Sep 1 – Oct 1, 2026 · 6 items
The AI week, for a journalist
A real edition, written for: Journalist
The one thing
Dots and Automations can now run your background research for you—do you have a topic you’d hand off today?
NVIDIA to acquire Hugging Face for $12.93B
NVIDIA has agreed to acquire Hugging Face, the open model sharing platform. Chief executive Jensen Huang announced the deal on NVIDIA's blog. He put the price at just under $13 billion. NVIDIA says Hugging Face will stay open to the whole AI industry. Developers will keep their choice of models, frameworks, clouds and chips. NVIDIA compute will not be required to build or deploy through the platform. Hugging Face will continue to support open source and open weight models from all builders. NVIDIA says its infrastructure and engineering can improve reliability, safety, model evaluation and deployment. The Hugging Face team and its brand will remain. No closing date or regulatory timeline was given.
Why it matters for you
NVIDIA buys Hugging Face but pledges to keep it open. That affects every model you pull from its hub.
- The platform stays open to all models and clouds
- No NVIDIA hardware is required to use it
- Developers keep their choice of frameworks and chips
Try this
Check whether your current workflows rely on Hugging Face exclusives
Sources
OpenAI launches Dots for always-on tasks
OpenAI launched Dots, always-on AI assistants that work without constant direction. They run on GPT-6 Astra with their own cloud computer. Dots connect to over 4,000 apps via plugins. They learn user preferences and work 24/7 on tasks. Users can inspect a dot’s work on its cloud computer. Dots can also use a user’s laptop with permission. They message progress or questions in ChatGPT, Slack, or Teams. Built-in safeguards include read-only tools for background work. Users control access, permissions, and approvals via Custom Rules. Specialist dots for organizations have their own identity and access. These are in focused enterprise pilots. Microsoft Agent 365 will integrate specialist dots. Dots roll out to Pro and Business Premium users in eligible markets.
Why it matters for you
Dots run 24/7 on GPT-6 Astra and can pull from 4,000 apps. That covers long background research you now do manually.
- They learn your preferences and work without constant direction
- You inspect their work on a cloud computer
- Pro or Business Premium plan required
Try this
Set a Dot to monitor a live topic and summarize daily updates
Paste this into your AI tool
Context: I am a journalist covering business and technology in Switzerland. Task: Monitor [topic] and summarize the most important developments each day. Constraints: - Only use public, reputable sources - Cite every claim - Flag any uncertainty Output: A bullet-point summary of key updates, with sources.
Sources
ElevenLabs v4 supports 90 languages and 10-second voice cloning
ElevenLabs released Eleven v4 and Eleven v4 Turbo text-to-speech models. Eleven v4 uses a new architecture for more emotive, controllable speech. It supports 90+ languages and 17,500+ voices. Professional Voice Clones are supported again after being absent in v3. Audio tags like laughs or whispers are followed more reliably. Context stitching keeps long-form audio consistent. Regenerations retain the same speaker identity. Eleven v4 Turbo is a low-latency variant for real-time use. It has ~100 ms median inference latency and ~150 ms time to first speech. Both models are available via apps, API, and agents. They support bidirectional streaming for agent loops. Professional Voice Clones work identically across both models. The models are available now.
Why it matters for you
ElevenLabs v4 now clones a voice from 10 seconds of audio. That lets you verify a source’s identity faster.
- Voice identity stays consistent over long text
- Inline tags stack multiple expressions
- Lower latency for real-time voice agents
Try this
Test cloning a known voice from a short clip to confirm authenticity
Paste this into your AI tool
Task: Clone this voice from the provided 10-second audio clip and read the following text in the same voice. Audio: [paste 10-second clip] Text: [paste text to verify]
Cisco Talos tracks AI-integrated malware
Cisco Talos built an open-source framework called CAIRN. It flags AI-integration traits in malware to classify and track samples. CAIRN already found a Windows hacking tool named CLOSEDQUORUM. CLOSEDQUORUM polls DeepSeek, Qwen, Mistral and Google Gemini for directives. The tool has no human input mechanism. It steals login credentials and cryptocurrency. Researchers linked it to cybercriminal forums from 2025. They could not confirm its real-world use. CAIRN also uncovered about 20 other AI-integrated malware examples. Researchers say AI is becoming operationalized for attackers.
Why it matters for you
Cisco Talos found malware that polls LLMs for directives. That changes how you verify a source’s digital footprint.
- CLOSEDQUORUM steals credentials and crypto without human input
- It polls DeepSeek, Qwen, Mistral and Google Gemini
- AI is becoming operationalized for attackers
Try this
Ask your IT team whether they monitor for AI-generated artifacts in malware
Sources
Most conduct codes lack AI guidance
Fewer than one in ten employee conduct codes mention artificial intelligence or technology ethics, LRN found. The advisory firm surveyed 2,000 full-time employees for its code of conduct report. Nearly all said their employer requires them to sign or acknowledge a code. A declining share said they actually use the code as a reference. Nearly one in five said their code lacked practical guidance. Two thirds felt they could report misconduct without retaliation, down from last year. LRN said most codes also fail to describe how investigations work. It advised employers to link AI to existing principles such as accountability and fairness, rather than add new sections. Separate HR Acuity figures show reported misconduct rising sharply.
Why it matters for you
Fewer than 1 in 10 employee conduct codes mention AI. That leaves your newsroom without clear rules on AI use.
- Nearly 1 in 5 say their code lacks practical guidance
- Two thirds feel safe reporting misconduct, down from last year
- Most codes fail to describe how investigations work
Try this
Review your newsroom’s conduct code for AI-specific clauses
Sources
Perplexity adds Automations for long-running agents
Perplexity Computer launched Automations for long-running agents. Agents remember prior work and pick up where they left off. They run on a schedule or when events occur in Slack, Gmail, Outlook, Linear, or GitHub. Users set triggers, define tasks, and specify outputs like Slack or Gmail. Automations can flag missed updates or deadlines. Users create them via the omnibar or the Automations interface. Admins can limit connector permissions. Automations do not use credits while waiting for triggers. Existing Scheduled Tasks can be migrated to Automations. Automations are available to all Computer users.
Why it matters for you
Perplexity Automations remember prior work and trigger on events. That automates ongoing research you now do by hand.
- Agents pick up where they left off
- They run on a schedule or when events occur in Slack or GitHub
- No credits used while waiting for triggers
Try this
Set an Automation to flag missed updates on a story you’re tracking
Paste this into your AI tool
Context: I am a journalist tracking [story topic] in Switzerland. Task: Monitor [specific sources or platforms] for updates on this story and flag anything I might have missed. Constraints: - Only use public sources - Note the date and source of each update - Highlight gaps or contradictions Output: A list of missed updates with sources and dates.
Build this
Every week, one small thing to build with AI in something you actually care about. No work in it. Five minutes to set up, and worth keeping if it earns a second run.
Make ChatGPT critique its own last answer in one line
Five minutes to set up
Now argue against the answer you just gave me in one sentence.
- Paste your last answer into the chat
- Add the prompt above on a new line
- Check whether the critique exposes a gap or bias
- Use the stronger of the two in your work
Yours arrives Thursday.
This one was written for a journalist. Tell us what you do and the next one is written for you — same news, your job, once a week.