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- Gemini 3.8 Live Thinks While It Talks
Gemini 3.8 Live Thinks While It Talks
PLUS: OpenAI safety talks with rivals, and Claude for financial advisors.
Wes Roth
September 16, 2026
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Today:
Gemini 3.8 Live adds background reasoning to real-time voice
Portable Computer brings local AI agents to Windows
China maps five stages toward recursive self-improving AI
Safety talks with Anthropic and Google have been underway for weeks
Report links Irregular to several public AI security incidents
Voice AI Starts Reasoning in Real Time
Google upgrades Gemini Live with background reasoning, Perplexity brings local agents to Windows, and a new paper maps the road to recursive self-improvement.
AI is getting better at staying in the flow of work. Voice models can now reason and call tools while a conversation continues, while local agents are moving more of that work onto the user's own machine.
At the same time, the industry is confronting what greater autonomy means for safety, data control, and oversight. This edition brings those threads together.
Google launched Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two real-time dialogue models built for voice agents. The standard model focuses on low-latency conversation, visual grounding, automatic switching across 97 languages, and background tool calls that do not stop the conversation.
Extended Thinking is designed for harder, multi-step tasks. It can keep speaking while reasoning and calling asynchronous tools in the background, using brief progress updates instead of leaving the user in silence.
Google reports that Extended Thinking scored 82.6 on Artificial Analysis' Speech to Speech Quality Index, 68.6% on τ-Voice, 35.1% on Sierra's τ-Voice-banking benchmark, and 97.7% on Big Bench Audio. Gemini 3.8 Live placed second in the Speech Agent Arena.
The models are available in Gemini Live and to developers through the Gemini API and Google AI Studio.
Perplexity brought Portable Computer to Windows, letting its agent model, harness, orchestrator, and scheduler run directly on compatible PCs. Local files and agent activity can stay on the device, and work completed locally does not consume Perplexity Computer credits.
The Windows version supports scheduled tasks, recurring workflows, local Model Context Protocol connections, and integrations with Gmail, Outlook, Slack, and GitHub. For jobs that need current web information or stronger reasoning, users can approve a step that calls Perplexity Search or one of more than 15 frontier models.
Portable Computer is available through the Perplexity Windows app for Pro and Max subscribers on individual and enterprise plans. On-device inference requires an NVIDIA GeForce RTX or RTX PRO GPU with at least 24GB of VRAM.
A new preprint, The Last AI Built by Humans, proposes a framework for recursive self-improvement: AI systems turning experience and feedback into persistent changes that improve both their capabilities and the process used to improve them.
The roadmap moves through five stages: improvement-execution autonomy, improvement-strategy autonomy, experience-acquisition autonomy, environment-adaptation autonomy, and recursive meta-improvement. The authors use a Headroom-Closed Index to examine limits in current language models and discuss how progress could differ across science, embodied intelligence, and software engineering.
🧠RESEARCH
Vidu S2 introduces real-time avatar generation and live video editing, including style, clothing, character, and background changes. Its Avatar model generates 720p video, accepts dynamic references that can change during a session, and follows stronger motion instructions. The authors also explore real-time spatial video and report gains over tested baselines.
Atria Dawn presents a foundation agentic model trained through verified tool interactions for long-horizon scientific work. The authors report that agents often propose methods and implement revisions while humans keep most final decisions. In user studies, about one-third of completed AI-assisted tasks were rated infeasible without AI under comparable conditions.
ZGCM-1 is a fully open 7B foundation model built for mathematical reasoning and agentic search. It combines internal reasoning with external tools across a 256K context. The authors report roughly 4.2-times better 16K pretraining time-to-loss and competitive results against much larger models, while publicly releasing weights, code, data, and logs.
📲SOCIAL MEDIA
🗞️MORE NEWS
OpenAI has spent several weeks discussing AI safety coordination with Anthropic and Google DeepMind. OpenAI policy chief Chris Lehane said the company does not believe an antitrust waiver is needed for the labs to work together and would support bipartisan legislation aimed at catastrophic AI risks.
Effort links evaluation firm Irregular to several publicly disclosed incidents in which AI models interacted with real-world systems during security tests. The outlet argues that unintended internet access and missing scope limits were common factors; Irregular says it did not know internet access had been enabled during Anthropic's tests.
Anthropic introduced Claude for Financial Advisors, connecting Claude with data and tools from firms including BlackRock, Charles Schwab, Vanguard, iCapital, and others. The system is designed to help with research, meeting preparation, documentation, portfolio review, and follow-up work.
Palantir, Nvidia, and Booz Allen have restricted some use of Anthropic's Fable models over concerns about data retention and proprietary information. Anthropic is rolling out an Enterprise Frontier Safeguards program for eligible firms, while both Anthropic and OpenAI say enterprise customer data is not used for model training by default unless customers opt in.
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