POLICY

EU could loosen privacy, tech regulations

The European Union might be rolling back its red tape. 

The European Commission will unveil a “digital omnibus” package in late November, according to POLITICO, aimed at simplifying its tech and privacy laws. The amendments include broad changes to the General Data Protection Regulation, the EU’s strict rules governing individuals’ control over their personal data. 

The move could open doors for tech giants seeking to grow their AI footprint in Europe, something which model providers are already ramping up to do.

• Bloomberg reported in late October that ChatGPT Enterprise adoption is up sixfold year-over-year in Europe, the Middle East and Africa.

• As part of its broader international expansion, Anthropic last week announced new offices in Paris and Munich. The company noted in a press release that the region has become its fastest-growing market, with customers representing more than $100,000 in run-rate revenue growing ten times over the past year.

The move could also help strengthen homegrown AI in the region. While the EU has a few stand-out AI firms, such as Mistral AI and DeepL, the region has largely struggled to keep pace with the rapid development of U.S. and Chinese firms. 

This move is not the region’s first attempt to try and compete. In early October, EU officials outlined two plans to boost AI adoption and research, and announced a $1.1 billion investment in doing so. The plans specifically target European workforces adopting the tech and raising the profile of the EU’s AI-powered scientific research. 

And following pressure from the Trump administration and Big Tech, the European Commission is also reportedly weighing plans to delay parts of the EU AI Act, a landmark initiative to rein in AI development that could pose a risk to people’s safety, offering a yearlong “grace period” to companies that break these rules.

The EU differs from the U.S. and China in one main way: stringent tech regulation that protects people over companies. The region has largely prioritized data security and safety over moving fast and breaking things, as evidenced by the EU AI Act’s passing in the first place. Upending the GDPR marks a stark 180 in the region’s approach to AI regulation thus far — and its tech policy strategy as a whole — potentially signalling a shift in priorities as the tech continues its rapid ascent. 

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PRODUCTS

Google eyes Maps for AI integrations

Google Maps is getting an AI upgrade. 

The search giant has added a number of Gemini-powered features to its GPS app in recent weeks. The latest feature, released Monday, is a builder agent and a model context protocol server to help developers create interactive projects using Maps data and code, powered by its Gemini models. 

The features come just days after Google announced several new consumer-focused features for the popular app, including: 

• Landmark-based mapping that directs users based on things like gas stations, restaurants and famous buildings that are easy to spot;

• Proactive traffic alerts, even when a user isn’t navigating; 

• And a “lens” feature that gives users conversational insights, allowing users to ask questions about whatever is in front of them. 

These features, while targeting two different audiences, underscore the vast opportunity that Google has with the navigation app. Though Google Maps’ exact user numbers aren’t available, the company noted that the app has more than one billion monthly users worldwide. 

As Google fights for AI dominance over competitors like OpenAI, Microsoft and Amazon, Maps’ solid consumer user base uniquely positions it to expose its Gemini models to a wide audience.

Embedded features like these may help with adoption as consumers are still warming up to trusting and using AI in their day-to-day lives. The developer features, meanwhile, could help it secure a more enterprise-focused audience and leverage the vast amount of data that it has through Maps. 

In both cases, these features put Google’s AI models in front of a massive audience.

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RESEARCH

AI needs to do more than talk

The next step change in AI might not be large language models. 

Spatial intelligence, or AI that can understand the world visually, might be the “next frontier” of the technology, Dr. Fei-Fei Li, a Stanford University computer science professor and founding co-director of Stanford’s Human-Centered AI Institute, wrote in an essay published Monday.

In the essay, Li, who founded large-scale visual learning benchmark ImageNet, called spatial intelligence “the scaffolding upon which our cognition is built,” She argues that that perception and action are the “core loop driving the evolution of intelligence,” and machines have yet to achieve the “fluency” of spatial intelligence, such as the ability to make split second decisions or communicate through gestures. 

While significant strides have been made in the field, such as multimodal language models and video generation tools, “spatial capabilities remain far from human level.” The next frontier, she notes, are building world models, or those capable of understanding dynamically complex worlds, both real and virtual.

• A good world model has three qualities: physically consistent generation, understanding multimodal inputs, and the ability to output “next states.” 

• While the scope of this challenge is wide, the gains could be massive. It could supercharge creativity in the short term, robotics in the mid term and education and scientific discovery in the long term. 

“Our dreams of truly intelligent machines will not be complete without spatial intelligence,” she concludes. 

Li’s essay highlights that the key to unlocking real value from AI might lie beyond just making language models bigger and better (despite the fact that some of the biggest model developers are keenly focused on besting each other's LLMs). A number of companies, both startups and Big Tech alike, have dedicated resources to boosting this intelligence.

And Li isn’t the first AI leader to make this declaration. Yann LeCun, chief scientist of Meta AI, made a similar point in an interview with journalist Alex Kantrowitz back in May, noting that “We are not going to get to human-level AI just by scaling up LLMs.”

LINKS

• CoreWeave revenue more than doubles amid AI infrastructure boom

• Hundreds of people have been hacked with government spyware

• AI server startup Majestic Labs raises $100 million 

• Amazon Prime’s “House of David” used more than 350 AI-generated shots

• XAI to host a hackathon in the SF Bay Area in December

• Rumble will acquire AI infrastructure firm Northern Data for $970 million

• Legal AI startup DeepJudge raises $41 million for custom law firm search engines

• C3.ai is possibly exploring a sale following a leadership change

• Meta Generative Ads Recommendation Model: A new foundational model to help businesses get more value out of their ads on Instagram.

• Taku: An operating system built for AI, generates apps and builds tools for users and agents. 

• Logical: A “proactive” AI copilot for desktop that suggests email drafts, tracks to-do lists and provides meeting insights. 

• Jarmin.ai: A round-the-clock machine learning engineer for building and shipping production-ready AI features. 

• Replit AI Integrations: Build AI apps through Replit with access to more than 300 models, no API keys or setup necessary

• OpenAI: Deployed Researcher, Strategic Deployment

• Uber: Sr. Machine Learning Engineer, Earner Growth

• Meta: Research Engineer, Language - Generative AI

• Google: Senior Software Engineer, AI/ML, YouTube

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