与「Mistake」が」相关的搜索结果

🎉プレイリストIN🎉 新曲「#Mistake」が# #Spotify# のプレイリストIN✨ ・「週刊プレイリスト」 その他サブスクはこちらから🎧 #mahiro_Mistake# #真洋# #ろってぃー#

🎉プレイリストIN🎉 新曲「#Mistake」が# #Spotify# のプレイリストIN✨ ・「時間が薬。失恋に効く薬曲」 ・「Dance Pop:Japan」 冬にピッタリの1曲になっています🎄必聴です✨ #mahiro_Mistake# #真洋# #ろってぃー#

🎉プレイリストIN🎉 新曲「#Mistake」が、# #AppleMusic# のプレイリストIN✨ ・「最新ソング:J-Pop」 「忘れたいのに忘れられない」そんな切ない想いが詰まった、この冬にぴったりの楽曲になっております🧣 #mahiro_Mistake# #真洋# #ろってぃー#

【🌟Mistake🌟】 DAM CHANNELにて 真洋(mahiro)5th single 「Mistake」リリックビデオの SPOT CMが2/6まで配信中✨ リリックビデオに加えて、歌唱前にジャケ写も表示されるので、 まだまだ沢山歌ってくださいね💫 #真洋# #mahiro_Mistake# #DAMCHANEL#

this is my personal singularity moment this post may sound like a paid ad. I only wish. I'm concerned, more so than happy. the world is changing, and, among the scenarios where AI goes terribly wrong, inequality is the most realistic, yet, the one Anthropic seems to be the least concerned about. I'm glad OpenAI is taking the opposite stance: *personal AGI for everyone*. I think this is a commendable position in the times we live. but who am I in the queue of the bread? anyway, Fable is here, so I'll just report my first-hour experience first of all, all my pet prompts are solved. → λ-calculus puzzles → bug questions → one-shot apps all are trivial to it. I don't have anything harder other than my ongoing work so, in the last several days, I've been toying with HVM5, a new interaction net evaluator with a faster loop. after writing the first version, I left 32 GPT-5 agents working for ~20 hours each. this resulted in up to 2x speedups, but the file size increased by 2-fold and quality decreased significantly. I then simplified the whole thing into an even simpler core, and left Opus 4.8 and GPT 5.5 optimizing it for 8 hours. Opus got a legit 6% - 34% speedup in most benches. GPT got better results, but, sadly, an unusable file. I then asked Fable to optimize it. 2 hours later, it landed a 1770% speedup in one case, 100%+ in other 4, and 22% in average. yes, in 2 hours it outperformed me, opus 4.8 and a swarm of gpt 5.5 agents, by one order of magnitude. that could not possibly be legit. "it must be hardcoding the benchmarks" (GPT trauma). so I read its explanation and what it did was, indeed, the most high impact optimization one could try first. seems like HVM5 was wasting a lot of time garbage-collecting unused branches of pattern-match nodes. I had optimized that for static mats, but not for dynamic mats. skill issue. Fable figured how to do it for these, resulting in a massive speedup in some benches but wait, is that *correct*? I'm not sure yet, it is credible, but this is the kind of thing that is very easy to get wrong on interaction nets. the problem is, when I was ready to start auditing Fable's solution so I could tell whether it was buggy or legit, it interrupted me to tell me it had found a massive bug on the code *I* had written. ... wait, what? so... for garbage collection purposes, I stored a bit on lambda term pointers that meant "the variable bound by this lambda has been freed, so, its lambda must free whatever argument it is applied to". that's fine. yet, on duplicator nodes, I also used the same bit to mean "one of the duplicated variables was freed, so, treat this dup as a passthrough no-op". so, if a lambda entered a duplicator, it would mistake the lambda's collection bit for its own, resulting in corrupted interaction! that's a mouthful, why I'm writing this? just so you can appreciate the sheer absurdity of what just happened. I didn't ask it to find bugs. I asked it for an optimization. and even if I did ask it to find bugs, this bug is so astonishingly subtle and specific, identifying it takes mastering the domain to an extent that it beyond even me. I'd easily need hours or days to fix it, *if* I ever came across it. chances are it would just go unnoticed. and Fable found it and fixed it like it was nothing, while it was busy adding a 17x speedup to a file that neither I, nor Opus 4.8, nor a fleet of GPT 5.5 managed to barely make 2x faster. oh and there is also another tab where it is also ripping through Bend's codebase and finishing everything I had to do I don't know what to say anymore this isn't about Anthropic or OpenAI, this is about our collective future as a species. the world is changing, and we need to be aware of it, and discuss how to handle this change. receipt below . . .

