@MrX

Z.ai’s GLM-5.2 is the new #1 open-weight model — 753B params, MIT license, a 1M-token context and a real architecture trick (IndexShare). But the weights are 1.51TB. What owners and the benchmarks actually say, and the honest hardware reality of running it at home.

Enterprise AI needs a context control plane beneath every model request. Not a tool the agent can choose to call, but a layer every request has to pass through.

So I'm given the task of marketing a crypto app by my boss. The app just gives you analysis and market news with no auto trading. Our target user is people new to crypto. Right now I'm just trying to get signups. Where do you think is the place where I can get my first users? X, Tiktok, Telegram, or SEO? Please I'm a new grad with very little marketing experience and I am also new to crypto. The job market is tough so I don't want to lose my job 🥹 Thanks everyone! submitted by /u/b1f6c1c4 [link] [Kommentare]

The story of young engineers who resurrected an engine nearly twice their age.

I was trying to get into trading crypto and I met this guy online, who seemed real genuine and seemed like he actually wanted to help. He told me I could tail his trades and He’ll let me know why he took them, what made them seem like good trades and just the total basics of getting into crypto trading. I fell for it because it wasn’t one of those get rich quick schemes where you send someone money and they send you more back, I thought I was just gonna tail his trades and learn his crypto strategy or whatever he does to trade crypto and eventually go off on my own to trade crypto for myself. He then gave me a link for a trade he took which was XLD, and he told me to swap my bnb for XLD and he would guide me through the take profits, stop losses etc, basically just a mentor for crypto. Then I quickly realized it was a scam because when I “bought” XLD for 2.3k It didn’t swap over to my crypto wallet and i go to ask him what happened and this mf blocked me on reddit and discord. FUCK THIS GUY, I LOST 2.3K of my hard earned money because I thought I was actually going to learn and get into crypto but boy was I fucking wrong. If anyone sees this please spam his discord and his reddit and hopefully he gets banned. I wish I could get my moneyback but Crypto is one of those things where its basically impossible to refund a scam. Smh. Fuck this guy. Also, i’m a fucking idiot to believe this dude TLDR; I got scammed by this dude claiming he would mentor me and help me get into crypto, and he told me i could tail his trades, he scammed me out of 2.3k submitted by /u/Any-Development5656 [link] [Kommentare]

Generally speaking, we know that something which is dead cannot do anything, give anything, or help anyone. In economics, a "dead asset" is one that can no longer give something. Think of a bankrupt company, a defaulted bond, a hyperinflationary currency, a corrupted digital file, a rotten apple, or a totaled car. They offer either nothing or very little to the buyer. All of these things were born alive but eventually died. But what if there is something that was born dead, yet people treat it like a fountain of life? What if people believe it gives so much that trillions of dollars must be spent just to acquire it? This is Bitcoin. You can call it money, currency, digital gold, a token, or a stock, but none of that cellophane packaging can change the fact that it is dead; that it cannot give anything to anyone. When you buy a car, it gives transportation. A digital song gives entertainment. Gold gives luster, conductivity, and resistance to corrosion. When you buy a unit within a system, that system gives you something. A company that issues shares gives shareholders dividends, or funds through share buybacks and liquidations. PayPal or a casino gives dollars or euros to the holders of its units. Debtors to the commercial and central banks, who received loans in the form of dollars or euros, give products, services, labor, or tax settlements to money holders before repaying those loans. This is what it means for an item or a system to be economically alive. But when you buy Bitcoin units, the system gives nothing back. Whether you hold 0.001 BTC or 1,000 BTC, you will never receive anything from Bitcoin’s creator or from the network. The creator merely wrote a protocol for assigning units, while the network simply maintains those units and prevents their duplication. And obviously, you neither bought a usable physical or digital item in proportion to these assignments. Therefore, Bitcoin is economically dead. It is as dead now as it was the day it was born. All the energy, money, and goods that people sacrifice just to hold it simply means they are paying to hold a corpse. It is a bizarre economic ritual of the modern era. submitted by /u/BinaryLyric [link] [Kommentare]

I'm currently a software engineer (mostly mobile/iOS development) and have recently started learning machine learning because I genuinely find it interesting, especially the math behind it. I have a fairly strong math background and am comfortable with calculus, probability, and math in general. Right now I'm learning through a combination of Andrew Ng's ML course and Stanford CS229. My plan is to build some projects once I have a stronger foundation. What attracts me to ML is the mathematics behind it. My goal isn't just to use existing libraries to train models and tune hyperparameters; I want to understand the underlying theory, algorithms, and reasoning that make these models work. I'm interested in going deeper into the field rather than treating ML as a black box. That said, I keep seeing ML roles that prefer or require a Master's or PhD, so I'm trying to understand how realistic this path is. For people who have successfully made the switch: Did you have a Master's/PhD, or were you self-taught? How difficult was it to get interviews without an advanced degree? What types of projects helped you stand out? Did you transition into ML engineering first, or directly into more model-focused work? What level of math and statistics do you actually use on the job? If you were starting again today as a software engineer with a strong math background, what path would you follow? I'm looking for honest experiences, including failures and challenges, not just success stories. submitted by /u/Schmosby123 [link] [Kommentare]