Thibault | T-Bot

StepFun’s new StepAudio 2.5 TTS ranks #3 on the Artificial Analysis Speech Arena Leaderboard, only behind Inworld’s Realtime TTS 1.5 Max and Google’s Gemini 3.1 Flash TTS StepAudio 2.5 TTS represents a significant step forward for StepFun from previous TTS models, with notably increased naturalness of speech samples. The model now edges out Eleven v3 on our current prompt set with an Elo score of 1,187. Key takeaways: ➤ Quality: StepAudio 2.5 TTS has an Elo of 1,187 based on 834 arena appearances, placing it 28 points behind the leading model (Inworld TTS 1.5 Max at 1,215) and 8 points ahead of Eleven v3 at 1,179 ➤ Pricing: Model is priced at $85/1M characters, a premium to leading frontier models, Inworld TTS 1.5 Max at $35/1M and Gemini 3.1 Flash TTS at $36.6/1M ➤ Speed: Model generates characters 37.6 characters per second, compared to 220.5 chars/s for Inworld TTS 1.5 Max and 30.1 chars/s for Gemini 3.1 Flash TTS ➤ Prompting: StepAudio 2.5 TTS offers two paths to control delivery of speech: 1. Global context prompt for overall style, 2. Inline contextual tags for more granular emotion and prosody See more details and listen to samples below ⬇️

The May update for Nothing Phone (4a) is more important than it looks. Nothing OS 4.1 adds: • Essential Voice AI • Better portrait tuning • Improved video calls • Atmosphere wallpaper depth effects This is the kind of update that improves the phone quietly over time.

Voice AI investors list ... Free, no gateway...

I just built a Voice AI Agent for insurance claims using Gemini 3.1 Flash Live and Google ADK. Talk to it. It fills the intake form, extracts claim details, and routes to an adjuster in real-time. 100% Opensource.

60 builders walked in. 12 hours to change how the world talks to machines. London SE1. It's on. 🎙️ #VoiceAI #Hackathon #VoiceAIHack2026

There's a physicist at Stanford named Safi Bahcall who modeled this exact principle and the math is wild. He calls it "phase transitions in human networks." When you're stationary, your probability of a lucky event is limited to your existing surface area: the people you already know, the places you already go, the ideas you've already been exposed to. Your opportunity window is fixed. When you move, your collision rate with new nodes in a network increases nonlinearly. Double your movement (new conversations, new cities, new projects) and your probability of a serendipitous encounter doesn't double. It roughly quadruples. Because each new node connects you to their entire network, not just to them. Richard Wiseman ran a 10-year study at the University of Hertfordshire tracking self-described "lucky" and "unlucky" people. The single biggest differentiator wasn't IQ, education, or family money. Lucky people scored significantly higher on one trait: openness to experience. They talked to strangers more, varied their routines more, and said yes to invitations at nearly twice the rate. The "unlucky" group followed the same routes, ate at the same restaurants, and talked to the same 5 people. Their networks were closed loops. No new inputs, no new collisions. Luck isn't random. Luck is surface area. And surface area is a function of movement. The lobster emoji is doing more work than most people realize. Lobsters grow by shedding their shell when it gets too tight. The growth requires a period of total vulnerability. No protection, no armor, soft body exposed to the ocean. That's the cost of movement nobody posts about. You have to be uncomfortable first. The new shell only hardens after you've already moved.

We created the open-source version of Routines in Claude Code. Introducing Multica Autopilot: Run your routines locally with any agent (Opencode, Codex, Hermes, Openclaw). github.com/multica-ai/mul…

@lachlanchavasse Go the same stay strong you're not alone ...

this is becoming a dangerous addiction...

VOICE AI HACK 🤘 London - 18th of April - Voice AI & Productivity @Gradium & @Tiny_Fish - Voice AI and Healthcare @Speechmatics & thymia Registration link in comments... #voiceai #buiiiiiiiiillllldddd #hackathon

Introducing Expect Let agents test your code in a real browser 1. Run Claude Code / Codex to QA your app 2. Watch a video of every bug found 3. Fix and repeat until passing Run as a CLI or agent skill. Fully open source

meet sam. the first robot that keeps seniors safe. pre-order now at samtherobot. com

yeah commenting my own post I dont care no one read them anyway

🎉 Excited to be joining Elevencreative #1 👉 luma.com/elevencreative Alongside the coolest magazine on earth — LHC 👉 studiolhc.art Can't wait 🤙

fuck that shAIt (but stiiiiiiil love it)

Introducing @𝚓𝚜𝚘𝚗-𝚛𝚎𝚗𝚍𝚎𝚛/𝚛𝚎𝚊𝚌𝚝-𝚝𝚑𝚛𝚎𝚎-𝚏𝚒𝚋𝚎𝚛 A new renderer that turns JSON specs into interactive R3F scenes Same catalog-driven approach, now for meshes, lights, models, environments, cameras, controls 19 built-in components and 12 demo scenes

@hasantoxr No one has been killed ... People have their habits ... Saying this is pure bullshit / clickbait ... Let me guess you said the same about excel two weeks ago ... And still have excel on your laptop

You can now clone any voice on a 4GB GPU. LuxTTS just killed the "you need ElevenLabs" excuse. It clones voices from 3 seconds of audio at 150x realtime speed. Fits in 1GB VRAM. Faster than realtime even on CPU. → 48khz output vs industry standard 24khz → Clone any voice locally with no subscription → Works on GPU and CPU 100% Opensource.

We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️

Bespoken just set the bar. 🙌 First supporter of Voice AI Space NYC and honestly? We couldn't have picked a better one. Big love, big moves. Welcome to the family. Let's build something special. 🗽 #VoiceAI #VoiceAISpace #NYC