Vast Data tackles data sync problems in AI pipelines
SiliconANGLE: Vast Data bets stitched-together AI pipelines can’t keep sensitive data in sync
Data sovereignty is becoming an architectural problem as enterprises push artificial intelligence inference toward their most sensitive information. Pipelines assembled from separate tools struggle to keep embeddings, permissions and source data aligned, leaving many valuable data sets out of AI’s reach. The shift from model training to inference is changing what AI infrastructure has to […] The post Vast Data bets stitched-together AI pipelines can’t keep sensitive data in syn
Get smart on it
As enterprises move artificial intelligence from training to inference on sensitive corporate data, they face a challenge: data assembled through multiple separate tools often loses synchronization between updated information, user permissions, and the vector embeddings that AI systems use. This creates a problem where valuable regulated datasets remain inaccessible to AI because companies cannot reliably keep data in sync across their pipeline components. One company argues that integrated platforms combining storage and data processing functions can maintain tighter control over data access and consistency than the current approach of stitching together best-of-breed components. The company has also announced a confidential AI runtime that uses secured virtual machines and cryptographic verification to allow frontier models to access sensitive data in regulated industries while maintaining strict access controls and audit logs.
Relevant courses
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on MavenRelated news
How Third Moment Research runs 10,000 agents for 36+ hours
With GPT-6 Astra and GPT-6.1 Sol, Codex, and Daybreak for cybersecurity, this AI lab builds agents that focus for days and improve with use.
SolarWinds’ Avior pairs AI agents with deterministic execution for enterprise IT
Observability and information technology management software company SolarWinds Worldwide LLC today unveiled Avior, a standalone agentic artificial intelligence system built to take on first-line operations work for enterprise IT teams. The launch goes after the reliability problem that comes with letting AI agents act on production systems. SolarWinds argues that an agent producing different outcomes […] The post SolarWinds’ Avior pairs AI agents with deterministic execution for ent
Google DeepMind and Singapore Government announce new AI tool to protect citizens against scams
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Epic Games reportedly pivoting to "AI first" game development model
Epic Games is shifting to an "AI first" development strategy for its collaboration with the Walt Disney Company, letting AI models write all the code and guide all the artwork for an upcoming shooter. That's according to a Bloomberg report, which cites unnamed people familiar with the project who commented on the significant pivot in internal development at the Unreal Engine maker. Human developers will be tasked with managing and guiding code and art assets generated by models such as Anthropic
Also reported by The Verge
Laplace Intelligence red-teams robots and self-driving cars before they hit the real world
University of Michigan spinout Laplace Intelligence uses AI agents and interactive simulation to stress-test robots and self-driving vehicles before deployment. The profitable startup is competing at TechCrunch Disrupt's Startup Battlefield.
Pluto Security raises $42M as AI gives enterprise security teams a new headache
The problem with giving everyone in a company access to AI tools is that people will use them in unexpected ways. And that fact is steadily seeding fears that companies now have new, gaping security holes in their systems or, at least, will soon.