Odyssey-3 connects a world model to robot control. Figure takes Helix 2.5 into thirty unfamiliar homes. Jev brings fast decisions into agent workflows, while an experiment with communities of agents shows how a malicious message can influence behavior almost two days later.
In this episode of Attention Span, we connect the week’s developments in AI’s ability to understand and act in the world. We explore Reka’s world-model plans, why handing a box to a person is brutally hard, and how FAMOS infers an object’s moving parts from incomplete observations. I also share my Dreamforce conversation with Salesforce’s AI research team about learning from feedback and updating models after deployment.
We finish with Google’s household assistant CC, Edison Scientific and FutureHouse’s Millennium Problems for Biology, and the questions raised by the new DeepMind Institute.
👇 Which of these developments deserves a deep dive? Tell us in the comments.
🔳 SPONSORSHIP
Partner with Turing Post to reach AI engineers, researchers, and builders: ks@turingpost.com
🔷 WORLD MODELS
Odyssey-3 announcement and demonstrations https://odyssey.systems/introducing-odyssey-3
Reka’s omni-world-model research direction https://reka.ai/news/evolution-of-llms-omni-world-models
🔶 ROBOTS, GENERALIZATION & MEMORY
Figure Helix 2.5: zero-shot tests in 30 homes https://www.figure.ai/news/helix-2-5-zero-shot-30-home-generalization
Index human-behavior dataset, background https://www.figure.ai/news/introducing-index
Agility Digit 5 https://www.agilityrobotics.com/solutions/digit-5
Agility’s safety interview https://www.youtube.com/watch?v=2dbyg67EtUA
FAMOS paper https://arxiv.org/abs/2609.20817
FAMOS demonstrations https://kevinqu7.github.io/famos/
Workspace Models paper and task examples https://arxiv.org/html/2609.20820v1
🔹 DREAMFORCE & LEARNING FROM FEEDBACK
Salesforce Koa announcement https://www.salesforce.com/news/press-releases/2026/09/15/koa-reasoning-model/
How Salesforce trained Koa https://www.salesforce.com/news/stories/why-we-post-trained-our-own-reasoning-model/
🔸 EMERGENCE WORLD & AGENT MEMORY
Season 2 research paper https://world.emergence.ai/publication/emergenceworld-s2.pdf
Season 2 video https://www.youtube.com/watch?v=LTtbTEufPGA
🔹 JEV & FAST AGENT DECISIONS
TypeSafe AI’s Jev announcement https://typesafe.ai/blog/introducing-system-one-models-and-jev
Our detailed guide: Jev, RLCD, and the AI classifier https://www.turingpost.com/p/what-is-jev-rlcd
Jev on Vercel AI Gateway https://vercel.com/changelog/typesafe-ai-jev-now-available-on-ai-gateway
LangChain: building a harness with Jev https://www.langchain.com/blog/building-a-harness-with-jev
🔸 GOOGLE CC
Google’s experimental agent for families and households https://blog.google/innovation-and-ai/models-and-research/google-labs/cc-expanding-to-groups/
🔺 DEEPMIND INSTITUTE & SCIENTIFIC AMBITIONS
Introducing the DeepMind Institute https://institute.deepmind.com/essays/introducing-the-deepmind-institute/
DMI essays https://institute.deepmind.com/#essays
The Millennium Problems for Biology https://millenniumproblems.bio/
Organizations behind the Millennium Problems for Biology: Edison Scientific https://edisonscientific.com/ and FutureHouse https://www.futurehouse.org/
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