𝙲𝚘𝚛𝚗𝚘𝚔𝚞𝚗

@alphafox Propranol. ~80mg dose @ ~176lbs

How do you delete something you watched from your brain? 😵‍💫

@eMTBrides Goddamnit I have a serious weakness for cute goths... wow...

She’s all natural! 😏 Bro double dunked it in a row😭💔 via David Alvarez

@SenWarren I think you are a profoundly stupid woman. Where is your God now?

Pete Hegseth called rules of engagement "stupid." But those rules can help prevent tragedies like bombing an elementary school in Iran. Commanders agree.

this is so accurate

The longer you’re in Bitcoin, the less you try to help other people understand Bitcoin. Not because you become less passionate or less convicted. But because you get burnt out by how incredibly retarded and self-sabotaging the people you’re trying to help truly are. Fuck ‘em.

@ItsMrsRabbitToU LOL. You're retarded.

White men are the problem. If you read this and get offended, yes it’s about you.

@HowlingRedcoat He shouldn't be let back into the country. Let him stay in Cuba.

Rape Hasan Piker.

>Steals a gun >Sees a random asian woman >Shoots her >Kills her >Kills her unborn baby >Overwhelming evidence >Admits to doing it >Ruled “insane” >Found “not guilty” >May be released soon >Yes, really

@RodmanAi I'm retarded :( Couldn't figure out how to get it running locally.

Holy shit... Microsoft open sourced an inference framework that runs a 100B parameter LLM on a single CPU. It's called BitNet. And it does what was supposed to be impossible. No GPU. No cloud. No $10K hardware setup. Just your laptop running a 100-billion parameter model at human reading speed. Here's how it works: Every other LLM stores weights in 32-bit or 16-bit floats. BitNet uses 1.58 bits. Weights are ternary just -1, 0, or +1. That's it. No floats. No expensive matrix math. Pure integer operations your CPU was already built for. The result: - 100B model runs on a single CPU at 5-7 tokens/second - 2.37x to 6.17x faster than llama.cpp on x86 - 82% lower energy consumption on x86 CPUs - 1.37x to 5.07x speedup on ARM (your MacBook) - Memory drops by 16-32x vs full-precision models The wildest part: Accuracy barely moves. BitNet b1.58 2B4T their flagship model was trained on 4 trillion tokens and benchmarks competitively against full-precision models of the same size. The quantization isn't destroying quality. It's just removing the bloat. What this actually means: - Run AI completely offline. Your data never leaves your machine - Deploy LLMs on phones, IoT devices, edge hardware - No more cloud API bills for inference - AI in regions with no reliable internet The model supports ARM and x86. Works on your MacBook, your Linux box, your Windows machine. 27.4K GitHub stars. 2.2K forks. Built by Microsoft Research. 100% Open Source. MIT License

@Contrarian624 @CsTominaga What drugs are you on, and where can I score some?

Just like Apple when Steve Jobs returned after exile - so too will BSV make an extraordinary comeback when Satoshi @CsTominaga returns. (AKA Dr Wright) #BSV #Crypto #CSW #Satoshi

@LackJavalette @APompliano How does that glue smell like?

@APompliano BSV, not BTC

There is only one asset purpose-built for when the money printer is turned on. Bitcoin.

@aaronp613 Mac Studio M5 Ultra w/768gb RAM. Looking for a beast of a system to run openclaw local models.

Apple could announce WWDC 2026 as soon as this week! What do you hope to see announced at WWDC this year?

@GayBirdManGuy @ak2themax @AboveTP The data does not lie.

@cornokun @ak2themax @AboveTP LOLLLLLLLLLLLLLL YOUR GAME IS DYING

The Steam chart era is the worst era of gaming social media and it’s not even close. Enjoy what you enjoy & ignore this nonsense.

@GayBirdManGuy @ak2themax @AboveTP First three weekends. Not four.

@ak2themax @AboveTP Arc raiders set new highs their first 4 weekends lmao gg rekt

China's long range fishing fleet is causing widespread disaster around the world. This is off the coast of Peru. They don't care, they catch everything and wipe out the local fish population. Poor countries cannot stop them. China is a parasite.

Who of you was this? 😂

They voted for this. No sympathy.