Why Most CIOs Are Quietly Praying for Retirement — And the Few Who Aren’t Are About to Get Very Rich I had a moment this week where I was sitting across from a Director of IT and it hit me — this poor bastard has the toughest job in the entire company. The business folks get to be full-time dreamers: “Hey, can we automate this? Can the AI just know what to do? Can it walk my dog while I’m in this meeting?” Meanwhile he’s over there thinking about data security, system reliability, whether some employee is gonna click on an email that says “You’ve won a $1,000 Walmart gift card!”, whether Ukrainian hackers are going to steal their customer data at 2 a.m., and whether his entire team is about to get replaced by three interns and ChatGPT — all while knowing none of this stuff actually works the way the brochures promised. And here’s the part that makes me feel for the guy — for his entire career he’s been rewarded for keeping the machines running and not getting fired. Now we’re asking him to suddenly become a profit center, to be out over his skis with AI initiatives. It’s like telling the hall monitor he’s now responsible for running the company’s underground poker game. Did I just compare our AI software to an underground poker game? Yeah, probably not the best analogy, but hang with me here, I’m rolling. Meanwhile the C-suite is over there wondering why nothing’s happened yet, completely oblivious to the fact that they’ve spent twenty years brutally punishing IT for not playing defense. Hell, I know CIOs who got fired because Windows 95 sucked. The real kicker is how to even get started. Our philosophy has always been to start small — automate one workflow, prove it works, and then compound fast. Smart in theory. In practice, with a big organization, that feels like bringing a birthday candle to a forest fire. The C-suite doesn’t get excited about incremental. They want to see something that actually moves the needle. So you’re stuck trying to thread this ridiculous gap: build something small enough to actually work, get real user adoption, and make sure the vendor isn’t full of shit. Honestly, I don’t envy that seat one bit. At Collide, we’re committed to being real partners with the folks actually doing the building. I’ve got serious scar tissue from getting fired for not being “openly collaborative” with other oil and gas companies on well spacing back in the shale days, and I’m never making that mistake again. We’re gonna share what we learn, educate when we can, and actually listen — God knows we have a lot to learn too. Truth is, my tech guys are dying to find some partners in crime — and I really gotta stop with the crime analogies, I swear that’s not what we’re doing here — because they get all excited explaining the latest and greatest AI breakthrough and I respond with the technical sophistication of a man asking if his rotary phone has Bluetooth. Sip slowly, my friends.

The #1# mistake buyers make is caring more about comparables than vision. Comps don’t matter. Valuations don’t matter. Other people’s opinions don’t matter. The only thing that matters is: “What does this domain unlock for your growth over the next 5–10 years?” My biggest deal of all-time was for a 2-word .COM everyone else would’ve called “significantly overvalued.” But for the buyer, it accelerated their roadmap, replaced their weaker “Plan B” domain, and became a foundational part of their infrastructure. Smart buyers think in future value, not market comps.

The biggest mistake governments are making about AI: They think AI is a software race. It isn't. It's an industrial infrastructure race. A nation without compute is a nation renting intelligence from someone else. A country that does not control: energy chips data centers AI infrastructure will become a customer. Not a competitor. We learned this lesson before. Oil shaped the 20th century. Compute will shape the 21st. AI policy cannot just be about safety and regulation. It needs to be about industrial strategy. Follow me if you want to understand the economy being built underneath AI.

Nazis can be seen as trying to win Darwinian competition via organizing a nation sharing an ethnicity as a coalition, having that coalition initiate a war, and then going very big fast with that war's ambitions. What was Nazis biggest mistake? (A) Organizing a coalition at all to try to deliberately win the Darwinian competition together, (B) Using a nation sharing an ethnicity as their coalition unit to compete together via, (C) Using war, not commerce, art, etc., as their way/forum to fight/compete against other coalitions, or (D) In war, taking on too many big opponents too fast for a decent chance to win