iFeeling Daily
Daily curated AI insights you can't miss.
Google Cloud CISO: How AI agents secure the SDLC at machine speed
Google Cloud's CISO details how they've embedded specialized AI agents across the entire SDLC — from design review through fuzz testing and autonomous patching — to counter AI-driven threats at machine speed. The Mantis framework, now partially open source, reduces token overhead by 85% while preserving critical code context, and a self-reflection loop continuously improves agent performance.
Async Inference: Why the Future of AI Agents Runs on Queues, Not Real-Time
The article argues that as AI agents shift from real-time chat to background batch work, inference infrastructure must follow. Sail Research builds an async inference stack that queues requests, routes to the cheapest capable open model, and uses spot capacity to cut costs dramatically—GLM-5.1 on Sail costs 6x less per token than Anthropic's Haiku.
Turla’s STOCKSTAY Backdoor: A New .NET Spy Tool Targeting Ukraine and Europe
Google Threat Intelligence Group's deep analysis of Turla's STOCKSTAY backdoor reveals a multi-component .NET implant that's been actively developed since 2022, targeting Ukrainian military and European diplomatic entities. The report includes code overlaps with the KAZUAR toolkit, YARA rules, and detailed operational timelines that are invaluable for threat hunters tracking Russian cyber espionage.
Databricks’ Agent Cloud: Why Open Source and LTAP Matter for AI
Databricks co-founders Matei Zaharia and Reynold Xin unpack Omnigent (an open-source meta-harness above coding and enterprise agents), LTAP (their database bet for live transactional data in column-oriented formats), and why agent security, spend controls, and a common API matter more than ever. The thesis: traditional software gets rewritten once the data is in the right place and agents sit on top.
FFASR Leaderboard: Benchmarking ASR in Real-World Far-Field Conditions
The FFASR Leaderboard from Treble Technologies and Hugging Face is the first open, community-driven benchmark for far-field ASR, evaluating models across 14 simulated rooms with validated acoustics. Early results show far-field WER at low SNR is several times higher than near-field WER, making the real-world robustness gap visible and comparable for the first time.
OpenAI and Broadcom unveil LLM-optimized inference chip Jalapeño
OpenAI and Broadcom unveiled Jalapeño, a custom LLM inference chip designed from scratch with substantially better performance per watt than current accelerators. Taped out in nine months using OpenAI's own models to accelerate chip design, it will deploy at gigawatt scale starting in 2026 as part of a multi-generation platform.
Zero-Day Exploit in Cisco SD-WAN Manager: Attack Chain and Defenses
Mandiant details how a threat actor exploited CVE-2026-20245 in Cisco Catalyst SD-WAN Manager, using rogue peering and credential manipulation to escalate privileges to root and then cover tracks with anti-forensic techniques. The attack chain and detection guidance are essential for any organization running SD-WAN.
NVIDIA NeMo AutoModel: 3.7x Faster MoE Fine-Tuning with One Import Change
NVIDIA NeMo AutoModel delivers 3.4-3.7x higher training throughput and 29-32% less GPU memory for MoE fine-tuning through a single import line change. By adding Expert Parallelism as a dedicated dimension, DeepEP fused dispatch, and TransformerEngine kernels on top of Transformers v5, it makes 550B-scale full fine-tuning feasible and produces standard HF checkpoints for downstream deployment.
How GPT-5 solved an immunologist’s 3-year T cell mystery
Immunologist Derya Unutmaz used GPT-5 Pro to solve a three-year-old puzzle about glucose and T cells, discovering that the model identified a mechanism—IL-2 protein disruption—that his lab had missed. It then correctly predicted results from an unpublished experiment, convincing him these models truly understand biology.