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AI · Sunday, 14 June 2026 · Issue 20 · 13 stories

SwiftVR upscales 1080p in real time, Mistral goes open speech

Models & Releases

SwiftVR delivers real‑time 1080p video upscaling on a consumer GPU

SwiftVR is the first generative video restoration model that streams 1080p video at roughly 26 fps on a consumer‑grade RTX 5090, and reaches 31 fps at QHD on a single H100. Its mask‑free shifted‑window attention and restoration‑aware autoencoder cut inference time dramatically, making real‑time upscaling practical for creators.

github.com ↗3 min read at source

Marin‑8B models debut as the first fully open JAX‑trained foundation models

Stanford’s CRFM released Marin‑8B‑Base and Marin‑8B‑Instruct, the first fully open‑source foundation models built with JAX, and shipped every artifact, code, dataset, hyperparameters, training logs, under Apache 2.0. This end‑to‑end transparency lets researchers reproduce, audit, and extend large‑scale models without opaque black‑boxes, raising the baseline for openness in AI.

Mistral Unveils Voxtral: Open‑Source 24B & 3B Speech Models for Scalable, Edge AI

Voxtral adds a 24‑billion‑parameter and a 3‑billion‑parameter speech model to Mistral’s open‑source lineup, delivering production‑grade transcription, semantic understanding, 32k‑token context, multilingual support and built‑in Q&A, summarisation, and function‑calling. Released under Apache 2.0, the suite promises half the cost of comparable proprietary APIs while enabling edge deployment.

mistral.ai ↗6 min read at source

Research

Energy‑Based Transformers Scale Faster and Think Deeper Than Standard Models

Energy-Based Transformers (EBTs) replace next‑token prediction with a learned verification function, letting models refine outputs via gradient‑based energy minimization. The paper shows EBTs scale up to 35% faster than standard Transformers and improve out‑of‑distribution performance by up to 29%, heralding a new, modality‑agnostic “System 2” thinking paradigm.

arxiv.org ↗131 min read at source

Adding a Daydreaming Loop Could Give LLMs True Insight

Gwern proposes adding a default‑mode ‘daydreaming’ loop to LLMs: a background process that samples concept pairs, generates novel links, and filters for value. This continuous, costly search could unlock genuine breakthroughs and supply proprietary data for future, more efficient models.

gwern.net ↗12 min read at source

Products & Industry

Thinking Machines Lab lands $2 B seed round, valuing startup at $12 B

Mira Murati's Thinking Machines Lab announced a $2 billion seed round that values the stealth startup at $12 billion. The round was led by Andreessen Horowitz and included Nvidia, Accel, Cisco and others, even though the company has no product or revenue yet. Murati says the first offering, with a major open‑source component, will arrive in the coming months.

reuters.com ↗4 min read at source

OpenAI taps Google Cloud to power ChatGPT in five key markets

OpenAI added Google Cloud to its supplier list, deploying ChatGPT and its API on Google’s platform in the US, UK, Japan, the Netherlands and Norway. The move diversifies its compute base beyond Microsoft, underscoring the escalating demand for AI‑scale infrastructure and reshaping the cloud rivalry landscape.

reuters.com ↗3 min read at source

Policy & Safety

Tools & Open Source

You’re caught up.

That was all 13 stories in the 14 June issue.