6 months of manual testing. Replaced in 30 minutes.
Jun-shuo (Lance) Liu , a research engineer at Columbia University, was stuck in a cycle most AI agent developers know well - designing test cases by hand, reading through every conversation, writing bug reports, and starting over with every update.
He tried ArkSim. Here's what happened:
→ Test report time: 2–3 days → 30 minutes
→ Iteration cycle: 1–2 weeks → 1–2 days
→ Accuracy: 80% → 90% in one week
But the biggest unlock wasn't speed. It was visibility. ArkSim surfaced a tool selection bug he'd been living with for months. This type of bugs was invisible to manual review, caught in a single run.
He wrote up the full story:
https://t.co/GUDKCLPDhn
#AIAgent #AIEval #AgentTesting
This Free AI Made a Trader $1.2 Million!!
That’s exactly what happened when a Reddit trader used FinGPT — a free, open-source AI that scans real-time news, earnings reports, and tweets — to turn $280K in a week… & $1.2 million in 3 months.
#FinGPT#AITrading#FreeAI#AlgoTrading
«Финуслуги» от Мосбиржи представил обновленную версию FinGPT — своего инвестиционного ИИ-помощника. Он может предоставлять инвесторам информацию о происходящем на российском рынке, транслировать биржевые котировки, объяснять финансовые термины и тонкости…
https://t.co/exdBEMBqPN
🚀 Day 5 of #OpenSourceWeek: 3FS, Thruster for All DeepSeek Data Access
Fire-Flyer File System (3FS) - a parallel file system that utilizes the full bandwidth of modern SSDs and RDMA networks.
⚡ 6.6 TiB/s aggregate read throughput in a 180-node cluster
⚡ 3.66 TiB/min throughput on GraySort benchmark in a 25-node cluster
⚡ 40+ GiB/s peak throughput per client node for KVCache lookup
🧬 Disaggregated architecture with strong consistency semantics
✅ Training data preprocessing, dataset loading, checkpoint saving/reloading, embedding vector search & KVCache lookups for inference in V3/R1
📥 3FS → https://t.co/JRZ2eYk1aK
⛲ Smallpond - data processing framework on 3FS → https://t.co/BoUA6YNjZK
🚀 Day 3 of #OpenSourceWeek: DeepGEMM
Introducing DeepGEMM - an FP8 GEMM library that supports both dense and MoE GEMMs, powering V3/R1 training and inference.
⚡ Up to 1350+ FP8 TFLOPS on Hopper GPUs
✅ No heavy dependency, as clean as a tutorial
✅ Fully Just-In-Time compiled
✅ Core logic at ~300 lines - yet outperforms expert-tuned kernels across most matrix sizes
✅ Supports dense layout and two MoE layouts
🔗 GitHub: https://t.co/cxJ55w61pT
🚀 Day 2 of #OpenSourceWeek: DeepEP
Excited to introduce DeepEP - the first open-source EP communication library for MoE model training and inference.
✅ Efficient and optimized all-to-all communication
✅ Both intranode and internode support with NVLink and RDMA
✅ High-throughput kernels for training and inference prefilling
✅ Low-latency kernels for inference decoding
✅ Native FP8 dispatch support
✅ Flexible GPU resource control for computation-communication overlapping
🔗 GitHub: https://t.co/Q6eRxZ9kgW
🚀 Day 1 of #OpenSourceWeek: FlashMLA
Honored to share FlashMLA - our efficient MLA decoding kernel for Hopper GPUs, optimized for variable-length sequences and now in production.
✅ BF16 support
✅ Paged KV cache (block size 64)
⚡ 3000 GB/s memory-bound & 580 TFLOPS compute-bound on H800
🔗 Explore on GitHub: https://t.co/4JvJTn5HX2
Just open-sourced PrimoGPT – an automated trading system using Deep Reinforcement Learning (DRL) & LLMs!
Built as part of my PhD dissertation, inspired by FinRL & FinGPT. It features an RAG-based approach for generating trading signals.
🔗 Repo: https://t.co/kIt4INyzr3
It's still a work in progress, but please feel free to check it out and contact me if you have any questions!