IT consultant and services provider Accenture has agreed to buy Speedtest and Downdetector owner Ookla from Ziff Davis for $1.2 billion in cash.

Accenture plans to integrate Ookla’s data products into its own offerings that are targeted at helping communications service providers, hyperscalers, government entities, and other types of customers “optimize … mission-critical Wi-Fi and 5G networks,” Accenture’s announcement today said.

Ookla’s platform also includes Ekahau, which offers tools for troubleshooting and designing wireless networks, and RootMetrics, which monitors mobile network performance.

Accenture plans to use data gathered from Ookla’s services for applications such as helping hyperscalers and cloud providers “ensure the resilience of AI infrastructure and edge datacenters, which deliver most of the inference workload,” improving fraud prevention in banks, conducting smart home analytics in utilities, and retail traffic optimization.

News Corp’s global chief executive has described news organisations as a valuable “input” for artificial intelligence, as the media empire signs an AI content licensing deal with Meta worth up to US$50m (A$71m) a year.

In an upbeat presentation, the chief executive of Rupert Murdoch’s company, Robert Thomson, said the “reliable” breaking news and information in publications like the Australian, the Times of London and Dow Jones was “hard to beat” as an “input” for AI.

The Meta deal, which was revealed by the Murdoch-owned Wall Street Journal earlier this week and is expected to last at least three years, will allow Facebook and Instagram’s parent company to scrape News Corp’s US and UK content to train its artificial-intelligence products.

The outlets include the Journal and the New York Post, but the Australian mastheads, which include the Daily Telegraph and the Herald Sun, are not part of the deal.

“We’re essentially an input company,” Thomson told a Morgan Stanley tech conference in San Francisco on Monday ahead of the landmark Meta deal.

Φ In the Phaedrus, Plato argued that the invention of writing would destroy our memory and replace true wisdom with a mere shadow of it. He believed that when we stop internalizing knowledge and start relying on external tools, we lose the ability to actually think. Thousands of years later, we are having the exact same conversation about Large Language Models and ChatGPT.

The danger of AI is not that it will become too smart, but that it will make us too lazy to be wise. True education is what Plato called a turning of the soul, a difficult process that requires active engagement. If you let a machine summarize the world for you, you are only holding onto dead speech. We must treat writing and thinking as a practice of the mind rather than a task to be automated.

🧠 Plato feared that external tools create the illusion of knowledge.
⚡ Large Language Models offer quick results while bypassing understanding.
🎓 Genuine insight comes from human dialectic and struggle.
🔍 We must focus on literacy that teaches how these algorithms function.

templeton.org/news/plato-warne…
#ArtificialIntelligence #Philosophy #Learning #ChatGPT #Education #Teaching #AI #Technology

The hed here is a bit misleading ... 40% of total staff is not 40% of an individual job.

Jack Dorsey cited AI as the driving force behind cutting 40% of his company’s employees, but other factors such as a weak crypto market, overstaffing and a declining stock price may also have motivated the move.

Last week, the financial technology company Block announced that it would lay off 4,000 of its 10,000 workers. Dorsey, Block’s CEO, said in a letter to shareholders that advances in AI “have changed what it means to build and run a company”.

“We’re already seeing it internally. A significantly smaller team, using the tools we’re building, can do more and do it better. And intelligence tool capabilities are compounding faster every week,” he wrote. He also said that Block’s business remained strong and that these cuts weren’t an austerity measure.

Can AI operate 40% of a business? Perhaps, but other specters haunt Dorsey’s company.

I'd be surprised if LLMs can handle 40% of anyone's job. You know what often can? Good, old-fashioned automation. It handles tedious tasks no one wanted to do in the first place and produces improved, predictable and testable results.

The Banality of Artificial Intelligence

What happens when an AI hallucination leads to bombing an elementary school?

By Michael Altfield
License: CC BY-SA 4.0
tech.michaelaltfield.net/

It appears likely that the US government is using Anthropic, OpenAI, Google and/or xAI data models for processing signals intelligence (SIGINT), for AI-generated "kill lists" to determine where to drop their bombs.

[right] This AI datacenter is a machinery of war. Its LLM hallucinations decide which children to assassinate [left] This IG Farben (Bayer/BASF) factory in Auschwitz produced Zyklon B for the Nazis, who murdered over a million children

In Apr 2024, +972 (an Israeli news outlet) published a >9,000 word article describing how the Israeli military had been using Artificial Intelligence to decide which (residential) buildings, hospitals, and schools to bomb in Gaza.

In Feb 2026, the US (and Israel) bombed Iran -- killing over 100 schoolchildren (and Ali Khamenei).

In Mar 2026, it appears that the US has likely built a similar system, leveraging US AI companies' tech to decide which (school) buildings to bomb, false-positive hallucinations be damned.

Who targeted the Shajareh Tayyiba girls' elementary school in Minab, Iran? Could it have been an AI hallucination? A false-positive?
...

Read the full article here:

• tech.michaelaltfield.net/2026/…

Burner accounts on social media sites can increasingly be analyzed to identify the pseudonymous users who post to them using AI in research that has far-reaching consequences for privacy on the Internet, researchers said.

The finding, from a recently published research paper, is based on results of experiments correlating specific individuals with accounts or posts across more than one social media platform. The success rate was far greater than existing classical deanonymization work that relied on humans assembling structured data sets suitable for algorithmic matching or manual work by skilled investigators. Recall—that is, how many users were successfully deanonymized—was as high as 68 percent. Precision—meaning the rate of guesses that correctly identify the user—was up to 90 percent.

The findings have the potential to upend pseudonymity, an imperfect but often sufficient privacy measure used by many people to post queries and participate in sometimes sensitive public discussions while making it hard for others to positively identify the speakers. The ability to cheaply and quickly identify the people behind such obscured accounts opens them up to doxxing, stalking, and the assembly of detailed marketing profiles that track where speakers live, what they do for a living, and other personal information. This pseudonymity measure no longer holds.

As you’ve probably heard, on Friday that political caprice came home to roost for many in Silicon Valley when Defense Secretary Pete Hegseth announced he was declaring Anthropic a “supply chain risk” and that no one with US military contracts could have a commercial relationship with the company any more (a gross exaggeration of what being declared a supply chain risk actually means, but that’s besides the point).

We’ve criticized these “supply chain risk” designations going back years, but mainly for how they tend to be used to prop up American companies against foreign (usually Chinese) competitors with little evidence regarding the actual risk. Of course, you can easily understand the stated intent of an “SCR” designation: if there’s a foreign company with ties to a government that is averse to the US, there is always a risk that the company could agree to sneak backdoors or spyware into the network and do something bad. Hell, it’s what the US does.

But here, it makes no sense at all. The only “risk” was Anthropic saying its technology shouldn’t be used for domestic mass surveillance or to power autonomous killing machines. There is no underlying risk.