maikeru

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maikeru

maikeru

@LearnedVector

ex ai researcher. making gpus go brrr. aspiring polyglot

Tham gia Temmuz 2013
981 Đang theo dõi1.8K Người theo dõi
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Anthropic
Anthropic@AnthropicAI·
AI can make work faster, but a fear is that relying on it may make it harder to learn new skills on the job. We ran an experiment with software engineers to learn more. Coding with AI led to a decrease in mastery—but this depended on how people used it. anthropic.com/research/AI-as…
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Grummz
Grummz@Grummz·
AI is getting pretty good.
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dax
dax@thdxr·
i didn't think this would be a big deal or happen so fast but i'm seeing teams nerf their own ability to use their brains because of llm dependence and when they run into a problem the llm can't fix they start doing really weird stuff
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Aporia
Aporia@0xaporia·
What Claude Code has revealed is that most people either have mediocre ideas or no ideas at all. The tool is a force multiplier for those who already know what they want to build and how to think through it systematically; it elevates competence, rewards clarity, and accelerates execution for people who would have gotten there anyway, just slower. If you have a sharp vision and can break it into coherent steps, Claude Code becomes an extension of your own capability. But there's another mode of use entirely. For people without that clarity, the appeal is precisely that the input can stay vague; you gesture at something, hit enter, and wait to see what comes out. This is structurally identical to a slot machine: low effort, variable reward, and that intermittent reinforcement loop that hooks the susceptible. So the same tool that elevates the focused and capable is also manufacturing a kind of gambling behavior in people prone to it.
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maikeru
maikeru@LearnedVector·
@Market_Mind_ @wabi build me an app that teaches me a new japanaese words and phrases everyday
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The Market Mind
The Market Mind@Market_Mind_·
Japanese Ways to stop overthinking
The Market Mind tweet media
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George Stock
George Stock@georgesttock·
Here’s how to do it with AI in 3 minutes: Upload a photo → generate with AI → post. No dropshipping. No crypto. No filming yourself. Just an AI system posting 2x/day in proven niches (AI, fitness, beauty, self-care). Done, this is how you make content that gains millions of followers in minutes. RT + reply ''Sound'' and i’ll send the full guide (must be following)
George Stock tweet media
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maikeru
maikeru@LearnedVector·
@dabit3 To be far any good engineer could have built this in a couple hours without ai. The time to build is not their value prop here but I get your point how this lowers barrier for everyone
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nader dabit
nader dabit@dabit3·
Something I wanted to see if Claude Opus 4.5 could do: clone a fully functional Billion $ SAAS product and make it at least 100x cheaper. The first product that came to mind was TypeForm because it's very popular, very expensive, and in theory, very simple. The result is OpenForm: a polished + functional and Open Source Typeform clone at ~100x less cost, that can be setup and deployed in ~15 minutes. The agent building this ran for ~35 minutes. Here are the details, technique, and the code:
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oliverb
oliverb@oliverbrocato·
I’ll die on this hill: Even on vacation, you and your team should still check in periodically. 2 minutes. Quick peek at Slack. Quick scan of Gmail. Anything urgent? Handle it or route it. If you completely disappear, you simply don’t care. Tell me I’m wrong.
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maikeru
maikeru@LearnedVector·
@tatealax Did the definition of organic shift? Paying tiktok influencers is still paid
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tateala
tateala@tatealax·
the new trend is people showing single feature apps making $400K/mo and acting like it's easy to replicate Guillaume nailed why this is misleading, you are not competing against solo founders, you are competing against Monkey Taps and studios with 50+ employees running performance marketing at scale These studios have mastered paid acquisition and dominating entire app store categories, you can't beat them at buying traffic and optimizing funnels, they're just too fucking good at it but what's their weakness? organic content distribution here's exactly how you'd compete against a Monkey Taps affirmation app activate 2000-50000 creators making content about your app across TikTok and Instagram, people posting faceless from their own accounts getting paid per view Content angles that work for affirmation apps: "morning routine" content showing your app as part of their 5am routine. "I replaced scrolling Instagram with affirmations and my life changed" "transformation content" with 30 days of daily affirmations and before/after mood tracking "comparison content" testing your app vs Monkey Taps side by side "aesthetic productivity" content for the "that girl" morning routine niche each creator posts 6-7 times per week testing different hooks, some get 500 views, some hit 500k you are creating conditions for multiple videos to break through every week 2000 creators posting 6 times a week = 48000 pieces of content per month, even if only 5% perform well, that's 120 winning videos driving consistent installs monkey taps wins the paid game but you win the organic game if you're in need of distribution and a marketing strategy DM me
Guillaume@iamgdsa

