Category: AI News
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Agentic AI solved coding — and exposed every other problem in software engineering
[ad_1] Agentic AI is now a core part of the engineering process, driving massive execution leverage and helping us generate more code than ever before. Yet, a difficult question I’ve increasingly heard from business leaders is: if we’re shipping code faster than ever, why aren’t our products improving at the same rate? The reason is…
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When Claude changed, everything changed: Managing AI blast radius in production
[ad_1] Our system did one thing, and it did it well: It turned natural-language questions into API calls. The users were analysts, account managers, and operations leads. They knew what data they needed, but assembling it manually meant pulling from four dashboards, two BI tools, and a Salesforce report builder. With our system, they typed…
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AI agents are learning on the job — just not for your whole team
[ad_1] When someone on a team corrects an AI agent — better prompts, better feedback, better context — that improvement disappears the moment a colleague opens the same tool. The correction doesn't transfer, and the next person starts from zero. The problem compounds in multi-agent workflows, where teams expect agents to share context across users…
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Miso Labs Releases MisoTTS: An 8B Emotive Text-to-Speech Model with Open Weights
[ad_1] Miso Labs has released MisoTTS, an open-weights 8-billion-parameter text-to-speech model. It generates expressive speech from both text and audio context. The model uses residual vector quantization (RVQ) to widen its sonic range. This avoids scaling a single flat vocabulary while keeping parameter count fixed. What is MisoTTS MisoTTS is an 8B-parameter text-to-dialogue RVQ Transformer.…
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Google's new open source Gemma 4 12B analyzes audio, video — and runs entirely locally on a typical 16GB enterprise laptop
[ad_1] While many AI open source model providers are pursuing larger and more powerful models, Google is still giving attention to the smaller, more local side of the market. Today, the tech giant released Gemma 4 12B, an 11.95-billion-parameter open-weights model with permissive Apache 2.0 license optimized to execute locally on a standard enterprise laptop…
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Perplexity AI unveils hybrid local-cloud inference system at Computex 2026
[ad_1] Perplexity AI, the fast-growing search startup now valued at $20 billion, unveiled what it calls the first hybrid local-server inference orchestrator at Computex 2026 on Monday night, demonstrating software that autonomously decides — in real time and mid-task — which AI workloads stay on a user's device and which get routed to frontier models…
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Meet Memory OS: A 6-Layer Open-Source Memory Stack Built on Top of Hermes Agent
[ad_1] Hermes Agent already remembers across sessions. The open-source agent from Nous Research ships with curated memory files and full-text session search. But a new community project argues that built-in memory is too shallow for serious work. A new library named ‘Memory OS‘ has been released under an MIT license by a developer (ClaudioDrews). It…
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Claude Mythos exposed a hard truth: Your enterprise patching process is way too slow
[ad_1] In 2024, researchers from the University of Illinois found that GPT-4, when provided with a common vulnerabilities and exposures (CVE) description, could autonomously exploit 87% of a curated 15-vulnerability one-day dataset. Without the description, it could only exploit 7%. This provided a “margin of safety” for the industry because while AI could exploit known…
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Trajectory Releases a Concurrent Multi-LoRA Training Stack for Continual Learning, Reporting a 2.81× Experiment-Throughput Gain
[ad_1] Trajectory’s concurrent multi-LoRA stack reports a 2.81× experiment-throughput gain over single-tenant RL, with all code in the NovaSky-AI/SkyRL GitHub repository. Most language models improve in discontinuous jumps. A team collects data, trains, and ships a new version. This takes months and produces remarkable or catastrophic behavior for users. Trajectory wants to replace that cycle…
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The AI agent bottleneck isn't model performance — it's permissions
[ad_1] Enterprise AI agents are stalling — not because of model performance, but because of permissioning. Every agentic workflow eventually hits the same wall: what is this agent allowed to touch, on whose behalf, and how does the system know? Workday's answer is to make its existing system of record the governance layer for agents.…