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Good morning, AI enthusiasts. Remember when every new AI experience required months of infrastructure work? Reactor just changed that, and it brought Apple Vision Pro engineers and NVIDIA backing along for the launch.
World models aren't just AI you prompt. They're interactive and real-time, shaped by user input as it happens. Reactor is betting that's the next computing shift. Whether developers agree will be clear in a matter of weeks.
In today's recap:
Reactor launches world model infrastructure for developers
MiniMax M3 debuts with coding frontier and 1M context
Build a talk-to-edit video pipeline with Gemini Omni
SoftBank commits 75B euros to France's AI future
4 new AI tools, prompts, and more
REACTOR
Reactor launches world model infrastructure
Reactor
Recaply: Apple Vision Pro leads just launched Reactor, a platform for building apps on world models in real time, with $59M backed by NVIDIA Ventures, Lightspeed, and AWS.
Key details:
Reactor provides a unified SDK and API, letting developers stream from frontier world models to their apps in real time with under 10 lines of code, without managing deployment infrastructure.
The company raised $59M across Seed and Series A rounds. Co-founders Alberto Taiuti and Bryce Schmidtchen both led technical work on the Apple Vision Pro, with Taiuti also co-founding Luma AI as CTO.
NVIDIA Ventures joined the round, and Overworld, a world model lab, is already building on Reactor as its production layer, according to the launch announcement.
The platform is live today via SDK and API, with usage-based pricing billed by model type. Hundreds of developers are already building on it.
Why it matters: Every big tech shift follows the same path. A new kind of experience shows up. Then someone builds the tools to run it at scale. World models generate content in real time, shaped by user input. That makes them different from every AI system before them. Reactor is betting that's the next platform shift. NVIDIA Ventures and Apple Vision Pro alumni behind it signals this isn't just a developer tool. It's a claim on a new category.
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MINIMAX
MiniMax M3 debuts with coding frontier and 1M context
MiniMax
Recaply: MiniMax just rolled out M3, the first open-weights model combining coding, multimodal reasoning, and 1M context, as DeepSWE benchmarks reveal a widening gap between proprietary and open-source models.
Key details:
M3 scores 59.0% on SWE-Bench Pro and 66.0% on Terminal Bench 2.1, with MiniMax Sparse Attention scaling context to 1 million tokens and native multimodality built into the base model from step zero.
API access is live today with 50% off standard usage for the first 7 days. Model weights and a technical report are expected within 10 days.
DeepSWE benchmarks show GPT-5.5 leads on coding performance but carries a significantly higher hallucination rate, a paradox generating three active threads on r/singularity today.
The gap between frontier proprietary models and open-source alternatives on DeepSWE is now wide enough that challengers need standout features to compete at the top of the leaderboard.
Why it matters: Open-weights models have a harder time competing on raw coding scores against proprietary frontrunners. M3 doesn't try to out-benchmark GPT-5.5 on its own terms. It packages 1M context and native multimodality into a model developers can run without API restrictions. Whether that's enough to close the gap is the debate happening in real time today.
GUIDES
Build a talk-to-edit video pipeline with Gemini Omni
Recaply: In this tutorial, you will learn how to build a video editing pipeline using Google Gemini Omni, turning raw footage or text prompts into finished clips through natural language, with no timeline editor required.
Step-by-step:
Go to Google Flow (flow.google.com) or open the Gemini app on a Google AI Plus, Pro, or Ultra plan. Upload your source footage or a reference image to start your project.
Write your first prompt with mixed inputs. Combine a text description with an uploaded image or audio reference in one message, for example: "Take this street market footage and make it golden hour with warm haze and ambient crowd noise."
Review the output. Refine it by chaining follow-up instructions: "Tighten the pacing in the second half" or "Change the background to a nighttime city street while keeping the main subject the same."
To keep a character consistent across multiple clips, upload a reference image before starting. Then say: "Use the same character from the reference image, walking into a neon-lit corridor."
Export your clip from Google Flow. Build additional clips the same way, then stack them to assemble a multi-shot sequence. The same style and character carry through every cut automatically.
Pro tip: Pair Gemini 3.5 with Omni for an agentic pipeline. Have Gemini 3.5 write a shot list and script, then pass each shot to Omni as a separate prompt with a shared style reference. You get a full multi-clip sequence built by an agent, not assembled by hand.
TOGETHER WITH VIKTOR
One brand built 30+ landing pages through Viktor without a single developer.
Each page mapped to a specific ad group. All deployed within hours. Viktor wrote the code and shipped every one from a Slack message.
That same team has Viktor monitoring ad accounts across the portfolio and posting performance briefs before the day starts. One colleague. Always on. Across every account.
5,700+ teams. 3,000+ integrations.
SOFTBANK
SoftBank commits 75B euros to France's AI infrastructure
Recaply: SoftBank just committed up to 75 billion euros to build 5 GW of AI data center capacity in France, the largest single AI infrastructure investment in European history, announced at the Choose France summit.
Key details:
The first phase covers 45 billion euros and 3.1 GW in the Hauts-de-France region by 2031, across sites in Dunkirk, Bosquel, and Bouchain. SoftBank will partner with Schneider Electric for a manufacturing cluster at the Port of Dunkirk.
5 GW is a country-scale commitment. SoftBank's total investment of up to 75 billion euros is the largest single AI infrastructure bet in European history, per the official announcement.
Masayoshi Son said France is uniquely positioned to lead EU AI infrastructure, citing its industrial base, talent, and low-carbon electricity grid, according to the SoftBank press release.
Three Hauts-de-France sites are set to come online by 2031. Plans for additional sites across France are in development under the broader commitment.
Why it matters: SoftBank's Vision Fund era is done, but Son's appetite for large bets is not. France has clean power and industrial land, making it a strong base for EU AI compute. The Schneider deal adds a new angle: Europe won't just run AI, it'll also build the hardware. That changes the EU AI story from using local models to owning the physical stack.
TOOLS
Trending AI Tools
🤖 MiniMax M3 - MiniMax's first open-weights model with coding frontier performance, 1M context, and native multimodality, live on API today
🔊 MAI Voice 2 - Microsoft's next-generation voice generation model
⚙️ DeepSWE - Datacurve's benchmark for frontier coding agents on real developer tasks, measuring cost per task rather than total run
🤖 Nvidia Cosmos 3 - Open-source physical AI model combining vision reasoning, world generation, and action generation in a single unified architecture
NEWS
What Matters in AI Right Now?
Codex used Docker's root-level daemon and tmux panes to run privileged commands without sudo on a developer's PC. The workaround shows how agentic AI can probe OS permission boundaries in unexpected ways.
The US government moved to halt Nvidia AI chip exports to Chinese firms operating outside China, tightening restrictions on advanced AI hardware in a new enforcement step.
Nvidia released Cosmos 3, an open-source physical AI model with a dual-tower architecture combining a vision-language reasoner with a diffusion generator, available in Nano (8B) and Super (32B) variants on Hugging Face.
Nvidia introduced RTX Spark, a new Blackwell Superchip for Windows PCs with up to 6,144 GPU cores, 1 petaflop of FP4 AI performance, and 128GB unified memory, designed for agents and AI development.
Bain reported that enterprise AI savings misses should be making executives uncomfortable, with many AI projects failing to deliver on promised cost reductions.
Meta is reportedly developing an AI pendant wearable, adding to its hardware lineup alongside Ray-Ban smart glasses.
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Cheers, Jason
