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Pika H3 Flex debut as #1 open weight model on DesignArena

, 8 items in AI Leaders and Thinkers, 4 min read

In this digest (8 items)

Pika H3 Flex debuts as the #1 open weight model on DesignArena’s t2v board, offering exportable audio stems and up to 4k resolution. It generates a 15-second clip with soundtrack in as little as 7 seconds and runs faster than real time.

Key points

  • Rank: 1 open weight model on DesignArena’s t2v board

  • Speed: 15-second clip with soundtrack produced in 7 seconds, faster-than-realtime generation

Sources

GeneralMagic AI 2x more accurate, 24 s faster

GeneralMagic AI was 2x as accurate and 24 seconds faster on average than 7 frontier models and 2 enterprise assistants in an underwriting benchmark. The test used the same insurance documentation for all systems.

Key points

  • Benchmark: compared against 7 leading frontier models and 2 enterprise AI assistants using the same insurance documentation

  • Result: 2x as accurate and 24 seconds faster on average than the other AI systems tested

Sources

Dream introduces new models and raises $17M seed

Dream announced a new class of models that reason about physical space, geometry, constraints, and object-space relationships. The startup disclosed $17 million in seed funding and targets the $13 trillion architecture, engineering, and construction industry.

Key points

  • Funding: $17M seed from a16z, svangel, xyz_vc, and ziggcap.

  • Focus: models trained to reason about physical space, its geometry, constraints, and object-space relationships.

Sources

Cohere Series E funding up to CAD $7B at $35.7B valuation

Cohere announced the initial close of its Series E, targeting up to CAD $7 billion and a CAD $35.7 billion valuation. The round is described as the largest private financing round in Canadian startup history.

Key points

  • Series E initial close targeting up to CAD $7 billion

  • Valuation set at CAD $35.7 billion

  • Largest private financing round in Canadian startup history

Sources

Atelico AI Engine launches on-device game AI, 121 FPS

Atelico AI Engine is a library that runs AI inside games and now achieves 121 FPS while generating text. It bundles language models, image generation, voice, speech recognition, lip-sync, memory, search, guardrails, and a behavior engine. The engine integrates with Godot, Unity and Unreal and supports Windows, macOS, Linux, iOS and Android.

Key points

  • FPS: first test dropped from 123 FPS to 3 FPS; after engine integration the same scene holds 121 FPS while a model generates text.

  • Compatibility: plugs into Godot, Unity and Unreal, has a C ABI, and runs on Windows, macOS, Linux, iOS and Android.

Sources

Le Chonk weights released; ranks #1 on FrontierCode

Le Chonk weights released; ranks #1 on FrontierCode and sets a new Pareto efficiency benchmark on artificialanalysis. Positioned for cyberdefense, tested by CrowdStrike, Cloudflare, Rubrik, Zscaler and others, and available on HuggingFace for customization with Mistral Forge.

Key points

  • Rank: 1 on @cognition’s FrontierCode among open models

  • Benchmark: new benchmark for Pareto efficiency on @artificialanalysis

  • Testing: evaluated by CrowdStrike, Cloudflare, Rubrik, Zscaler and others

  • Availability: download weights on HuggingFace; customize with Mistral Forge

Sources

Relics – new domain-specific swarm configurations announced

Relics introduces domain-specific configurations that change how an entire agent swarm operates. Installing a Relic gives a swarm the methods, infrastructure, and research machinery of that field. Available now to enterprise ArkenOS customers and rolling out to all users soon.

Key points

  • Relics package all skills, tools, environments, hooks, evals, verifiers, and guardrails into domain-specific configurations.

  • Installing a Relic makes a swarm inherit the methods, infrastructure, and research machinery of that field.

Sources

Vercel agents can send feedback via Vercel MCP

Vercel agents can send feedback via Vercel MCP, attaching structured context to comments. Use plain language to describe bugs or feature requests; the system calls submit_feedback.

Key points

  • Capability: agents can send feedback to Vercel.

  • Method: submit_feedback via Vercel MCP attaches structured context and submits the comment.

Sources