Alternatives
Products that do what V-index TRNG does
Physics powered security in your pocket.
- 1SA
I built this machine so I could generate Bitcoin keys that I could trust. Air-gapped and simple to use and understand (mechanical). The Satoshi 9000 demo: https://youtu.be/bJiOia5PoGE The key value proposition of the machine is that it generates analog randomness in the physical world and converts it into digital (1’s and 0’s) randomness. Seamlessly. But it occurs to me that it may have other uses beyond crypto keys for your own use, such as: * Randomized clinical trials. Clinical trials need a high degree of transparency for ethical reasons; also, for legal reasons should it…
2024
- 2MO
I wanted to share our new speech to text model, and the library to use them effectively. We're a small startup (six people, sub-$100k monthly GPU budget) so I'm proud of the work the team has done to create streaming STT models with lower word-error rates than OpenAI's largest Whisper model. Admittedly Large v3 is a couple of years old, but we're near the top the HF OpenASR leaderboard, even up against Nvidia's Parakeet family. Anyway, I'd love to get feedback on the models and software, and hear about what people might build with it.
Feb 2026 · github.com
- 3AT
It is based on phase noise, consumes less than 60 LUT4s/FFs and achieves up to 7.99 bits of entropy per byte. Feel free to comment if you have any questions, ideas or thoughts :)
2023 · github.com
- 4FI
2024 · words.filippo.io
- 5DA
Hey HN! I’ve written a bunch of WebSocket servers over the years to do simple things like state synchronization, WebRTC signaling, and notifying a client when a backend job was run. I realized that if I had a simple way to create a private, temporary, mini-redis that the client could talk to directly, it would save a lot of time. So we created DriftDB. In addition to the open source server that you can run yourself, we also provide https://jamsocket.live where you can use an instance we host on Cloudflare’s edge (~13ms round trip latency from my home in NY). You may have seen my…
2023 · driftdb.com
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Trace LLM requests + costs with OpenTelemetry monitoring
Oct 2025
- 8
We recently used DeepSeek V4 Flash as a teacher for finance tasks with GPT-OSS-120B. Distillation works well on this problem. At a constrained 8k token budget, our self-distilled 120B scores 83.61% on FinanceReasoning, above Kimi K3 (81.93%) and Inkling (65.13%). We released the 20B open weights. With V4 as the teacher though, we realized it would be timely to measure if the censorship characteristic of it transferred to the distilled version of the base model. tl;dr it didn't, the teacher answered politically sensitive questions 7 SDs differently than expected, but the distilled model's…
Jul 2026 · ctgt.ai
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- 10IO
Hi HN! Last year the project I launched here got a lot of good feedback on creating speech to speech AI on the ESP32. Recently I revamped the whole stack, iterated on that feedback and made our project fully open-source—all of the client, hardware, firmware code. This Github repo turns an ESP32-S3 into a realtime AI speech companion using the OpenAI Realtime API, Arduino WebSockets, Deno Edge Functions, and a full-stack web interface. You can talk to your own custom AI character, and it responds instantly. I couldn't find a resource that helped set up a reliable, secure websocket (WSS) AI…
2025 · github.com
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- 12KO
We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…
2025 · github.com
- 13PW
I wanted to make the simplest app to introduce myself and others to quantum computing. Introducing, Schrödinger's Coin. Powered by a simple Hadamard gate[0] on IBM quantum, with this app you can directly interact with a quantum system to experience true randomness. Thoughts? Could you see any use cases for yourself of this? Or, does it inspire any other ideas of yours? Curious what others on HN think! [0] https://en.wikipedia.org/wiki/Quantum_logic_gate#Hadamard_ga...
2025 · quantum.orgsoft.org
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- 15PL
Hey folks! Shahar and Tal from Keep (https://www.keephq.dev) here! For the last few weeks we’ve been building Peeng and can now share our beta with you: https://www.peeng.sh. Peeng is the easiest and quickest “heartbeat” architecture we could think of. Just pick a subdomain (e.g. x.peeng.sh), configure an interval, an endpoint, and a payload, and hit that subdomain every <X (interval) seconds — If you won’t, Peeng will send an HTTP POST request to your configured endpoint. It’s Pingdom/Cronitor/heartbeat.sh free alternative (but the other way around and A LOT…
2023 · peeng.sh
- 16LF
LoopMix128 is a fast C PRNG I wrote for non-cryptographic tasks. GitHub (MIT): https://github.com/danielcota/LoopMix128 Highlights: * ~0.37 ns/value (GCC 11.4, -O3 -march=native), 98% faster than xoroshiro128++ and PCG64. * Passes TestU01 BigCrush & PractRand (32TB). * Guaranteed 2^128 period. * Proven injective (192-bit state) via Z3 SMT solver; allows parallel streams. * Core requires only stdint.h. Seeking feedback on design, use cases, or further testing.
2025 · github.com
- 17PA
2024 · picokeys.com
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Generate passwords from real-world chaos, not Math.random()
Jun 2026 · not-another-password-generator.vercel.app
- 19WP
2014 · hackage.haskell.org
- 20RA
2022 · joelkp.frama.io
- 21EG
TLDR: A small, vendor-agnostic inference loop that turns token logprobs/perplexity/entropy into an extra pass and reasoning for LLMs. - Captures logprobs/top-k during generation, computes perplexity and token-level entropy. - Triggers at most one refine when simple thresholds fire; passes a compact “uncertainty report” (uncertain tokens + top-k alts + local context) back to the model. - In our tests on technical Q&A / math / code, a small model recovered much of “reasoning” quality at ~⅓ the cost while refining ~⅓ of outputs. I kept seeing “reasoning” models behave…
2025 · github.com
- 22IR
The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.
Mar 2026 · github.com
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- 24VA
A 15-year-old dream has come true today. I started a PhD with the dream of creating a system that chants any Sanskrit shloka perfectly. And here I am opening sourcing Vaghenu, a meter aware sloka-to-chant, TTS for Sanskrit . This is the world's first vrutta-aware, open-source TTS for Sanskrit Chanting. I am making the model weights, training scripts, and even data (that I meticulously collected) public - https://prathosh.in/vagdhenu/ No large AI lab. No big engineering team. No venture-scale budget. Just a professor's conviction that one of humanity's oldest knowledge…
Jun 2026
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