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I Built a Telegram Client for Pi
Old MIDI Instruments Don't Like Modern MIDI. What's to Be Done?
Microsoft cuts 4,800 Jobs, Half from Xbox division
Triple Dragon Fractal (2020)
Microsoft is selling off four Xbox studios as part of significant gaming cuts
Microsoft is laying off 4,800 employees today, and more than 30 percent of the job losses are in the company's Xbox division. The significant gaming cuts will affect nearly every part of Xbox and also involve four game studios being spun off to be run independently from Microsoft. Today's layoffs, which are being described as […]
Microsoft is laying off 4,800 employees
A year after cutting around 9,100 employees, Microsoft is making further layoffs today as it begins its new financial year. The software maker is laying off around 4,800 employees today, approximately 2.1 percent of its workforce. Most of the employees affected by today's cuts are in Microsoft's commercial sales business or the company's Xbox division. […]
Aluminum foil (2021)
Nintendo announces new product revisions in Europe with replaceable batteries
Show HN: Scan your AI agents for dangerous capabilities
How Kalshi Infects the News
Why low-latency Java still requires discipline?
DKIM2 and DMARCbis Have Landed
Workers Cache
NoiseLang: Where N = 5 is a Dirac delta
Fable 5 On Vending-Bench: Misbehaving, With Plausible Deniability
Anthropic's Method to Losing Goodwill in a Few Easy Steps
Lost city discovered beneath Egypt's desert with ancient church
The AI Big Crunch Is Starting
Ask HN: Are there good security benchmarks for LLMs?
I'm looking for this myself but figured it's good to have an actual discussion about this. I'm pretty new to the benchmarking side of LLMs. For example, I looked at eyeballvull [1]. It seems promising but I don't see wide support for example. I respect the author for still committing. A benchmark where an agent scans a repo in full is what I'm looking for. But then I also wondered: maybe there are others out there that I haven't been aware of yet. And, at the risk of potentially being flooded, f