- Meta gives the West its best open-weight model
- Rowan’s Corner: My AI walks my company’s factory floor
- Turn a ChatGPT answer into a tool you can use
- Report: Harvard maps AI’s gender divide
Image source: Mark Zuckerberg on XThe Rundown: Meta just released Muse Spark Open, an open-weight, 816B-parameter multimodal model built for coding and agentic work, and worked with Apple so that it could run locally on Mac Studios — a first for a model in this size class, Meta says.The details: - Two M5 Ultra Mac Studios with 1TB combined memory can run Spark Open via Apple’s updated MLX toolkit, with Meta saying the model shipped iOS app fixes and edited video in DaVinci Resolve without the cloud.
- On Artificial Analysis’ Intelligence Index, it sits at 39, ahead of the West’s open-weight models but behind China’s GLM 5.3 (45), Kimi K3 (44), and Qwen3.8 (40).
- Spark Open either matches or tops open rivals on multimodal and knowledge tasks, but Chinese models still code better, with Kimi, GLM, and Qwen all ahead.
- It’s the third major Western open launch this month, after Reflection AI’s Beam and Mistral’s 1T-parameter Le Chonk, whose weights arrive Oct. 27.
The Rundown: HubSpot’s new free “200+ AI-Powered Income Ideas” guide offers actionable strategies to turn artificial intelligence into your own personal revenue generator — unlocking a gateway to financial innovation in the digital age.With this guide, you can:- Explore hundreds of revenue-generating ideas across industries with real-world applications
- Follow step-by-step instructions that make AI accessible to everyone
- Adopt cutting-edge strategies to stay ahead in today’s fast-paced market
Rowan: At an in-person company, the CEO can walk the factory floor. You watch how the company actually runs, catch errors in real time, spot slow handoffs, and identify processes worth automating. The best operators do it religiously.The problem is that The Rundown is fully remote and has just over 20 people.There is no floor to walk. So every Friday, I do what I call a digital factory inspection: I pick random important things across the company (support queries, newsletter posts, specific finance items, etc.) and review each one with the same lens. What’s slow? Which handoffs could disappear? What should be automated?This week, I handed the entire prep to AI. A scheduled Claude task now runs every Friday before I wake up, and it:- Picks the random areas to inspect (randomness matters so nothing gets gamed)
- Pre-gathers the samples, links, and data for each area into a report in my Notion
- Checks last week’s findings against Slack to verify they actually got fixed before I move on
The Rundown: In this guide, you’ll try ChatGPT’s new Intelligent UI by creating a workshop cost calculator. You’ll change the headcount, check the figures, and ask it to add a budget buffer.Step-by-step:- Open ChatGPT in a web browser and start a Chat with GPT-6. Choose Medium where available and leave Pro reasoning off for this exercise
- Paste the guide’s prompt to create a calculator with editable costs, budget, and attendance. Check that the starting total is $700 for 20 people
- Change attendance to 30 using its controls. The total should rise to $950 and show that you are $50 over budget
- Try zero attendees and check that the fixed room fee stays. Test the budget boundary too, so a useful-looking calculator does not hide a wrong result
- Return to 20 people and ask for a 10% buffer. Check for a $770 final cost and $130 left, then change the headcount again to test the update
The Rundown: How are top organizations realizing value as AI spending accelerates? This webinar explores the leadership, operating model, and organizational shifts required to deliver measurable business and financial value with AI.In this webinar, you’ll learn:- How to cut through the AI hype
- Why there is a gap between AI access and business impact
- What leading CEOs do differently to scale AI
Image source: Harvard Kennedy School’s Shorenstein CenterThe Rundown: Harvard researchers just found consistent gender gaps in how Americans use AI, get support for it, understand it, and appear in coverage of it, drawing on a survey of 5,400+ adults, browsing data, and 78K news articles.The details: - 29% of women said they’d never used AI vs. 22% of men, though browsing data showed no real gap in trying it, only in how much time users spent on it.
- At work, 64% of employed women reported no AI training vs. 49% of men, with the study linking training and encouragement to higher use and confidence for both.
- Men answered more AI questions correctly while women chose “not sure” more often, though more men also claimed to recognize made-up AI figures.
- AI headlines named men 14.6x as often as women, a gap the researchers partly tie to male-led companies, though the gap also held among quoted experts.
Muse Spark Open - Meta’s open-weight AI for coding and long-horizon agents
GPT-Live-1.1 - OpenAI’s new voice AI with more natural multilingual accents
Nemotron 3.5 Super VL - Nvidia’s open multimodal AI for specialized AI agents
FLUX 3 Image Klein - BFL’s small open model for 4K image generation, editing
- Read our last AI newsletter: Rogue AI agents sit for their first interview
- Read our last Tech newsletter: Apple goes all-in on the home
- Read our last Robotics newsletter: Inside Amazon’s million-robot experiment
- Today’s AI tool guide: Turn a ChatGPT answer into a tool you can use
- RSVP to next workshop on Oct. 21: Get real work out of Microsoft Copilot
Source: https://therundownai.beehiiv.com/p/meta ... ercomputer