Pivot to AI creator "David Gerard has been researching tech industry bullshit for many years now. For the sake of full disclosure, Gerard is a member of Stop Gen AI and my friend, so this isn’t an unbiased book review. But I will do my best to give you my honest impression of Libra Shrugged."

Libra Shrugged is a worthwhile read in 2026, because it's excellent historical context for the horrors of Gen AI today.

Libra was the cryptocurrency Mark Zuckerberg announced in 2019. It was renamed Diem, PayPal, Visa, and MasterCard have backed away since 2020, and it still has yet to launch!

Gerard researched Libra and Facebook thoroughly, and his 2020 book features his same sense of humour that Pivot to AI fans enjoy.

@davidgerard

https://stopgenai.com/stop-gen-ai-book-review-libra-shrugged-by-david-gerard/

Is #AI killing #opensource software?: https://thenewstack.io/is-ai-killing-open-source-software/ via @thenewstack & @sjvn

No, but it's certainly changing its fundamental assumptions.

"The private capital industry’s problems are far worse than Wall Street has acknowledged, as traditional metrics obscure weaknesses in the leveraged buyout market, according to a top credit hedge fund.

A “substantial portion” of the private equity industry is already “stressed or distressed”, said Tony Yoseloff, managing partner and chief investment officer at credit hedge fund Davidson Kempner Capital Management.

“You’re not looking at a problem five years from now, you’re looking at a problem that exists today.”

In new research to be published on Monday, the hedge fund, which manages more than $38bn of assets, gives a broad diagnosis of growing risks in the private capital industry, and why it soon expects buyouts from the last decade to crack. The hedge fund argues excessive leverage, weak cash flows and loose debt contracts have converged to create a ripe environment for corporate defaults."

https://www.ft.com/content/f77b2891-5d83-47a1-a328-1b526073a266

Esto es una puta barbaridad. Los dispositivos crecen en potencia y memoria constantemente y sin embargo cada vez tenemos que esperar más a que se cargue una web 😑

The 49MB Web Page
https://thatshubham.com/blog/news-audit

Grammarly pulls AI tool mimicking Stephen King and other writers

https://www.bbc.com/news/articles/cx28v08jpe7o

Watched that Louis Theroux manosphere documentary where that dude was like "what did women ever do to build the modern world?"

Well, for a start: the broad concept of computer programming, the first compiler, radio frequency hopping, numerous programming languages, the pertussis vaccine, chemotherapy, gas-powered central heating, and the use of the electric guitar for rock'n'roll.

God knows how to weigh those achievements up against hosting podcasts and wearing ill-fitting suits.

> When developers say that LLMs make them more productive, you need to keep in mind that this is what they’re automating: dysfunction, tampering as a design strategy, superstition-driven coding, and software whose quality genuinely doesn’t matter, all in an environment where rigour is completely absent.

https://www.baldurbjarnason.com/2026/the-two-worlds-of-programming/

by @baldur

"Each time one person contributes data to improve an AI model, that model becomes better — not just at doing that individual’s job, but at doing the job of everyone in that role, anywhere.

In that sense, workers can end up competing against one another by supplying data too cheaply to companies or intermediaries that recruit people to train AI to do their jobs. When this happens, individuals may unintentionally undermine the bargaining power of others in their occupation.

If the goal is to ensure that workers share in the gains from AI, co-ordination may be necessary. Without it, individuals may strengthen the very systems that weaken their collective bargaining power. Instead, co-operation can benefit workers and companies alike. If fear about career risk leads people to hold back knowledge from AI systems, productivity may suffer. Smart companies will know that finding ways to recognise workers for their talent will ensure that they continue to supply it.

What, then, is to be done? As workers, people should think about how to use AI to expand their skills: whether by building complementary capabilities or by finding ways to scale their expertise through AI systems. As citizens, they should press for policies that give workers clearer rights over the data generated by their work and compensation for it."

https://www.ft.com/content/23c70905-147d-4213-8c30-c43e3bde7fec

#AI #AITraining #GenerativeAI #Automation #Productivity