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Munich-based NavVis, which provides enterprises with spatial data on factories, plants, buildings, and more, raised an $85M Series D led by The Jordan Company (Rahul Raj/EU-Startups)
https://www.eu-startups.com/2026/08/munich

Munich-based NavVis raises €73.7 million to build its spatial data engine and accelerate AI roadmap | EU-Startups
NavVis, a Munich-based spatial twin platform for the built world, has raised a €73.7 million ($85 million) Series D round to build its massive spatial

#Strava hat jetzt also einen #MCP Server an den Start gebracht.
Und damit der Sinn ergibt, hat man gleichzeitig 3rd Party Tools den #API-Zugriff entzogen.
Vielleicht sollte Strava die Sinnhaftigkeit des …

🔊 #NowPlaying on #BBCRadio3:
#Radio3Breakfast
- Start the day on the right note with classical music
Hannah French presents Radio 3's Breakfast show. To get in touch, email 3breakfast@bbc.co.uk.
Relisten now 👇
https://www.bbc.co.uk/programmes/m002x5vv

ANNS-AMP: Accelerating Approximate Nearest Neighbor Search via Adaptive Mixed-Precision Computing
Mingkai Chen, Cheng Liu, Shengwen Liang, Lei Zhang, Xiaowei Li, Huawei Li
https://arxiv.org/abs/2606.07156 https://arxiv.org/pdf/2606.07156 https://arxiv.org/html/2606.07156
arXiv:2606.07156v1 Announce Type: new
Abstract: Approximate nearest neighbor search(ANNS) is a critical kernel in modern applications such as LLM and recommendation systems.However,its efficiency is fundamentally limited by the need to compute distances between a query and a massive number of high-dimensional vectors,most of which are non-neighbors.Existing approaches reduce redundancy via index optimization or early termination,but remain constrained by fixed-precision computation,leading to unnecessary arithmetic and memory bandwidth overhead.This paper presents ANNS-AMP,an adaptive mixed-precision framework and accelerator that adapts the precision of distance computation to the characteristics of queries and data distribution.The key insight is that different regions of the vector space require different levels of precision to preserve top-k accuracy.ANNS-AMP leverages the clustered structure of PQ-based indices and introduces a lightweight predictor to determine cluster-level precision at runtime based on features such as scale,radius,and query distance.To efficiently realize variable-precision execution,we design a bit-serial accelerator with a bit-interleaved data layout,enabling throughput to scale with reduced precision while mitigating memory bandwidth bottlenecks and load imbalance through a greedy scheduling strategy.Moreover,the runtime predictor can also reuse the bit-serial computing array for efficient runtime prediction and can be fitted to the ANNS pipeline without performance penalty.According to our experiments on representative datasets,ANNS-AMP achieves 163.76x,10.57x,and 2.06x performance speedups on average,and reduces average energy consumption by 1100.00x,39.41x,and 6.66x compared to CPU,GPU,and customized ANNS accelerator baselines,respectively,while maintaining accuracy loss below 2.7%.These results demonstrate that adaptive mixed-precision computing is a promising direction for efficient large-scale ANNS.
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Would have been a massive start for Norway, but the offside decision is correct and the goal struck off.
#BRANOR #WorldCup #fedifc

Amazon, Google, and Microsoft are “all engaged in a combination of multiple outright price increases and changing their core subscriptions to force AI features on them as a means of boosting revenues and conning the street into believing that ‘AI is paying off’ every time they non-consensually thrust it on their customers, framing higher prices as ‘better value’ in a way that fucks the user to appease Wall Street.”

Amazon, Google, and Microsoft are “all engaged in a combination of multiple outright price increases and changing their core subscriptions to force AI features on them as a means of boosting revenues and conning the street into believing that ‘AI is paying off’ every time they non-consensually thrust it on their customers, framing higher prices as ‘better value’ in a way that fucks the user to appease Wall Street.”

Day 3 of #dhbenelux2026 starts with a key panel on “Invisible Stories: Labor, Infrastructure, Recognition.”
#dhbenelux26

Day 3 of #dhbenelux2026 starts with a key panel on “Invisible Stories: Labor, Infrastructure, Recognition.”
#dhbenelux26

Day 3 of #dhbenelux2026 starts with a key panel on “Invisible Stories: Labor, Infrastructure, Recognition.”
#dhbenelux26