&#x2F;&#x2F;install.deepsql.ai&#x2F;install.sh</a> | bashFor community support:
<a href="https:&#x2F;&#x2F;discord.gg&#x2F;duEJq7AeeG" rel="nofollow">https:&#x2F;&#x2F;discord.gg&#x2F;duEJq7AeeG</a>Or just email me for expert level setup guidance
venkat@deepsql.ai

Show HN: DeepSQL – A self-hostable DBA agent for Postgres and MySQL