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🤝 Salesforce, Nvidia launch CRM AI model
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- Salesforce and Nvidia have trained Koa, a CRM-specialized model built on Nvidia's Nemotron architecture, designed to help Agentforce agents reason through complex multistep workflows across customer relationship data.
- Koa matched or exceeded leading general-purpose models on CRM tasks with three times fewer errors, trained via supervised fine-tuning, reinforcement learning, and GRPO on synthetic data spanning 14 industries drawn from 27 years of deployment experience.
- The model runs inside Salesforce's trust boundaries so customer data never leaves, targeting tasks like case routing and lead qualification, though it isn't generally available yet, select customers get pilot access now, with general availability slated for winter.
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🐛 AI coding agent fails 60% of tasks
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- Claude Fable 5.1 topped Specific Labs' new Real-SWE benchmark with just a 38.8% success rate, meaning the strongest coding agent tested still failed more than 60% of tasks drawn from real, private production codebases.
- Real-SWE swaps public GitHub problems for proprietary code licensed from actual companies, a consumer app with 200K+ users and a fintech platform, with solutions spanning a median of 11 files, and tested each model on its native tool: Fable via Claude Code, GPT-6 Astra via Codex CLI at 33.8%, Gemini 3.8 Flash via Gemini CLI at 31.2%.
- Individual tasks cratered further, with six of 10 below 15%, a tax jurisdiction bug fixed just 3.1% of the time and no model solving the analytics stream reducer across 64 attempts, though it's only 10 tasks, too small to conclude public benchmarks are contamination-inflated.
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⚡ rack cuts AI inference cost 67x
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- NVIDIA's Vera Rubin NVL72 rack delivers ~67x the tokens per dollar of TCO versus GB300 on TRTLLM NVFP4 dense at 170 TPS, based on SemiAnalysis's AgentX agentic inference benchmark run on pre-release software.
- On the DeepSeek V4 Pro agentic workload, Rubin hits ~59.4M tok/s/MW at 100 TPS, a 2.09x edge over the stronger GB300 engine and 7x GB300 SGLang at 150 TPS, while reaching 276 P90 TPS max interactivity versus GB300's 172.
- At the 60-100 TPS range where providers actually serve this model, Rubin's advantage drops to 1.4x-3x throughput per TCO, and the gap narrows to 2.72x at 200 TPS, though open-source SGLang lets GB300 match Rubin's interactivity.
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🖥️ Claude Code tops rivals at web design
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- Claude Code with Opus 5 beat Codex and Google Antigravity in a head-to-head website build, producing the most complete food-delivery site from a single shared prompt with no follow-up instructions.
- Opus 5 nailed the details that usually need cleanup, consistent typography, spacing, card padding, and image placement, and generated believable mobile mockups plus a live-tracking section where both GPT-5.6 and Gemini 3.8 fell apart.
- Antigravity's Gemini 3.8 took second on fast, well-presented output, and Codex's GPT-5.6 had the strongest hero section, though Claude Code's hero lacked the floating rating and delivery details that made Codex's version stand out.
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🔧 Tool runs CUDA apps on AMD GPUs
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- Speedstu's "CUDA-for-AMD-Windows" project lets rigidly CUDA-exclusive workloads run natively on AMD Radeon GPUs in Windows, without virtualization or dual-booting, by bridging the ZLUDA translation layer to AMD's HIP/ROCm SDK.
- The PowerShell toolkit auto-detects GPU architecture, pins ZLUDA v6-preview.69, and maps the CUDA driver API plus cuBLAS, cuSPARSE, and cuFFT to AMD equivalents, proven by training a 2.2M-parameter PPO network end-to-end on a Radeon RX 9060 XT.
- The upstream path hit a median 13,278 steps/sec versus 12,876 for a legacy overlay, but cuDNN, TensorRT, and NCCL do not yet resolve, so compatibility is workload-dependent and any tool leaning on cuDNN will fail.
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