The new trend seems to be people showing a single feature app making $400K, like an alarm app or an affirmation app or a faxing app, and claiming how easy it is to build a utility app studio. The truth is that you cannot, and do not want to, compete against the big Turkish app studios. Or, to be fair, against other non Turkish single app companies like Alarmy at their own game. Monkey Taps , Spanish co, started back in 2014. They created an ecosystem of apps that goes after extremely competitive keywords, smart acquisition strategies, solid viral features, and ends up dominating a category that is nearly impossible to break into + their cross selling ecosystem, with scale, lets them consistently outcompete others in the Meta CPI/CPM game.l never beat their effective CPMs. Even an app like Alarmy probably has over 50+ employees, and most of them are performance marketing. Monkey Taps below, Spanish co, started back in 2014. They made an ecosystem of apps that goes after extremely competitive keywords, smart acquisition strategies, solid viral features, and ends up dominating a category that is nearly impossible to break into + their cross selling ecosystem, with scale, lets them consistently outcompete others in any CPI game.

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Oscar Le
Oscar Le@oscarle_x·
@VictorTaelin It is not that much gaining. Gemini 3 Flash is super fast, but when you do agentic coding, you gain just 20% percent of time probably. Because majority of time is spending on web searching, running terminal commands, which can't be faster.
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Jacob Rodri
Jacob Rodri@jacobrodri_·
This is going to be huge guys We are building the most powerful apps database where you’ll be able to see: - New winning apps - Their winning ads - Their viral videos - Niches with untapped potential - Track competitors And much more Early access? comment "🐱" and i’ll dm you
Jacob Rodri tweet media
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Dr. Dominic Ng
Dr. Dominic Ng@DrDominicNg·
Massive new @Nature study: castration increases lifespan across vertebrates (zoo mammals, rodents, wild animals). This aligns with historical human data: Korean eunuchs lived 14-19 years longer than their peers. Your move, @Bryan_Johnson.
Dr. Dominic Ng tweet media
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maikeru
maikeru@LearnedVector·
@ekuyda Any chance I get bumped up on the list? been super eager to try it!
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Nikita Bier
Nikita Bier@nikitabier·
@im_roy_lee Virality is reproducible product-led growth. What you’re describing is a media bump. The former has compounding benefits to a product. The latter is just short-term spurts of attention that need to be remanufactured every time.
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Roy
Roy@im_roy_lee·
[ THE CASE FOR VIRALITY ] There’s been a lot of noise the last month on X about attention as a strategy and whether or not it works. As one of the frontrunners getting most talked about here, I think it’s about time for me to offer my thoughts. Fundamentally, I believe that it has never been easier to scale an idea quickly, and it has never been harder to break through the noise. Pretty much every attention-first company is less than, or around a year old. The relevance behind us is hyper inflated because, despite being months old, we’re seen much more than some of the biggest companies. Virality compresses time, and a few big moments make a months-old startup feel, in your head, like we’ve been around for five years. The truth is, there is no “proof” that attention-first strategies don’t work because the experiment has barely even started. Startups fail all the time, but most of them just fail quietly. The key difference is that attention-first companies are hard to forget, so people obsess over their trajectory in a way they never would for 99% of startups who sit behind a waitlist for 2 years. The macro suggests the same too. There have never been more eight-nine-figure ARR bootstrapped companies. Most of these would not be possible without social media. Distribution today scales orders of magnitude faster than in any previous era. A “disappointing” few months for one or two early startups don’t disprove the entire model. And at a cultural level, the actual winners of the attention-era who have built the biggest empires are ALWAYS the most polarizing figures. It’s Donald Trump, Kai Cenat, iShowSpeed, the Kardashians. This is fundamentally different from the world these older operators come from. Short-form only became the dominant cultural medium a few years ago, and there are already countless examples of impressive businesses formed out of it. Nobody is claiming that virality is the only way to build a company or even necessarily the best way. But it is intellectually unserious to claim that it’s not a viable way when the entire experiment has just started. This time 12 months ago, I was studying for my midterms back at Columbia. Companies are built by building something and selling it. If you can go viral, you can sell something good much more quickly than you could in the past. That is the case for virality.
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maikeru
maikeru@LearnedVector·
@nizzyabi That’s at least 1.2M with inflation
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🚨Indian Gems
🚨Indian Gems@IndianGems_·
This is Huawei's latest laptop. Why are we so far behind in developing such technology?
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maikeru
maikeru@LearnedVector·
@atulit_gaur But the next likely token can literally just be “I don’t know?”
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atulit
atulit@atulit_gaur·
it is mathematically impossible for LLMs to not hallucinate it is because LLMs are conditional probability machines, it tries to choose the most likely next token, given the input, given the training distribution and given its internal weights. at its core, an llm does this: LLM(x) = argmax P(y|x) as you can see in this equation there is no term for factual correctness, only likelihood so if the model gets low-context or ambiguous input, it’s forced to "fill in the missing pieces" using statistics, not truth, and any probabilistic filling-in will sometimes mismatch the real world thus, this is a mathematical guarantee of hallucinations in LLMs
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