Salience Labs raised $125 million in an oversubscribed Series B to scale its photonic chip technology for AI data-centre optical switching. The round aims to accelerate deployment after the company demonstrated a 64-port all-optical photonic switch at ECOC 2026. The funding supports wider manufacturing and product development, including planned 128-port and 256-port switches, plus added locations and engineering hires.
Skeleton Technologies announced a Siemens investment that increased its valuation to over $1 billion and targets US manufacturing and Silicon Valley R&D for AI data-centre power systems.
The UK government’s Sovereign AI Fund invested in Augur, a UK security startup that uses AI to turn fragmented surveillance sensor networks into a real-time intelligence layer. The fund said it is operating as a £500m VC program and described its typical cheques as £5m to £10m, while not disclosing Augur’s specific investment amount. Augur will gain access to the Isambard-AI supercomputer to train multi-camera datasets and use its technology to help security teams identify risks as they develop.
Tracxn Technologies released its UK Tech – 9M 2026 report, finding that UK tech companies raised $25.7 billion in US-dollar equity funding from 1 January 2026 to 30 September 2026. Early-stage funding rose to $10.9 billion (up 58% from 9M 2025) while late-stage funding rose to $12.4 billion (up 121% from 9M 2025). London stayed the leading hub with 15 of 18 new unicorns, and the UK added 18 new unicorns in 9 months (up from 5).
ASML reported record results but said its planned lithography machine production capacity for 2027 and 2028 will not meet demand from chip customers already placing orders for 2029 and 2030. Revenue reached €11.7 billion (about $13.4 billion) in the third quarter of 2026. ASML is responding by expanding capacity plans by 30 percent for 2027 and reassessing whether it can exceed another 30 percent for 2028.
ScaleFlux argues that smarter SSD and CXL memory controllers can reduce AI data-movement bottlenecks by using NAND flash as active memory for key-value cache offload. It cites GPU memory-speed gaps of about 37 to 40 times slower for DRAM and about 800 times slower for storage. As a result, AI workloads could place more frequently used data on NAND via intelligent controller-driven placement and writes rather than waiting on slower memory/storage paths.
OpenAI says it discovered a sophisticated recording device hidden in one of its offices, then used its own AI models to help trace the device to an employee it says had planted it. The company says the case was reported to the FBI on October 13, 2026, and that it has no indication the person improperly accessed or exfiltrated model weights, source code, or customer data. OpenAI says the investigation will proceed with the FBI and the employee was arrested and terminated, changing the company’s immediate insider-threat response approach.
NVIDIA announced multiple deployments and partnerships across the U.K., spanning AI use in areas like healthcare, smart cities, finance, and quantum workflows. It committed $250 million over five years, including $50 million in accelerated computing access via BOLD at Oxford, SOFAIR at UCL, and Imperial College London. The effort shifts from AI ambition to operational application by funding research access and supporting organizations moving models and compute into real-time and large-scale services.
Applied Materials unveiled its new EPIC semiconductor R&D facility at its Sunnyvale, California campus to bring multiple chip companies into the same lab for early work on microprocessors and memory. The project is a $5 billion, 600,000-square-foot center. This co-location is intended to cut the “concept to commercialization” timeline from 10–12 years to as little as six and speed up next-generation AI-related chip development.
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