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The surveillance browser trap: AI companies are copying Big Tech’s worst privacy mistakes

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The browser wars are back — only this time, the battleground isn’t tabs or load times. It’s intelligence.

A new wave of AI-powered browsers promises to transform how we interact with the web, turning passive pages into active assistants that summarize, search, automate, and act on your behalf. But while the tech may feel novel, the business model behind it isn’t. These browsers don’t just offer smarter tools — they risk ushering in a new era of data extraction, baked into the very architecture of how we browse.

Andrew Frost Moroz

Privacy-focused tech innovator and the creator of Aloha Browser.



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China unveils ‘world’s first’ brain-like AI, 100x faster on local tech

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Researchers at the Chinese Academy of Sciences’ Institute of Automation in Beijing have introduced a new artificial intelligence system called SpikingBrain 1.0. 

Described by the team as a “brain-like” large language model, it is designed to use less energy and operate on homegrown Chinese hardware rather than chips from industry leader Nvidia. 

“Mainstream Transformer-based large language models (LLMs) face significant efficiency bottlenecks: training computation scales quadratically with sequence length, and inference memory grows linearly,” said the researchers in a non-peer-reviewed technical paper. 

According to the research team, SpikingBrain 1.0 performed certain tasks up to 100 times faster than some conventional models while being trained on less than 2% of the data typically required.

This project is part of a larger scientific pursuit of neuromorphic computing, which aims to replicate the remarkable efficiency of the human brain, which operates on only about 20 watts of power.

“Our work draws inspiration from brain mechanisms,” added the researchers.

To replicate efficiency of human brain

The core technology behind SpikingBrain 1.0 is known as “spiking computation,” a method that mimics how biological neurons in the human brain function. 

Instead of activating an entire vast network to process information, as mainstream AI tools like ChatGPT do, SpikingBrain 1.0’s network remains mostly quiet. It uses an event-driven approach where neurons fire signals only when specifically triggered by input. 

This selective response is the key to reduced energy consumption and faster processing time. To demonstrate their concept, the team built and tested two versions of the model, a smaller one with 7 billion parameters and a larger one containing 76 billion parameters. Both were trained using a total of approximately 150 billion tokens of data, a comparatively small amount for models of this scale.

The model’s efficiency is particularly notable when handling long sequences of data. In one test cited in the paper, the smaller model responded to a prompt consisting of 4 million tokens more than 100 times faster than a standard system. 

In a different test, a variant of SpikingBrain 1.0 demonstrated a 26.5-fold speed-up over conventional Transformer architectures when generating just the first token from a one-million-token context.

Stable performance

The researchers reported that their system ran stably for weeks on a setup of hundreds of MetaX chips, a platform developed by the Shanghai-based company MetaX Integrated Circuits Co. This sustained performance on domestic hardware underscores the system’s potential for real-world deployment.

These potential applications include the analysis of lengthy legal and medical documents, research in high-energy physics, and complex tasks like DNA sequencing, all of which involve making sense of vast datasets where speed and efficiency are critical.

“These results not only demonstrate the feasibility of efficient large-model training on non-NVIDIA platforms, but also outline new directions for the scalable deployment and application of brain-inspired models in future computing systems,” concluded the research paper.



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Flexential Hires Greg Ogle as CIO to Accelerate IT Transformation and AI Strategy

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Data center veteran to drive AI integration and advance security across Flexential’s operations and customer-facing systems

DENVER, Sept. 10, 2025 /PRNewswire/ — Flexential, a leading provider of secure and flexible data center solutions, has appointed Greg Ogle as Chief Information Officer (CIO) to unify its internal technology systems, strengthen cybersecurity oversight, and lead the next phase of its digital and AI-enabled transformation.

Ogle brings more than 25 years of experience aligning enterprise IT with business goals, most recently as Vice President of Global IT Infrastructure and Cloud Operations at Equinix. In that role, he directed global networks, cloud platforms, and enterprise applications, and served a board-appointed term as the interim Chief Information Security Officer.

As Flexential’s CIO, Ogle will also oversee enterprise systems, cloud architecture, data governance, and AI integration. Additionally, he will shape IT policy and investment strategy, support compliance efforts, and modernize the company’s digital foundation. His appointment comes as demand for hybrid infrastructure and AI-ready capacity accelerates, and data center vacancy rates dipped to a low of 1.6% in primary North American markets earlier this year.

