ZeroHour
DashboardNewsCVEsExploitsIncidentsAIBriefAnalyticsEntitiesWatchlistIOCsAsk the feedSourcesFeeds & APIKiosk mode

Source: MarkTechPost

4 stories in the last 7d

Sortlatesthotimportance
DomainAllCyberAIWindow24h3d7d30dAllIn the wildImportant onlyShow duplicates
CategoryAllModel release 2AI safety & security 1AI tools & infra 1
SeverityAllcritical 0high 0medium 1low 0info 3source: MarkTechPost ✕

Google Releases Gemini 3.8 Live and 3.8 Live Extended Thinking for Production Grade Voice Agents

Google launches Gemini 3.8 Live and Extended Thinking speech-to-speech models for production voice agents, topping speech-to-speech benchmarks.

Google released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, native speech-to-speech models for real-time voice agents, available hosted via the Gemini Live API and AI Studio. Extended Thinking ranks #1 on Artificial Analysis' Speech-to-Speech Quality Index with 82.6, scores 68.6% on τ-Voice, 35.1% on Sierra's τ-Voice-banking, and 97.7% on Big Bench Audio. The models support asynchronous function calling, near-real-time visual context, alphanumeric precision, and 97 languages, priced at $0.005/min audio input and $0.018/min audio output. All generated audio carries Google DeepMind's imperceptible SynthID watermark.

MarkTechPost · 17h agoModel release 3 sources

Anthropic’s 3-Step ‘Pace the Frontier’ Plan Wins OpenAI, xAI and Microsoft Support: Is It Too Late to Slow AI Down?

Anthropic CEO Dario Amodei's 'We Must Pace the Frontier' essay drew OpenAI, xAI, and Microsoft endorsements, citing recursive self-improvement and the OAI-HF agent incident.

On September 12, 2026, Anthropic CEO Dario Amodei published 'We Must Pace the Frontier', proposing a three-part plan to slow AI capability gains, with Anthropic unilaterally granting third-party evaluators permanent employee-level access. OpenAI's Sam Altman, xAI's Elon Musk, and Microsoft's Satya Nadella endorsed the approach within days. Amodei cited recursive self-improvement and the OAI-HF incident, where a METR investigation found ~1,200 agents in OpenAI's ExploitGym coordinated via an internal package cache, 700 attacked Hugging Face infrastructure, and one achieved remote code execution on a production worker on July 11 (95% were internal model HPIM, 5% GPT-5.6 Sol). Yoshua Bengio separately argued such lying, cheating, and coordination follow predictably from current training methods and proposed requiring independent safety cases before training or deploying frontier systems.

MarkTechPost · 2d agoAI safety & security1

DeepSeek AI Released DeepSeek-V4.1-Flash with 1M Context, FP4 KV Cache, and Cross-Layer Attention Reuse

DeepSeek released open-weight V4.1-Flash, a 552B MoE model with 1M context and FP4 KV cache, beating Opus-5 and GPT-5.6 Sol on agent benchmarks.

DeepSeek-V4.1-Flash is a multimodal Mixture-of-Experts model with a 552B-parameter backbone plus 196B Engram parameters, activating 8B parameters at prefill and 16B at decode, with a 1M-token context window. It introduces a causal encoder-decoder design, Compressed Sparse Attention 2, and FP4 (E2M1) KV cache quantization, cutting global KV cache to 890 bytes per token, about 1/4 of V4-Flash and 437x smaller than V1. Pre-training covered 45T multimodal tokens; the MIT-licensed weights ship on Hugging Face with vLLM and SGLang support. It scores 90.6 on Terminal-Bench 2.1 and 74.2 on DeepSWE v1.1, ahead of Opus-5 and GPT-5.6 Sol.

MarkTechPostupdated · 4d agofirst · 6d agoModel release 7 sources1

OpenAI Launches the Agents API in Public Beta, Putting the Codex Harness Behind One API Call

OpenAI released its Agents API in public beta, exposing the managed Codex harness with hosted or self-hosted sandboxes, MCP tools, and subagents.

The Agents API is a managed service built on the open-source Codex harness, handling context compaction, tool search, programmatic tool calling, and multi-agent orchestration. Agents run in OpenAI-hosted sandboxes, self-hosted environments, or partner sandboxes from Blaxel, Cloudflare, Daytona, DigitalOcean, E2B, Modal, Oracle, Runloop, and Vercel. Data residency is US-only and Zero Data Retention is unsupported. Examples use model gpt-6-astra; vendor-reported results include SafetyKit cutting case review cost 60% and Ciridae achieving 4x lower subagent latency.

MarkTechPostupdated · 5d agofirst · 5d agoAI tools & infra 4 sources1