
Jean-Charles Gautard
3.4K posts

Jean-Charles Gautard
@NWD_Blockchains
Chief #AI Officer / CTO at @MyDataNestApp | Scalez votre business avec votre contenu | Apprenez de mes erreurs et de mes debunkages #Automation #Web3 #Gaming


New version of the investigation into start-up Ultra.io’s $12m funding round, now on Medium 👇 @Ultra_Times/the-12-million-question-ultras-funding-claims-under-scrutiny-75d929170d2e" target="_blank" rel="nofollow noopener">medium.com/@Ultra_Times/t…


Yes, our gaming thesis failed. Yes, activity is close to zero. Yes, we're at our lowest point in 7 years. And yet we're still here, still fast, still feeless, still open to anyone who wants to build.





We're opening the waitlist for our Monetization Gateway, which will allow you to charge for any web page, dataset, API, or MCP tool behind Cloudflare. The charges will settle in stablecoins over the x402 open protocol. cfl.re/4eUFdt6


We're opening the waitlist for our Monetization Gateway, which will allow you to charge for any web page, dataset, API, or MCP tool behind Cloudflare. The charges will settle in stablecoins over the x402 open protocol. cfl.re/4eUFdt6







Si GPT 5.6 propose vraiment 750 tokens par seconde en vitesse d’inference On va multiplier par 15~20 la vitesse. Je sais pas si vous réalisez ce que ça va permettre en terme d’innovation technologique un modèle LLM plus smart et 15 fois plus rapide On a jamais vécu ça





Aloha! 🌺 Meet Ornith-1.0, a family of open-source LLMs specialized for agentic coding. Ornith-1.0 spans the full parameter sizes including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. It achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks including: ✅Terminal-Bench 2.1(77.5) ✅SWE-Bench(82.4 on verified, 62.2 on pro, 78.9 on Multilingual) ✅NL2Repo(48.2) ✅SWE Atlas(41.2 on QnA, 42.6 RF, 39.1 TW) ✅ClawEval(77.1) Post-trained on top of gemma4 and qwen3.5, Ornith-1.0 employs a novel self-improving training strategy in which reinforcement learning is used to generate not only solution rollouts, but also the task-specific scaffolds that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model generate higher-quality solutions in agentic coding.😎 All models are released under the MIT license, enabling full commercial and research use. 📖Tech Blog: deep-reinforce.com/ornith_1_0.html 🤗Huggingface: huggingface.co/collections/de…












