Arlequin AI SAS announced it raised €28 million to develop a new AI model architecture built on topological neural networks rather than the graph-based networks used in most large language models. The Series A round totaled €28 million (about $32 million) and was exclusively backed by European investors, co-led by Redalpine and OTB Ventures. The funding will support scaling its platform and proprietary model, expanding its team, and accelerating commercial deployment across Europe and worldwide.
Skild AI launched its S1 robot foundation model that uses a single video demonstration to learn and perform new long-horizon tasks without updating model weights. It reports up to 10-minute unfamiliar task execution and an about 66% step success rate versus 9% for a similar system. As a result, robots can be adapted to changing factory work with in-context learning rather than retraining and post-training for each new task.
Cognition launched SWE-2, a post-trained coding model built from Kimi K3 and further trained with RL to optimize cost and capability. It scores 50.0% on FrontierCode 1.1 Main while being 64% cheaper than Fable 5.1 and about a quarter of the cost versus GPT-6 Astra. Compared with SWE-1.7, it uses 58% fewer turns, costs 81% less, and scores higher, and it’s available in Devin Desktop and CLI.
Maven Robotics won a logistics automation deal by proposing end-to-end, warehouse-linked robotics after getting a factory visit, then expanded to running up to eight robots for 16 hours per day with 99% uptime.
Nvidia and Palantir announced they are applying their “sovereign AI” partnership inside Nvidia by fine-tuning a supply-chain AI model for Nvidia’s own operations. The fine-tuned Nvidia Nemotron 3.5 Lightning uses 30B parameters and it achieved 86.7% accuracy versus 55.5% for a 550B Nemotron model (about 18 times larger). Nvidia says this demonstrates specialization on a focused task and plans to extend the approach to other industries while letting customers train and run tailored versions with data and weights kept under their control.
Arlequin AI raised €28 million in Series A funding to accelerate development of its topological neural network architecture and broaden international deployment. The round totals €28M, co-led by redalpine and OTB Ventures with Bpifrance’s Defence Innovation Fund participating. It will expand the international team building and training proprietary models, support commercial rollout, and add London and Berlin offices plus an AI lab in Silicon Valley soon.
Every AI story that matters,
in your inbox by 8am.
TLDRocket reads all relevant sources, removes duplicate coverage, and summarises the
day in two minutes. Follow companies and topics for alerts, or get the
briefing in Slack. Free, no spam, unsubscribe anytime.
Reading TLDRocket needs no cookies, and the readership counts we rely on come from
our own cookieless analytics. Google Analytics is the exception: it sets cookies and
reports to Google, so it stays switched off until you allow it. You can change your
mind any time from “Cookie settings” in the footer.
Strictly necessary
Session security and form protection (tldrocket-session,
XSRF-TOKEN, 2 hours). The site cannot work without them,
so they need no consent.
Always on
Google Analytics 4 (_ga,
_ga_<id>, up to 2 years). Measures which
stories and sections readers use. Google acts as a third-party processor and may
store the data outside the EU. No advertising, no profiling, no data sold.
