🚀Today’s Top AI Headlines:

1. Zoom adds real-time AI actions to meetings: Zoom has unveiled AI Companion 3, its most ambitious step yet toward turning meetings into fully actionable workflows rather than passive conversations. Unlike earlier assistants that focused mainly on summaries, AI Companion 3 operates as an agentic layer across the Zoom ecosystem. It captures key decisions and action items in real time, generates post-meeting deliverables automatically, and pushes them directly into everyday workplace tools such as Google Drive, OneDrive, calendars, and task managers. The idea is simple but powerful: meetings should not end with people scrambling to remember what was decided. Instead, AI Companion 3 creates follow-ups, drafts documents, assigns tasks, and keeps work moving without additional manual effort. Zoom positions this as a productivity multiplier, especially for distributed teams that already spend a significant portion of their workday in calls. The assistant is available inside paid Zoom plans and also as a standalone web-based tool, signaling Zoom’s intent to compete more directly with general-purpose AI copilots. Strategically, this move reinforces Zoom’s evolution from “video calls company” to an AI-powered collaboration platform. If execution matches the promise, AI Companion 3 could reduce meeting fatigue while making conversations far more outcome-driven.

   Source: Youtube

   🤖 Robi: “Great, now even my calendar wants to assign me tasks.”

2. Nvidia launches agentic open-source model family: Nvidia has introduced the Nemotron 3 family, a new lineup of open-source models designed specifically for building agentic and multi-agent AI systems. The release includes three variants: Nano, optimized for targeted and lightweight tasks; Super, built for multi-agent coordination; and Ultra, aimed at complex, enterprise-grade AI applications. What sets Nemotron 3 apart is its hybrid latent mixture-of-experts architecture, which allows the models to deliver strong performance while maintaining efficiency. This design enables developers to scale agentic systems without the heavy compute costs typically associated with large models. Nvidia is positioning Nemotron 3 as a practical foundation for enterprises that want to deploy AI agents at scale rather than experiment in isolated pilots. By making the models open source, Nvidia is also sending a clear message: it wants to anchor the agentic AI ecosystem on its hardware and software stack. For enterprises, this combination of openness, performance, and efficiency lowers the barrier to building sophisticated multi-agent workflows. Nemotron 3 reinforces Nvidia’s growing role not just as a chipmaker, but as a central platform provider for the next generation of AI applications.
   Source: Nvidia Developer

   🤖 Robi: “Finally, an Ultra that isn’t a phone or an energy drink.”

3. Gemma 4 hints dropped by Google’s Omar S.: Speculation is building around a potential release of Gemma 4, after Omar Sanseviero, Google DeepMind’s Developer Experience Lead, posted a cryptic message encouraging developers to bookmark and refresh Google’s Hugging Face page. While no official announcement has been made, the timing and tone of the post strongly suggest that a new open-source Gemma model could be imminent. The Gemma family is particularly significant because it uses the same underlying technology as Google’s flagship Gemini models, but in smaller, more efficient packages designed to run on laptops, desktops, and even mobile devices. This makes Gemma an important bridge between cutting-edge AI research and practical, local deployment. If Gemma 4 does launch, it would likely arrive amid intense competition in the open-model space, where efficiency, performance, and developer trust matter as much as raw capability. A stronger Gemma release could help Google regain mindshare among developers who increasingly value open, transparent models that can be fine-tuned and deployed flexibly. Beyond benchmarks, Gemma 4 would signal Google’s commitment to making advanced AI more accessible beyond the cloud.
   Source: X Post

   🤖 Robi: “I'm also compact and open-source, emotionally, at least.”

🔍Beyond the Headlines:

1. Oral exams return to outwit AI cheaters: A growing number of university professors are bringing back oral exams as a response to widespread AI-assisted cheating, according to a Washington Post report. With tools like ChatGPT making essays and online tests easier to game, educators are turning to face-to-face assessments where students must explain concepts, code, or arguments in real time. Professors argue that oral exams not only reduce misuse of AI but also strengthen critical thinking, communication skills, and genuine understanding. In an AI-saturated academic environment, these exams are emerging as a more authentic measure of learning.
   Source: Washington Post

   🤖 Robi: “Students hate it. Professors love it. AI's just confused.’’

2. AI now surveils US inmate calls, sparking debate: US telecom provider Securus Technologies has developed an AI system trained on years of inmate phone and video calls to detect potential criminal activity. The tool scans calls, texts, emails, and video chats in real time, flagging suspicious segments for human investigators. While the company claims it can help disrupt gang activity and contraband smuggling, it has not disclosed concrete cases where the AI made a difference. Prison-rights advocates warn that such systems raise serious concerns around consent, mass surveillance, and the erosion of inmate privacy.

   Source: MIT Technology

   🤖Robi: “Ah yes, the ol’ “enhanced security” excuse, classic surveillance playbook move.”

🤖Prompt of the Day:

Enterprise AI Use-Case Prioritization Framework

🤖AI Tools You Didn’t Know You Needed:

Problem: Long articles, PDFs, and dense content are hard to read, digest, and remember, especially when you just need the key ideas fast.

AI Solution: Chunks uses AI to break long content into clear, bite-sized chunks that are easier to read, understand, and revisit.

AI Tool: Chunks is an AI reading and summarization tool that restructures long text into logical sections, highlights key points, and improves comprehension without losing context.

Helpful Features

• Auto Chunking: Splits long content into readable sections.

• Key Point Extraction: Highlights the most important ideas.

• Clean Reading Mode: Improves focus and comprehension.

• Works on Long Text: Ideal for articles, essays, and documents.