“Greg has a proven track record of leading IT in complex, high-stakes environments,” said Ryan Mallory, President & COO at Flexential. “He brings the operational discipline and forward-looking vision we need as we embed AI more deeply into our technology and processes. Greg’s leadership will ensure our systems are more intelligent, resilient, and efficient, enhancing both the employee experience and the way customers engage with our services.

Ogle’s immediate focus will be on unifying Flexential’s technology stack, building a standardized architecture for digital services, and embedding AI across IT operations. His broader strategy includes streamlining platform portfolios and engineering processes, as well as reinforcing governance through centralized tools and policies.

“Flexential is at a pivotal moment, where the convergence of AI, cloud, and hybrid infrastructure are reshaping how enterprises operate,” said Greg Ogle, CIO at Flexential. “I’m excited to build on Flexential’s strong foundation to deliver technology that is smarter, more secure, and more connected. My focus will be on ensuring our digital backbone not only supports today’s needs but also provides the resiliency and trust our customers require as we prepare for the opportunities of tomorrow.”

Ogle’s appointment follows a series of recent leadership moves at Flexential aimed at supporting its long-term infrastructure strategy. In July, the company appointed Thomas Bailey as Vice President of Energy and Matthew Baumann as Vice President of Site Acquisition to expand development capacity and secure long-term power access. Flexential has also raised approximately $1 billion from GI Partners, GI Data Infrastructure, Hamilton Lane, and Morgan Stanley Infrastructure Partners in the last 12 months to support its continued expansion.

For more information on Flexential’s secure infrastructure and flexible IT solutions, visit www.flexential.com.

About Flexential
Flexential empowers the IT journey of the most complex businesses by offering customizable IT solutions designed for today’s demanding high-density computing requirements. With colocation, cloud, connectivity, data protection, and professional services, the FlexAnywhere® platform anchors our services in 40+ data centers across 18 highly connected markets on a scalable 100Gbps+ private network backbone. Flexential solutions are strategically engineered to meet the most stringent challenges in security, compliance, and resiliency. Experience the power of IT flexibility and how we enable digital transformation at www.flexential.com.

Media Contact
Alison Brooker
Corporate Marketing
[email protected]

Christian Rizzo
Gregory FCA for Flexential
[email protected]

SOURCE Flexential



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Google Cloud CEO Says Tech Giant Has ‘Made Billions’ on AI

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Google Cloud’s chief executive has reportedly outlined how the company is generating revenue through AI services.

“We’ve made billions using AI already,” Thomas Kurian said Tuesday (Sept. 9) at the Goldman Sachs Communacopia and Technology Conference in San Francisco, CNBC reported.

“Our backlog is now at $106 billion — it is growing faster than our revenue. More than 50% of it will convert to revenue over the next two years,” Kurian said.

Google reported revenue of $13.62 billion for its cloud computing unit, up 32% over the previous year. The company’s cloud business trails those of Microsoft and Amazon, the report noted, but is growing faster than them.

In some cases, the revenue comes from people paying by consumption, such as enterprise customers who purchase artificial intelligence infrastructure. Others pay for cloud services through subscriptions.

“You pay per user per monthly fee — for example, agents or Workspace,” said Kurian, referring to the company’s Gemini products and Google Workspace productivity suite, which come with a number of subscription tiers.

Kurian told the conference that upselling is another important part of Google Cloud’s strategy.

“We also upsell people as they use more of it from one version to another because we have higher quality models and higher-priced tiers,” he said, also noting that Google is capturing new customers more quickly.

“We’ve seen 28% sequential quarter-over-quarter growth in new customer wins in the first half of the year,” said Kurian, with nearly two-thirds of customers already using Google Cloud’s AI tools.

In other Google Cloud news, the company’s head of strategy, Web3 said recently that Google’s Layer 1 blockchain will provide a neutral infrastructure layer for use by financial institutions.

In a post on LinkedIn, Rich Widmann wrote that the blockchain, Google Cloud Universal Ledger (GCUL), “brings together years of R&D at Google to provide financial institutions with a novel Layer 1 that is performant, credibly neutral and enables Python-based smart contracts.”

Linking to a March report by PYMNTS, Widmann added that CME Group employed GCUL to as it explored tokenization and payments on its commodities exchange.

“Besides bringing to bear Google’s distribution, GCUL is a neutral infrastructure layer,” Widmann wrote in his post. “Tether won’t use Circle’s blockchain — and Adyen probably won’t use Stripe’s blockchain. But any financial institution can build with GCUL.”

Widmann said Google Cloud will reveal additional technical details about GCUL within months.



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