Alternatives
Products that do what TuringBot does
AI that discovers mathematical formulas from your data
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Solve math problems instantly with step-by-step solutions
2024
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Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make…
Jul 2026 · microsoft.github.io
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I've been building prototypes of new AI learning tools for months, but I recently learned that 3blue1brown open sourced his incredible math animation library, Manim, and that LLMs could generate code for it without any fine-tuning. So I made a tool that automatically generates animated math/science explanations in the style of 3blue1brown using Manim from any text prompt. Try it yourself at https://TMA.live (no signup required) or see the demo video here: https://x.com/i/status/1874948287759081608 The UX is pretty simple right now, you just write a…
2025 · tma.live
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Creating data visualizations with AI nowadays often means chat, chat and more chats...and writing long prompts can be annoying while they are also not the most effective way to describe your visualization designs. Data Formulator blends UI interaction with natural language so that you can create visualizations with AI much more effectively! You can: * create rich visualizations beyond initial datasets, where AI helps transforming and visualizing data along the way * iterate your designs and dive deeper using data threads, a new way to manage your conversation with AI. Here is a demo video:…
2024 · github.com
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Hi everyone, we are excited to share with you our new release of Data Formulator. Starting from a dataset, you can communicate with AI agents with UI + natural language to explore data and create visualizations to discover new insights. Here's a demo video of the experience: https://github.com/microsoft/data-formulator/releases/tag/0..... This is a build-up from our release a year ago (https://news.ycombinator.com/item?id=41907719). We spent a year exploring how to blend agent mode with interactions to allow you more easily "vibe" with your…
Nov 2025 · data-formulator.ai
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Save 30% of dev time - generate tests without writing code
2023
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2025 · mattsayar.com
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Hey HN, I’m a physicist turned quant. Some friends and I 'built' SymDerive because we wanted a symbolic math library that was "Agent-Native" by design, but still a practical tool for humans. It boils down to two main goals: 1. Agent Reliability: I’ve found that AI agents write much more reliable code when they stick to stateless, functional pipelines (Lisp-style). It keeps them from hallucinating state changes or getting lost in long procedural scripts. I wanted a library that enforces that "Input -> Transform -> Output" flow by default. 2. Easing the transition to Python: For many…
Feb 2026
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Hey HN, I don’t know who else has the same issue, but: Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI. Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts. In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing. This is an open & unconventional…
Feb 2026 · github.com
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Step-by-step math from a real engine — not AI guesswork
Jul 2026 · 8gwifi.org
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Hey HN! I've been curious about the history of computer science and decided to try to read Turing's 1936 paper where he conceptualizes the Turing Machine, etc. I had trouble understanding the paper, read The Annotated Turing by Charles Petzold (which is wonderful), but felt that reading a reference implementation would help formalize my understanding. When I couldn't find an open source implementation, I decided to write my own. The implementation includes: - Abbreviated tables (m-functions) - Conversions to Standard Descriptions and Description Numbers - A working universal machine - A…
2023 · github.com
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